Patent Application
20240385889
Today, cloud infrastructure services utilize many individual services to build a data center (e.g., to bootstrap various resources in a data center of a particular geographic region). A region is a logical abstraction corresponding to a localized geographical area in which one or more data centers are (or are to be) located. Building a data center (also referred to performing a “region build”) may include provisioning and configuring infrastructure resources and deploying code to those resources (e.g., to implement a variety of services). Any suitable number of data centers may be included in a region and therefore a region build may include operations for building multiple data centers. Bootstrapping operations for one service may depend on the availability of other functionality and/or services of the region. As the number of service teams and regions grows, the tasks performed for orchestrating provisioning and deployment drastically increase. Conventional tools for building a region require significant manual effort or automated techniques present drawbacks with respect to overhead, accuracy, and case of use. Improvements can be made.
Embodiments of the present disclosure relate to techniques for building a data center. Previous implementations had no centralized description from which to derive the operations needed to build a service. Instead, service build information was distributed across a myriad of configuration files. Current implementations lack a specification for how a service is built and include implementation details only. This leads to a lack of understanding of service builds and greatly increases the efforts required to unblock issues during a data center build. The present disclosure is directed to using execution target checkpoints defined within the service plan to track status of a service build at an execution target.
At least one embodiment is directed to a computer-implemented method (the “method,” for brevity). The method may comprise obtaining, by a cloud infrastructure orchestration system, a service plan defining a first release execution order for executing a release of one or more releases associated with a first process for bootstrapping a service of a plurality of services at one or more execution targets of a cloud-computing environment. The method may comprise generating, by the cloud infrastructure orchestration service, a directed acyclic graph based at least in part on a plurality of service plans comprising the service plan. In some embodiments, the directed acyclic graph defines a second release execution order for executing a set of releases comprising the one or more releases. The second release execution order may comprise the first release execution order for executing the one or more releases associated with the first process for bootstrapping the service. The method may comprise executing, by the cloud infrastructure orchestration service, the release at an execution target of the one or more execution targets as part of a second process for bootstrapping the plurality of services at the one or more execution targets of the cloud-computing environment. In some embodiments, the release may be executed according to the second release execution order. The method may comprise tracking, by the cloud infrastructure orchestration service, a state of the execution target based at least in part on executing the release at the execution target as part of the second process for bootstrapping the plurality of services at the one or more execution targets of the cloud-computing environment.
In some embodiments, the first release execution order may be defined based at least in part on a plurality of execution target checkpoint transitions. Each execution target transition may be associated with a release of the one or more releases and a transition between a pair of execution target checkpoints of a plurality of execution target checkpoints associated with the service.
In some embodiments, the service plan further specifies an ordered list of execution target checkpoints comprising a first execution target checkpoint and a second execution target checkpoint. The first execution target checkpoint may be associated with execution of a first release of the one or more releases associated with the first process for building the service. In some embodiments, the second execution target checkpoint may be associated with execution of a second release of the one or more releases associated with the first process for building the service.
In some embodiments, the state of the execution target may be associated with an execution target checkpoint, the execution target checkpoint may be associated with one or more build flags. In some embodiments, each build flag of the one or more build flags indicates that execution of a corresponding release associated with a corresponding execution target checkpoint has been successfully executed.
In some embodiments, the service is a first service and at least one release of the set of releases associated with the second process is associated with a second service. In some embodiments, a dependency of the at least one release associated with the second process on successful execution of the release associated with the first service is expressed based at least in part on a build flag of the one or more build flags associated with the execution target checkpoint.
In some embodiments, a release plan is generated that defines the second process for bootstrapping the plurality of services at the one or more execution targets of the cloud-computing environment. In some embodiments, the release plan is generated based at least in part on traversing the directed acyclic graph.
In some embodiments, tracking the state of the execution target comprises updating the state (e.g., the current checkpoint of execution target 1510) with a value corresponding to an execution target checkpoint (e.g., a current ET checkpoint of the execution target).
Another embodiment is directed to a cloud-computing service comprising one or more processors and memory storing instructions that, when executed by the one or more processors, cause the cloud-computing service to perform the method(s) disclosed herein.
Still another embodiment is directed to a non-transitory computer-readable medium storing computer-executable instructions that, when executed by one or more processors of a cloud-computing service, cause the cloud-computing service to perform the method(s) disclosed herein.
To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced.
In the following description, for the purposes of explanation, specific details are set forth in order to provide a thorough understanding of certain embodiments. However, it will be apparent that various embodiments may be practiced without these specific details. The figures and description are not intended to be restrictive. The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments or designs.
The adoption of cloud services has seen a rapid uptick in recent times. Various types of cloud services are now provided by various cloud service providers (CSPs). The term cloud service is generally used to refer to a service or functionality that is made available by a CSP to users or customers on demand (e.g., via a subscription model) using systems and infrastructure (cloud infrastructure) provided by the CSP. Typically, the servers and systems that make up the CSP's infrastructure and which is used to provide a cloud service to a customer are separate from the customer's own on-premises servers and systems. Customers can thus avail themselves of cloud services provided by the CSP without having to purchase separate hardware and software resources for the services. Cloud services are designed to provide a subscribing customer easy, scalable, and on-demand access to applications and computing resources without the customer having to invest in procuring the infrastructure that is used for providing the services or functions. Various different types or models of cloud services may be offered such as Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), Infrastructure-as-a-Service (IaaS), and others. A customer can subscribe to one or more cloud services provided by a CSP. The customer can be any entity such as an individual, an organization, an enterprise, and the like.
As indicated above, a CSP is responsible for providing the infrastructure and resources that are used for providing cloud services to subscribing customers. The resources provided by the CSP can include both hardware and software resources. These resources can include, for example, compute resources (e.g., virtual machines, containers, applications, processors), memory resources (e.g., databases, data stores), networking resources (e.g., routers, host machines, load balancers), identity, and other resources. In certain implementations, the resources provided by a CSP for providing a set of cloud services CSP are organized into data centers. A data center may be configured to provide a particular set of cloud services. The CSP is responsible for equipping the data center with infrastructure and resources that are used to provide that particular set of cloud services. A CSP may build one or more data centers.
Data centers provided by a CSP may be hosted in different regions. A region is a localized geographic area and may be identified by a region name. Regions are generally independent of each other and can be separated by vast distances, such as across countries or even continents. Regions are grouped into realms. Examples of regions for a CSP may include US West, US East, Australia East, Australia Southeast, and the like.
A region can include one or more data centers, where the data centers are located within a certain geographic area corresponding to the region. As an example, the data centers in a region may be located in a city within that region. For example, for a particular CSP, data centers in the US West region may be located in San Jose, California; data centers in the US East region may be located in Ashburn, Virginia; data centers in the Australia East region may be located in Sydney, Australia; data centers in the Australia Southeast region may be located in Melbourne, Australia; and the like.
Data centers within a region may be organized into one or more availability domains, which are used for high availability and disaster recovery purposes. An availability domain can include one or more data centers within a region. Availability domains within a region are isolated from each other, fault tolerant, and are architected in such a way that data centers in multiple availability domains are very unlikely to fail simultaneously. For example, the availability domains within a region may be structured in a manner such that a failure at one availability domain within the region is unlikely to impact the availability of data centers in other availability domains within the same region.
When a customer or subscriber subscribes to or signs up for one or more services provided by a CSP, the CSP creates a tenancy for the customer. The tenancy is like an account that is created for the customer. In certain implementations, a tenancy for a customer exists in a single realm and can access all regions that belong to that realm. The customer's users can then access the services subscribed to by the customer under this tenancy.
As indicated above, a CSP builds or deploys data centers to provide cloud services to its customers. As a CSP's customer base grows, the CSP typically builds new data centers in new regions or increases the capacity of existing data centers to service the customers' growing demands and to better serve the customers. Preferably, a data center is built in close geographical proximity to the location of customers serviced by that data center. Geographical proximity between a data center and customers serviced by that data center lends to more efficient use of resources and faster and more reliable services being provided to the customers. Accordingly, a CSP typically builds new data centers in new regions in geographical areas that are geographically proximal to the customers serviced by the data centers. For example, for a growing customer base in Germany, a CSP may build one or more data centers in a new region in Germany.
Building a data center (or multiple data centers) in a region is sometimes also referred to as building a region. The term “region build” is used to refer to building one or more data centers in a region. Building a data center in a region involves provisioning or creating a set of new resources that are needed or used for providing a set of services that the data center is configured to provide. The end result of the region build process is the creation of a data center in a region, where the data center is capable of providing a set of services intended for that data enter and includes a set of resources that are used to provide the set of services.
Building a new data center in a region is a very complex activity requiring coordination between various service teams. At a high level, this involves the performance and coordination of various tasks such as: identifying the set of services to be provided by the data center, identifying various resources that are needed for providing the set of services, creating, provisioning, and deploying the identified resources, wiring the resources properly so that they can be used in an intended manner, and the like. Each of these tasks further have subtasks that need to be coordinated, further adding to the complexity. Due to this complexity, presently, the building of a data center in a region involves several manually initiated or manually controlled tasks that require careful manual coordination. As a result, the task of building a new region (i.e., building one or more data centers in a region) is very time consuming. It can take time, for example, many months to build a data center. Additionally, the process is very error prone, sometimes requiring several iterations before a desired configuration of the data center is achieved, which further adds to the time taken to build a data center. These limitations and problems severely limit a CSP's ability to grow in a timely manner responsive to increasing customer needs.
Bootstrapping operations have been coordinated and orchestrated by an orchestrator (e.g., a Multi-Flock Orchestrator, an orchestration service, etc.). In previous implementations, the orchestrator attempted to automatically detect dependencies between operations. The orchestrator utilized various versions of configuration files and/or software artifacts and attempted to intelligently and automatically identify the artifacts and manner in which a data center build was performed. As a data center was built, the orchestrator utilized published capabilities (e.g., tags that could be toggled on or off to indicate availability of a resource or functionality) to drive these operations. However, both the automatic detection techniques and the use of capabilities included drawbacks.
Previous implementations of an orchestrator also lacked an exact plan of the work that may be needed (or is needed) to build a data center ahead of the actual build. The orchestrator utilized service build definitions that were spread across multiple flock configuration files (“flock configs”) and interpreted by the orchestrator at runtime. This caused the orchestrator to execute a non-predetermined number of releases, in a non-predetermined order, each of which published a non-predetermined number of capabilities per release. To compensate for this indeterministic behavior, manually curated micro-schedules were generated and used to track the work and order of operations necessary to build the data center. These micro-schedules were not machine executable nor derived from code. Service teams were not prevented from changing their build automation which could cause the existing micro-schedules to be invalidated. Additionally, it was not possible to determine exact behavior of a service build when configuration files for that service rely on external data.
In previous implementations, tasks were triggered by publishing capabilities. Capability availability was not held constant over a release leading to non-determinism in the planned activity if any optional capabilities were published mid-release. The use of optional capabilities made it difficult to determine when a release was expected to publish a certain capability of if a resource was ever going to be created. Service teams could also introduce changes that created unsatisfiable cyclic dependencies between services causing the build to deadlock or depend upon a capability that would never be published. For at least these reasons, it was impossible to determine when dependent releases would be unblocked. Heterogeneity in different regions also meant that there was no single plan for how a service should be bootstrapped. Rather, a different plan existed for each region furthering compounding the difficulty in understanding how the service is built, as capabilities might be depended upon or published in certain types of regions and not others.
Embodiments of the present disclosure may utilize a service plan and manifest (SPAMs) that serves as a deterministic specification for the bootstrapping process of a single service. A service plan and manifest (SPAM) provides a complete service build description that specifies the releases and the deterministic/explicit order of those releases that may be necessary (or are necessary) to build a service. The SPAM may include clear expectations for the progress expected by each transition (e.g., each release execution corresponding to a particular flock/phase/execution target). One or more services (e.g., all services to be bootstrapped within the region) may be associated with a corresponding SPAM. Information provided by these SPAMs may be utilized to eliminate various errors that can occur in a data center build by identifying issues early in the build lifecycle (e.g., upon SPAM submission) rather than during the build execution. SPAMs may be composed together by an orchestrator (e.g., a Multi-Flock Orchestrator, an orchestration service, etc.) and used to form a directed acyclic graph (DAG) of work (e.g., releases) that identifies the expected order of release executions that may be needed (or in some instances, is needed) to build the data center and capability dependencies between those releases.
A service plan may specify any suitable number of execution target (ET) checkpoints. Each ET checkpoint may be a reference point within the process of building the service (e.g., at an ET) that is associated with preconditions (e.g., required capabilities dependencies) and post-conditions (e.g., capability publications) that are expected to be met upon reaching a given checkpoint. The order of release execution may be identified in the service plan and expressed using ET checkpoint transitions. Each ET checkpoint transition (e.g., a transition from one ET checkpoint to another ET checkpoint) may be mapped to a corresponding infrastructure release or application release of the build. ET checkpoints may be associated with corresponding build flags that may be used to identify progress of the build. Executing a release may transition the ET from one ET checkpoint to another. Upon successful transition, one or more build flags that are associated with the release being executed at the ET may be set to indicate that the release was successfully executed (e.g., the corresponding infrastructure or application change corresponding to the release was successfully performed). The current ET checkpoint and build flags may be associated with a resource (e.g., an execution target resource) that is managed by the system. Using the SPAM enables an improved and deterministic plan to be generated for the build. Tracking the ET checkpoints defined within the SPAM enables the system to identify, at any suitable time, the progress already achieved and/or the amount and order of remaining work to be performed in an ongoing service and/or region/data center build.
A “region” is a logical abstraction corresponding to a geographical location. A region can include any suitable number of one or more execution targets.
A “phase” refers to a group of execution targets that can be executed at the same time.
An “execution target” refers to a unit (e.g., a set of devices, a tenancy, etc.) against which a release may be executed. In some embodiments, an execution target may be the smallest granular unit against which CIOS can execute a release. An execution target may be specific to a region and a tenancy. Execution targets may be aggregated into one or more phases. For some services, an execution target represents an “instance” of a service. A single service can be bootstrapped to each of one or more execution targets. An execution target may be associated with a set of devices (e.g., a data center).
A “release” refers to a representation of an intent to orchestrate a specific change to a service (e.g., deploy version 8, “add an internal DNS record,” etc.). In some embodiments, a release corresponds to a change type that indicates the release is an infrastructure change (e.g., provisioning) or an application change (e.g., a deployment). A release may target one or more phases or execution targets.
“Bootstrapping” is intended to refer to the collective tasks associated with provisioning and deployment of any suitable number of resources (e.g., infrastructure components, artifacts, etc.) corresponding to a single service.
A “service” refers to functionality provided by a set of resources. A set of resources for a service includes any suitable combination of infrastructure, platform, or software (e.g., an application) hosted by a cloud provider that can be configured to provide the functionality of a service. A service can be made available to users through the Internet.
An “artifact” refers to code being deployed to an infrastructure component (e.g., a physical or virtual host) or a Kubernetes engine cluster, this may include, but is not limited to, software (e.g., an application), configuration information (e.g., a configuration file) for an infrastructure component, or the like.
A “flock configuration file” or “flock config,” for brevity refers to a configuration file that describes a set of resources (e.g., infrastructure components and artifacts, also referred to as a “flock”) associated with a single service. A flock config may correspond to a single release (e.g., provisioning and/or deployment tasks that are to be performed as a unit). A flock config may correspond to an infrastructure release or an application release. A service may be built using any suitable number of releases and corresponding flock configs. A flock config may include declarative statements that specify one or more aspects corresponding to a desired state of the resources of the service for that release.
A “flock” refers to a set of CIOS managed resources or a set of execution targets that can be deployed as a unit. A flock may exist within an organizational unit referred to as a “project.”
“Service state” refers to a point-in-time snapshot of every resource (e.g., infrastructure resources, artifacts, etc.) associated with the service. The service state indicates status corresponding to provisioning and/or deployment tasks associated with service resources.
IaaS provisioning (or “provisioning”) refers to acquiring computers or virtual hosts for use, and even installing needed libraries or services on them. The phrase “provisioning a device” refers to evolving a device to a state in which it can be utilized by an end-user for their specific use. A device that has undergone the provisioning process may be referred to as a “provisioned device.” Preparing the provisioned device (installing libraries and daemons) may be part of provisioning; this preparation is different from deploying new applications or new versions of an application onto the prepared device. In most cases, deployment does not include provisioning, and the provisioning may need to be performed first. Once prepared, the device may be referred to as “an infrastructure component.”
IaaS deployment (or “deployment”) refers to the process of providing and/or installing a new application, or a new version of an application, onto a provisioned infrastructure component. Once the infrastructure component has been provisioned (e.g., acquired, assigned, prepared, etc.), additional software may be deployed (e.g., provided to and installed on the infrastructure component). The infrastructure component can be referred to as a “resource” after provisioning and deployment has concluded. Examples of resources may include, but are not limited to, virtual machines, databases, object storage, block storage, load balancers, and the like.
A “virtual bootstrap environment” (ViBE) refers to a virtual cloud network that is provisioned in the overlay of an existing region (e.g., a “host region”). Once provisioned, a ViBE is connected to a new region using a communication channel (e.g., an IPsec Tunnel VPN). Certain essential core services (or “seed” services) like a deployment orchestrator, a public key infrastructure (PKI) service, and the like can be provisioned in a ViBE. These services can provide the capabilities required to bring the hardware online, establish a chain of trust to the new region, and deploy the remaining services in the new region. Utilizing the virtual bootstrap environment can prevent circular dependencies between bootstrapping resources by utilizing resources of the host region. Services can be staged and tested in the ViBE prior to the physical region (e.g., the target region) being available.
A “Cloud Infrastructure Orchestration Service” (CIOS) may refer to a system configured to manage provisioning and deployment operations for any suitable number of services as part of a region build.
A “host region” refers to a region that hosts a virtual bootstrap environment (ViBE). A host region may be used to bootstrap a ViBE.
A “target region” refers to a region under build.
A “capability” identifies is a resource used during region build that signals that another resource, service, or feature is available, or that an event has occurred. By way of example, a capability can be published indicating that a resource is available for authorization/authentication processing (e.g., a subset of the functionality to be provided by a service). As another example, a capability can be published indicating the full functionality of the service is available. Capabilities may be used to identify functionality on which a resource or service depends and/or functionality of a resource or service that is available for use. A capability may be associated with an alphanumeric identifier and may be used to indicate the capability is available or unavailable.
“Publishing a capability” refers to “publishing” as used in a “publisher-subscriber” computing design or otherwise providing an indication that a particular capability is available (or unavailable). The capabilities are “published” (e.g., collected by a Capabilities Service, provided to a Capabilities Service, pushed, pulled, etc.) to provide an indication that functionality of a resource/service is available or that an event has occurred. In some embodiments, capabilities may be published/transmitted via an event, a notification, a data transmission, a function call, an API call, or the like. An event (or other notification/data transmission/etc.) indicating availability of a particular capability can be broadcasted/addressed (e.g., published) to a Capabilities Service.
A “Capabilities Service” may be a service configured to monitor and maintain capabilities data that indicates which capabilities are current available in a region. A Capabilities Service may be provided within a Cloud Infrastructure Orchestration System and may be used to identify what capabilities, services, features have been made available in a region, or which events have occurred within the region. The described Capabilities Service may service as a central repository/authority of all capabilities that have been published in the region (e.g., during a region build).
An “Orchestrator” is intended to refer to a service or system that initiates tasks involved in bootstrapping one or more services during a region build. A Multi-Flock Orchestrator (MFO), an example of an orchestrator, may be a computing component (e.g., a service) configured to coordinate events between components of the CIOS to provision and deploy services to a target region (e.g., a new region). An orchestrator may track relevant events (e.g., indicated through capabilities and/or skills as described herein) for each service of the region build and takes actions in response to those events (e.g., based on determining upstream dependencies have been met for a given release/skill, etc.).
A “Real-time Regional Data Distributor” (RRDD) may be a service or system configured to manage region data. This region data can be injected into flock configs to dynamically create execution targets for new regions.
A “Telemetry Service” may be a service or system that is configured to manage/monitor time series data associated with one or more services/resources and trigger (e.g., publish, store, etc.) various alarms and/or corresponding alarm states based at least in part on analyzing the time series data.
A “Skills Service” (also referred to as “Puffin”) may be a service or system that is configured to store planned and/or actual dependency relationships between services, resources, or units of functionality (also referred to as “service functionality”). It should be appreciated that the unit of functionality may relate to functionality provided by a computing component other than a service.
A “skill” may represent a functional unit that a service exposes and offers to consumers (e.g., other services). This functional unit (also referred to as “service functionality”) can include all or a subset of the total functionality associated with a service. In some embodiments, skills may be scoped where access is controlled based on access and/or authorization policies and/or based on an association with a particular namespace. A skill may be provided in multiple versions in which one or more aspects of the skill differs from other versions, where each skill version represents a specific implementation of the skill. Each skill version may be identifiable using a unique skill identifier. Skills are intended to replace (some or all) capabilities and enable enhanced and more accurate progress tracking of a region build as well as improved root cause analysis functionality when errors or unexpected events occur in the build. In some embodiments, a skill may be associated with one or more previously defined capabilities to provide backward compatibility with previous capabilities-based region build implementations. A skill may be monitored for health and may be configured to maintain health data. A “skill” may collectively refer to any suitable number of data structures (e.g., the skill metadata 404 of
A “fleet” refers to a logical environment (e.g., preproduction, production, etc.) to which a skill can be scoped. By way of example, a skill associated with a production fleet may be separate from a skill of the same name utilized with a preproduction fleet. A “project” may be similarly utilized to scope skills. In some embodiments, a skill may be scoped/applied to a particular environment based at least in part on any suitable combination of attributes such as skillID, skillversionID, compartmentID, namespaceID, producerServiceID, skillName, fleet, project, or the like, that collectively identify a particular application of a skill.
A “service plan specification” or “service plan,” for brevity, refers to a specification for a build implementation of a service. A service plan may include any suitable combination of build milestones, execution units, and flock configurations. A service plan details specific releases that may be needed (or that are needed) to build a service and the order by which the releases are to be performed to build the service. A service plan may separate inter-service coordination and intra-service coordination. A service plan may specify the expected state of a service at any suitable point of a region build.
A “service manifest” or “manifest,” for brevity, identifies the versions for flock configs and artifacts that are to be used to build a service. A service manifest may include a collection of service manifest items, each service manifest item identifying a particular flock config or artifact that may be needed (or is needed) to build a service. In some embodiments, a service manifest item may be associated with a git commit hash of the flock and all version declarations for any artifact that is required in application releases for that service's build.
A “SPAM” (also referred to as a “service build description”) refers to a combination of a service plan and a manifest that collectively provide a deterministic specification of the process for building a service. In some embodiments, a SPAM details a combination and order of releases that may be needed (or is needed) to build the service. A manifest of the SPAM may define all resources to be used for the releases, while the service plan specifies an order of release execution based on capability dependencies. A SPAM may be used to track compliance of a region build. A SPAM details the releases that may be necessary (or are necessary) to build a service where each release may be associated with pre and post-conditions. The preconditions may refer to capabilities that may (or in some instances, must) be present such that a release can be created that will result in the postconditions being satisfied. The post-conditions may be capabilities that should (or in some cases, must) be published as a consequence of the release succeeding. SPAMs may be created by service teams and are derived from YAML files they author. The SPAM may be delineated into discrete sections, including execution units which define transitions between well-defined points in the service's build, known as “build milestones.” A service may transition from one build milestone to the next by performing the releases defined by an execution unit. Execution units may specify the external dependencies (capabilities) that may be (or are) required to perform the releases defined within the unit. Build milestones may specify the capabilities published by the service that should (or in some cases, must) be made available once the service has reached that milestone. In some embodiments, the capabilities specified by a build milestone include capabilities that are intended for consumption by other services.
A “SPAM set” refers to a collection on SPAMs that are mutually compatible and/or that are previously associated with one another. A SPAM set may be used to derive a version set with which a directed acyclic graph may be generated and used to drive operations for building a data center. In some embodiments, a SPAM set may be associated with a scope and/or a regional context.
A “build milestone” refers to an entity defined in a service plan that identifies a synchronization point between the service build (e.g., the process for building a particular service) and the rest of the data center build. Build milestones may be defined coarsely to limit their number and provide a high-level overview of the process for building a service. As a non-limiting example, a set of build milestones for a service may include “absent” (e.g., a default starting milestone), “service functionality X available,” “service available,” and “service build complete.”
An “execution unit” refers to another entity of a service plan. One or more execution units may describe the process for transitioning from one build milestone to the next via a directed acyclic graph of CIOS releases (e.g., infrastructure and/or application releases).
An “execution target checkpoint” or “ET checkpoint,” for brevity, refers to a defined point in the data center build of a given execution target (e.g., a set of devices, a tenancy, etc.). An ET checkpoint may be associated with certain preconditions (e.g., required capability dependencies) and postconditions (capability publications) that are expected to have been met upon reaching that ET checkpoint. In some embodiments, steps identified within an execution unit may reference ET checkpoint transitions that may map logically to expected CIOS releases (e.g., infrastructure releases or application releases).
A “region archetype” may represent an overall structure of a region (e.g., an ONSR region, a single-availability-domain-region, a first region in a realm) that could be used to impact a service's installation. In some embodiments, a service plan may reference dimensions of a region archetype to conditionally change the service plan definition.
A “version set” may be used to define all flock configuration file and artifact versions across all services in a specific regional context (e.g., given a specific region such as “region1” and a specific version set identifier such as “golden” or “break glass”). A version set may be composed of many version set items, each of which may specify a flock and the artifacts for that flock. These entities may identify the existence of SPAMs and SPAM sets. By way of example, in some embodiments, a version set may be associated with a corresponding SPAM set. Any suitable version set item may be associated with a SPAM from which it was derived and/or corresponding to a common service.
“Static flock analysis” refers to an execution of a static analysis of code (e.g., that identifies data center infrastructure components as objects using a declarative configuration language) to infer capability publications and/or dependencies. In some embodiments, a static flock analysis may be performed utilizing an infrastructure-as-code software tool (e.g., Terraform®). In some embodiments, this software tool may generate one or more data structures (e.g., directed acyclic graphs) that represent these dependencies/publications. Each node in the graph may correspond to a flock config and/or a release, with edges identifying capability publications and/or dependencies between releases.
In some examples, techniques for implementing a Cloud Infrastructure Orchestration Service (CIOS) are described herein. Such techniques, as described briefly above, can be configured to manage bootstrapping (e.g., provisioning and deploying software to) infrastructure components within a cloud environment (e.g., a region). In some instances, the CIOS can include computing components (e.g., a CIOS Central and a CIOS Regional) that may be configured to manage bootstrapping tasks (provisioning and deployment) for a given service and an Orchestrator (e.g., a multi-flock orchestrator) configured to initiate/manage region builds (e.g., bootstrapping operations corresponding to multiple services in a region/data center).
CIOS enables region/data center building and world-wide infrastructure provisioning and code deployment with minimal manual run-time effort from service teams (e.g., beyond an initial approval and/or physical transportation of hardware, in some instances). The high-level responsibilities of CIOS include, but are not limited to, coordinating region builds in an automated fashion with minimal human intervention, providing users with a view of the current state of resources managed by the CIOS (e.g., of a region, across regions, world-wide, etc.), and managing bootstrapping operations for bootstrapping resources within a region.
The CIOS may provide view reconciliation, where a view of a desired state (e.g., a desired configuration) of resources may be reconciled with a current/actual state (e.g., a current configuration) of the resources. In some instances, view reconciliation may include obtaining state data to identify what resources are actually running and their current configuration and/or state. Reconciliation can be performed at a variety of granularities, such as at a service level.
CIOS can perform plan generation, where differences between the desired and current state of the resources are identified. Part of plan generation can include identifying the operations that would need to be executed to bring the resources from the current state to the desired state. Once the user is satisfied with a plan, the plan can then be marked as approved or rejected. Thus, users can spend less time reasoning about the plan and the plans are more accurate because they are machine generated. Plans are almost too detailed for human consumption; however, CIOS can provide this data via a sophisticated user interface (UI).
In some examples, CIOS can handle execution of change management by automatically executing the approved plan. Once an execution plan has been created and approved, engineers may no longer need to participate in change management unless CIOS initiates roll-back. CIOS can handle rolling back to a previous service version by automatically generating a plan that returns the service to a previous (e.g., pre-release) state (e.g., when CIOS detects service health degradation while executing).
CIOS can measure service health by monitoring alarms and executing integration tests. CIOS can help teams quickly define roll-back behavior in the event of service degradation, which it can later execute automatically. CIOS can automatically generate and display plans and can track approval. CIOS can combine the functionality of provisioning and deployment in a single system that coordinates these tasks across a region build. CIOS can discover dependencies between execution tasks at every level (e.g., resource level, execution target level, phase level, service level, etc.) through a static analysis (e.g., including parsing and processing content) of one or more configuration files. Using these dependencies, CIOS can generate various data structures from these dependencies that can be used to drive task execution (e.g., tasks regarding provisioning of infrastructure resources and deployment of artifacts across the region).
Today, during Large Scale Events (LSEs) (e.g., events in which a substantial error, blockage, or delay is experienced in a region build), incident management and region build operators frequently incur wide-spread overhead and sometimes delays, e.g., in collecting status, attribution of the issue, assessment of impacts, and the recovery of services, due to the heavily human-based and non-systemic approach of conventional approaches. Due to the complexity of the various dependencies between services, it can be extremely difficult and time intensive for operators to identify the contributing cause of the event. This causes delays in remediation as well as the ability to assess when an event has concluded. Similarly, building a region includes challenges in which human involvement may be utilized to troubleshoot and/or detect of failures or blocking situations. Conventionally, it is difficult for service teams to determine what dependencies exist for their service. Both the dependencies the service may have on other services, and vice versa. Additionally, service teams have incomplete indicators ahead of an actual region build as to whether their region build design will have critical issues (such as cyclic dependencies) that prevent or delay the build of their service.
Real-time Regional Data Distributor (RRDD) 104 may be configured to maintain and provide region data that identifies realms, regions, execution targets, and availability domains. In some cases, the region data may be in any suitable form (e.g., JSON format, data objects/containers, XML, etc.). Region data maintained by RRDD 104 may include any suitable number of subsets of data which can individually be referenceable by a corresponding identifier. By way of example, an identifier “all_regions” can be associated with a data structure (e.g., a list, a structure, an object, etc.) that includes a metadata for all defined regions. As another example, an identifier such as “realms” can be associated with a data structure that identifies metadata for a number of realms and a set of regions corresponding to each realm. In general, the region data may maintain any suitable attribute of one or more realm(s), region(s), availability domains (ADs), execution target(s) (ETs), and the like, such as identifiers, DNS suffixes, states (e.g., a state of a region), and the like. The RRDD 104 may be configured to manage region state as part of the region data. A region state may include any suitable information indicating a state of bootstrapping within a region. By way of example, some example region states can include “initial,” “building,” “production,” “paused,” or “deprecated.” The “initial” state may indicate a region that has not yet been bootstrapped. A “building” state may indicate that bootstrapping of one or more flocks within the region has commenced. A “production” state may indicate that bootstrapping has been completed and the region is ready for validation. A “paused” state may indicate that CIOS Central 108 or CIOS Regional 110 has paused internal interactions with the regional stack, likely due to an operational issue. A “deprecated” state may indicate the region has been deprecated and is likely unavailable and/or will not be contacted again.
CIOS Central 108 is configured to provide any suitable number of user interfaces with which users (e.g., user 109) may interact with CIOS 102. By way of example, users can make changes to region data via a user interface provided by CIOS Central 108. CIOS Central 108 may additionally provide a variety of interfaces that enable users to: view changes made to flock configs and/or artifacts, generate and view plans, approve/reject plans, view status on plan execution (e.g., corresponding to tasks involving infrastructure provisioning, deployment, region build, and/or desired state of any suitable number of resources managed by CIOS 102. CIOS Central 108 may implement a control plane configured to manage any suitable number of CIOS Regional 110 instances. CIOS Central 108 can provide one or more user interfaces for presenting region data, enabling the user 109 to view and/or change region data. CIOS Central 108 can be configured to invoke the functionality of RRDD 104 via any suitable number of interfaces. Generally, CIOS Central 108 (also referred to as a “provisioning and deployment manager”) may be configured to manage region data, cither directly or indirectly (e.g., via RRDD 104). CIOS Central 108 may be configured to compile flock configs (and/or SPAMs) to inject region data as variables within the flock configs (and/or SPAMs). CIOS Central 108 may be instructed (e.g., by Orchestrator 106) to perform one or more releases (e.g., infrastructure or application releases) corresponding to flock configs.
Each instance of CIOS Regional 110 may correspond to a module configured to execute bootstrapping tasks that are associated with a single service of a region (e.g., a data center such as host region 103). CIOS Regional 110 can receive desired state data from CIOS Central 108. In some embodiments, desired state data may include a flock config that declares (e.g., via declarative statements) a desired state of resources associated with a service. CIOS Central 108 can maintain current state data indicating any suitable aspect of the current state of the resources associated with a service. In some embodiments, CIOS Regional 110 can identify, through a comparison of the desired state data and the current state data, that changes that may be (or are) needed to one or more resources. For example, CIOS Regional 110 can determine that one or more infrastructure components need to be provisioned, one or more artifacts deployed, or any suitable change that may be (or is) needed to the resources of the service to bring the state of those resources in line with the desired state. As CIOS Regional 110 performs bootstrapping operations, it may publish data indicating various capabilities of a resource as they become available. A “capability” identifies a unit of functionality associated with a service. The unit could be a portion, or all of the functionality to be provided by the service. By way of example, a capability can be published indicating that a resource is available for authorization/authentication processing (e.g., a subset of the functionality to be provided by the resource). As another example, a capability can be published indicating the full functionality of the service is available. Capabilities can be used to identify functionality on which a resource or service depends and/or functionality of a resource or service that is available for use. In some embodiments, CIOS Regional 110 may transmit data indicating a state transition of a skill. By way of example, in some embodiments, CIOS Regional 110 performs bootstrapping operations which result in publishing a skill (e.g., transmitting skill metadata including a skill state value indicating the skill is installed). The skill metadata may be transmitted to Puffin (e.g., Puffin Regional 120) and used to update the skill state of the corresponding skill.
Capabilities Service 112 is configured to maintain capabilities data that indicates 1) what capabilities of various services are currently available, 2) whether any resource/service is waiting on a particular capability, 3) what particular resources and/or services are waiting on a given capability, or any suitable combination of the above. Capabilities Service 112 may provide an interface with which capabilities data may be requested. Capabilities Service 112 may provide one or more interfaces (e.g., application programming interfaces) that enable it to transmit capabilities data to Orchestrator 106, CIOS Regional 110 (e.g., each instance of CIOS Regional 110), Puffin Regional 120, and/or Puffin Central 118. In some embodiments, Capabilities Service 112 may store capabilities data in a data store that is accessible to one or more components of CIOS 102. Orchestrator 106, CIOS Regional 110 (e.g., each instance of CIOS Regional 110), Puffin Regional 120, and/or Puffin Central 118, and/or any suitable component or module of CIOS Regional 110 may be configured to request capabilities data from Capabilities Service 112 or otherwise obtain capabilities data (e.g., from a data store configured to store capabilities data generated by the Capabilities Service 112). Although the Capabilities Service 112 is depicted as being a separate component of CIOS 102, it should be appreciated that, in some embodiments, the functionality provided by Capabilities Service 112 may be provided, in whole or in part, as part of the Skills Service via any suitable combination of Puffin Central 118 and Puffin Regional 120.
In some embodiments, each regional component such as CIOS Regional 110, Capabilities Service 112, Puffin Regional 120, and/or Virtual Bootstrap Environment 116 may be one of many regional components. Each regional component may be specific to a given region (e.g., as depicted in
In some embodiments, Orchestrator 106 (an example of which may be a multi-flock orchestrator, an orchestration service, etc.) may be configured to drive region build efforts. In some embodiments, Orchestrator 106 can manage information that describes which flock config versions and/or artifact versions are to be utilized to bootstrap a given service within a region (or to make a unit of change to a target region). In some embodiments, Orchestrator 106 may manage any suitable combination of flock configs and/or service plans. In some embodiments, Orchestrator 106 may be configured to monitor (or be otherwise notified of) changes to the region data managed by Real-time Regional Data Distributor 104. In some embodiments, receiving an indication that region data has been changed may cause a region build to be triggered by Orchestrator 106. In some embodiments, Orchestrator 106 may collect various flock configs, artifacts, and/or SPAMs to be used for a region build. Some, or all, of the flock configs and/or SPAMs may be configured to be region agnostic. That is, the flock configs and/or SPAMs may not explicitly identify what regions to which the flock is to be bootstrapped. In some embodiments, Orchestrator 106 may trigger a data injection process through which the collected flock configs and/or SPAMs are recompiled (e.g., by CIOS Central 108). During recompilation, operations may be executed (e.g., by CIOS Central 108) to cause the region data maintained by Real-time Regional Data Distributor 104 to be injected into the config files and/or SPAMs. Flock configs and/or SPAMs can reference region data through variables/parameters without requiring hard-coded identification of region data. The flock configs and/or SPAMs can be dynamically modified at run time using this data injection rather than having the region data be hardcoded, and therefore, and more difficult to change.
In some embodiments, Orchestrator 106 can perform a static flock analysis in which the flock configs and/or service plans are parsed to identify dependencies between resources, execution targets, execution target checkpoints, phases, and flocks, and in particular to identify circular dependencies that need to be removed. In some embodiments static flock analysis (SFA) data corresponding to this analysis may be stored (e.g., via DB 312) for subsequent use. In some embodiments, Orchestrator 106 can generate any suitable number of data structures based on the dependencies identified. These data structures (e.g., directed acyclic graph(s), linked lists, etc.) may be utilized by CIOS 102 to drive operations for performing a region build. By way of example, these data structures may collectively define an order by which services are bootstrapped within a region. An example of such a data structure is discussed further below with respect to Build Dependency Graph 338 of
In some embodiments, one or service plan and manifests (SPAMs) may be utilized by the Orchestrator 106. A service plan and manifest may provide a deterministic specification of a build description for a service than previously provided by one or more flock configs. While flock configs specify aspects of a single release associated with a single service, a service plan may provide a single specification of the order and conditional requirements for executing all of the releases that may be needed (or are needed) to build a given service. Previous implementations of flock configs included optional dependencies which allowed for a degree of indeterministic behavior with respect to the order of operations performed during a region build. The inclusion of optional dependencies may require the Orchestrator 106 to perform multiple passes of the build dependency graph, resulting in wasteful processing. These types of dependencies make it difficult, if not impossible, for the system to track region build progress, identify remaining operations yet to be performed, and/or identify build completion. Service plans and manifests (SPAMs) may be utilized to eliminate at least some of the drawbacks to previous indeterministic approaches.
SPAMs (one SPAM corresponding to one service to be bootstrapped in the region) allow service teams to describe the corresponding operations that may be needed (or are needed) to build their service and may allow for separation between internal coordination (e.g., coordination of operations internal to the service) and external coordination (e.g., coordination of operations between components of different services). A number of visualizations may be provided (e.g., via Orchestrator 106 or any suitable component of CIOS 102) via one or more user interfaces. One visualization may depict a directed acyclic graph describing the build operations internal to a given service, and a separate visualization may depict a directed acyclic graph describing the order of build operations corresponding to multiple services (e.g., all services of the region/data center). As a specific example, one or more visualization can present a region-level directed acyclic graph (DAG) including only external coordination (e.g., an order of operations corresponding to coordination between services) while omitting operations that are internal with respect to each service. This DAG, for example, may depict nodes corresponding to one service's capabilities (or skills) on which other services depend, while excluding nodes corresponding to capability (or skill) dependencies between service components/functional units of the same service.
A SPAM may include an external interaction interface that includes a service build definition that includes a number of build milestones. Each build milestone may be associated with a set of capabilities (and/or skills) that the service is expected to publish upon reaching a given milestone. To transition between build milestones, the SPAM may include execution units that encapsulate a directed acyclic graph (DAG) of one or more releases, each release being equivalent to operations previously defined with a single flock config. Each execution unit may define a set of build time dependencies that identify one or more capabilities (and/or skills) that are required by at least one of the releases of the execution unit.
A SPAM may include a service build implementation. An execution unit of the SPAM may describe one or more releases that may be needed (or are needed) to build a service, with potentially multiple execution units being defined. Each execution unit may be associated with one or more execution target checkpoint transitions, each of which may be used to specify the expected capabilities that should be available before the time of the release and the capabilities that should be published as the result of performing the release.
In some embodiments, the Orchestrator 106 may be configured to aggregate SPAMs corresponding to each service to be deployed in a region to generate a larger directed acyclic graph (e.g., the Build Dependency Graph 338 of
In some embodiments, Puffin Central 118 may provide a number of user interfaces with which one or more skills can be defined. A skill may be used with, or in lieu of, previously capabilities and enables improvements over previous capabilities-based implementations. In contrast with capabilities, skills may be scoped (e.g., controllable through access and authorization policies), versioned, and attributed to a particular service and/or contact. Skills may be associated with a lifecycle and may be monitored for health and are designed to be more highly visible/accessible than capabilities. Puffin Central 118 may provide an authoritative registry for skills. Various user interfaces managed by Puffin Central 118 may be utilized to define, maintain, and manage skills that each service offers, as well as their dependency relationships with other services. Puffin Central 118 may be utilized to declare and persist strongly defined metadata of services in a versioned manner. This metadata may be used to generate a blueprint for build-time and run-time dependencies. These blueprints can be used to validate build plans, to drive orchestration decisions during region build, and to improve time-to-engage and time-to-diagnose measures during region build and/or Large-Scale Events (LSEs).
Puffin Central 118 may be configured to serve as a source of truth for services and may maintain metadata including each service's upstream and downstream dependencies and service team contact information and methods for each service across regions and realms (e.g., a set of regions). Each skill may represent a function unit that a service exposes and offers to consumers (e.g., other services). In some embodiments, skills may be scoped where access is controlled based on access and/or authorization policies and/or based on an association with a particular namespace. A skill may be associated with multiple versions in which one or more aspects of the skill differs from previous versions, where each skill version represents a specific implementation of the skill. Each skill version may be identifiable using a unique skill identifier. In some embodiments, Puffin Central 118 may be configured to generate a skill corresponding to a previously defined capability in order to provide backward compatibility with previous capabilities-based region build implementations.
In some embodiments, Puffin may maintain compatibility between skills and capabilities, such that any suitable combination of the two may be utilized to define a process by which a service is to be built. Based on maintaining a mapping between skills and/or capabilities a service publishes, Puffin may ensure that a skill may be transitioned based on capabilities and/or a capability may be published due to a state change of a corresponding skill. In some embodiments, Puffin may generate “shadow skills” (e.g., system-generated skills that represent corresponding capabilities) and/or shadow capabilities (e.g., system-generated capabilities that publish when a corresponding skill is transitioned to an installed state). These features, provided by Puffin, enable the orchestrator to use any suitable combination of skills and/or capabilities to drive orchestration during a region build (e.g., during a process for building a data center).
In some embodiments, a skill may be mapped to one or more capabilities. Puffin Regional 120 may be configured to publish and/or store skills metadata based on capabilities data published (or stored) by the Capabilities Service 112. In some embodiments, Puffin Regional 120 may publish capabilities data to the Capabilities Service 112 and/or store such data based at least in part on publishing a skill or identifying a skill has transitioned to or is otherwise associated with a particular state. In some embodiments, some services may utilize flock configurations that express progress using capabilities, while other services may utilize a service plan and manifest that defines a deterministic build process in which progress is expressed with capabilities and/or skills. Using the mapping (or multiple mappings) between skills and capabilities, Puffin Regional 120 may enable a region build to be performed using any suitable combination of capabilities and/or skills to indicate that 1) service or resource functionality is available, 2) a particular event has transpired, 3) a particular fact is true, 4) a condition has been met, or any suitable combination of the above. This mapping or mappings enable CIOS 102 to perform a region build/data center build using any suitable combination of capabilities and/or skills, enabling service teams to transition from capabilities-based implementations to skills-based implementations gradually.
In some embodiments, any suitable computing component of the Puffin Service (e.g., Puffin Central 118 and/or Puffin Regional 120) may be configured to monitor the health and/or lifecycle of a skill according to a predefined skill lifecycle. Health monitoring may be performed using one or more alarms that are associated with a given skill. In some embodiments, a telemetry service (e.g., an example of alarm service(s) 122) may utilize an application programming interface provided by the Puffin Service (including Puffin Central 118 and/or Puffin Regional 120) when an alarm is triggered. As another example, the Puffin Service (e.g., Puffin Regional 120) may request alarm data from the alarm service(s) 122 and/or from storage locations at which the alarm service(s) 122 store the alarm data. The Puffin Service may present, via one or more user interfaces, information related to the health of a skill based on the alarms corresponding to the alarm data obtained and their corresponding association to a given skill.
In some embodiments, the Puffin Service (e.g., Puffin Central 118 and/or Puffin Regional 120) may expose one or more application programming interfaces (APIs) with which validation operations may be performed. By way of example, a SPAM describing the build process with respect to one or more services may be provided via a given API (e.g., by the Orchestrator 106). The Puffin Service (e.g., Puffin Central 118) may execute any suitable operations for validating that all services and skills identified in the SPAM have been previously registered with the Puffin Service and that the build process defined in the SPAM does not violate previously defined dependency relationships maintained by the Puffin Service.
Additionally, or alternatively, Orchestrator 106 may perform any suitable validation check such as determining whether each flock config and/or artifact identified in a given service's manifest is referenced within the service's corresponding service plan and/or that no flock config and/or artifact is referenced within the service plan that is not referenced within the manifest. Orchestrator 106 may perform validation operations (e.g., a static analysis including parsing the service plan) to determine that a service plan lacks circular dependencies. If a circular dependency is found within a service plan, Orchestrator 106 may provide a notification and/or restrict the service plan and corresponding manifest from being utilized. In some embodiments, such restrictions may include restricting the service plan and manifest from being added to a SPAM set (e.g., a set of SPAMs to be used to perform a region build). In some embodiments, the Orchestrator 106 may perform any suitable validation operations to ensure that SPAMs of a SPAM set and/or a SPAM that is being considered as an addition to a preexisting SPAM set are mutually compatible. This may include analyzing the SPAM set (alone or with a SPAM that is being considered for addition) to ensure that the SPAMs of the SPAM set do not include circular dependencies.
In some embodiments, a user can request that a new region (e.g., target region 114) be built. This can involve bootstrapping resources corresponding to a variety of services. In some embodiments, target region 114 may not be communicatively available (and/or secure) at a time at which the region build request is initiated. Rather than delay bootstrapping until such time as target region 114 is available and configured to perform bootstrapping operations, CIOS 102 may initiate the region build using a virtual bootstrap environment (e.g., Virtual Bootstrap Environment (ViBE) 116. ViBE 116 may be an overlay network that is hosted by host region 103 (a preexisting region that has previously been configured with a core set of services and which is communicatively available and secure). Orchestrator 106 can leverage resources of the host region 103 to bootstrap resources to the ViBE 116 (generally referred to as “building the ViBE”). By way of example, Orchestrator 106 can provide instructions through CIOS Central 108 that cause an instance of CIOS Regional 110 within a host region (e.g., host region 103) to bootstrap another instance of CIOS Regional within the VIBE 116. Once the CIOS Regional within the ViBE is available for processing, bootstrapping the services for the target region 114 can continue within the VIBE 116. When target region 114 is available to perform bootstrapping operations, the previously bootstrapped services within ViBE 116 may be migrated to target region 114. Utilizing these techniques, CIOS 102 can greatly improve the speed at which a region is built by drastically reducing the need for any manual input and/or configuration to be provided. In some embodiments, any suitable combination of the components depicted as part of CIOS 102 may individually be examples of the cloud services of
In order to bootstrap a new region (e.g., target region 114 of
When the target region is available to provide bootstrapping operations, the VIBE 202 can be connected to the target region so that services in the ViBE can interact with the services and/or infrastructure components of the target region. This will enable deployment of production level services, instead of self-contained seed services as in previous systems, and may be connected over the internet to the target region. Conventionally, a seed service was deployed as part of a container collection and used to bootstrap dependencies necessary to build out the region. Using infrastructure/tooling of an existing region, resources may be bootstrapped (e.g., provisioned and deployed) into the VIBE 202 and connected to the service enclave of a region (e.g., host region 204) in order to provision (reserve and/or configure) hardware and deploy services until the target region is self-sufficient and can be communicated with directly. Utilizing the ViBE 202 allows for meeting the dependencies and providing the services needed to be able to provision/prepare infrastructure and deploy software while making use of the host region's resources in order to break circular dependencies of core services.
Orchestrator 206 (an example of Orchestrator 106 of
The method 200 may begin at step 1, where Orchestrator 206 may instruct CIOS Central 214 (e.g., an example of CIOS Central 108 and CIOS Central 214 of
At step 2, CIOS Central 214 may provide the ViBE flock config via a corresponding request to CIOS Regional 216. CIOS Regional 216 may parse the ViBE flock config to identify and execute specific infrastructure provisioning and deployment operations at step 3.
In some embodiments, the CIOS Regional 216 may utilize additional corresponding services for provisioning and deployment. For example, at step 4, CIOS Regional 216 CIOS Regional may instruct deployment orchestrator 218 (e.g., an example of a core service, or other write, build, and deploy applications software, of the host region 204) to execute instructions that in turn cause Capabilities Service 208, Worker 210, and in some embodiments Puffin Regional 209, to be bootstrapped within ViBE 202.
At step 5, capabilities data may be transmitted to the Capabilities Service 208 (from the CIOS Regional 216, Deployment Orchestrator 218 via the Worker 210 or otherwise) indicating that resources corresponding to the ViBE flock are available. Capabilities Service 208 may persist this data. In some embodiments, the Capabilities Service 208 adds this information to a list it maintains of available capabilities with the ViBE. By way of example, the capability provided to Capabilities Service 208 at step 5 may indicate the Capabilities Service 208 and Worker 210 (and in some embodiments, Puffin Regional 209) are available for processing. In some embodiments, skills metadata may be transmitted to Puffin Regional 209 indicating that any suitable combination of functionality corresponding to the Capabilities Service 208, Worker 210, and/or Puffin Regional 209 is available.
At step 6, Orchestrator 206 may identify that the Capabilities Service 208, Worker 210, and/or Puffin Regional 209 are available based on receiving or obtaining data (an identifier corresponding to a capability and/or skill) from the Capabilities Service 208 and/or Puffin Regional 209.
In some embodiments, published capabilities may be processed by Puffin Regional 209 (e.g., Puffin Regional 120 of
Although some embodiments describe shadow skill generation being conducted at build time, it should be appreciated that the Puffin Service may generate shadow skills at any suitable time and according of a variety of methods. By way of example, historical capabilities data (e.g., capabilities data historically published during one or more previous region builds) may be obtained by the Puffin Service (e.g., Puffin Central 118 and/or Puffin Regional 120 of
At step 7, as a result of receiving/obtaining the data at step 6, the Orchestrator 206 may instruct CIOS Central 214 to bootstrap a DNS service (e.g., DNS 212) to the VIBE 202. The instructions may identify or include a particular flock config and/or SPAM corresponding to the DNS service.
At step 8, the CIOS Central 214 may instruct the CIOS Regional 216 to deploy DNS 212 to the ViBE 202. In some embodiments, the DNS flock config and/or SPAM for the DNS 212 may be provided by the CIOS Central 214.
At step 9, Worker 210, now that it is deployed in the ViBE 202, may be assigned by CIOS Regional 216 to the task of deploying DNS 212. Worker may execute a declarative infrastructure provisioner in the manner described above in connection with
At step 10, the Deployment Orchestrator 218 may instruct Worker 210 to deploy DNS 212 in accordance with the operations identified at step 9. As depicted, Worker 210 proceeds with executing operations to deploy DNS 212 to ViBE 202 at step 11. At step 12, Worker 210 may notify Capabilities Service 208 (via a capability) or Puffin Regional 209 (directly, or via Capabilities Service 208 and using a skill) that DNS 212 is available in ViBE 202. Orchestrator 206 may subsequently identify that the resources associated with the ViBE flock config and the DNS flock config are available any may proceed to bootstrap any suitable number of additional resources to the ViBE.
After steps 1-12 are concluded, the process for building the ViBE 202 may be considered complete and the ViBE 202 may be considered built and ready for additional bootstrapping (e.g., the bootstrapping of various cloud services such as cloud services 1356 of
The method 300 may begin at step 1, where user 302 (e.g., a service team member) may interact with any suitable number of user interfaces managed by Puffin Central 340 (e.g., Puffin Central 118 of
At step 2, user 303 may utilize any suitable user interface provided by CIOS Central 304 (an example of CIOS Central 108 and CIOS Central 214 of
At step 3, CIOS Central 304 may execute operations to send the change to RRDD 306 (e.g., an example of RRDD 104 of
At step 5, Orchestrator 310 (an example of the Orchestrator 106 and/or 206 of
At step 6, detecting the change in region data may trigger Orchestrator 310 to obtain a version set (e.g., a version set associated with a particular identifier such as a “golden version set” identifier) identifying a particular version for each flock config and a particular version for each artifact to be used to build the region. The version set may be obtained from DB 312. As flock configs and/or artifacts evolve and change over time, multiple versions of each may be maintained, and certain versions of each may be used for a region build. The version set may be persisted in DB 312 such that Orchestrator 310 may identify which versions of flock configs and artifacts to use for building a region (e.g., a ViBE region, a Target Region/non-ViBE Region, etc. The flock configs (e.g., all versions of the flock configs) and/or artifacts (e.g., all versions of the artifacts) may be stored in DB 308, DB 312, or any suitable data store accessible to the CIOS Central 304 and/or Orchestrator 310.
In some embodiments, Orchestrator 310 may identify any suitable number of SPAMs (collectively referred to as a “SPAM set”) corresponding to the infrastructure to be provisioned and artifacts to be deployed as part of a region build. In some embodiments, each SPAM may identify versions corresponding to one or more flock configs and/or one or more artifacts that may be needed (or are needed) to build a single service. In embodiments in which one or more SPAMs are utilized, the SPAM(s) (or any suitable portion of the SPAM(s)) may be stored within DB 312 and utilized to identify the particular flock config and/or artifact versions to be utilized for building the region. In some embodiments, the flock configs and/or artifact versions of a SPAM set may be included in the version set and stored within DB 312. This enables some service teams to utilize a set of flock configs to define their service's build implementation while other service teams may choose to utilize a SPAM to define their service's build implementation.
In some embodiments, any suitable flock version sets and/or version set items may be derived from any suitable number of SPAMs and the Orchestrator 310 may be configured to verify compliance of a flock's behavior (e.g., the build/orchestration operations identified within a flock config) complies with the process defined by a corresponding SPAM. The Orchestrator 310 may be configured to ingest SPAMs which provide the information that may be required (or in some cases, that is required) to build an up-front plan of work and to introduce better guardrails than those available in previous implementations. Any suitable number of SPAMs may be aggregated into corresponding SPAM sets in a similar way that flocks may be aggregated into version sets. SPAM sets may enforce the invariant that all SPAMs within the set are mutually compatible and compose together to form a viable graph of releases required to build a region. In some embodiments, SPAM sets may be used within a given regional context to improve service build progress tracking. SPAM operations may be validated before they are applied and rejected if they are invalid, unlike version set item operations which were unconditionally applied. The utilization of SPAMs may enable the Orchestrator 310 to build a deterministic plan of work prior to building a region, to block updates that would jeopardize or break an ongoing or future build, to improve the tracking of process of a service build, to detect deviations of flock behavior from the SPAM's specification, and to alert operators of deviations and status.
At step 7, Orchestrator 310 may request CIOS Central 304 to recompile each of the flock configs associated with the version set (including any suitable number of flock configs identified by a SPAM of a SPAM set) with the current region data. In some embodiments, the request may indicate a version for each flock config and/or artifact.
At step 8, CIOS Central 304 may obtain current region data from the DB 308 (e.g., directly, or via Real-time Regional Data Distributor 306) and retrieve any suitable flock config and artifact in accordance with the versions requested by Orchestrator 310.
At step 9, CIOS Central 304 may recompile the obtained flock configs with the region data obtained at step 8 to inject those flock configs with current region data. CIOS Central 304 may return the compiled flock configs to Orchestrator 310. In some embodiments, CIOS Central 304 may simply indicate compilation is done, and Orchestrator 310 may access the recompiled flock configs via RRDD 306.
In some embodiments, at step 10, Orchestrator 310 may perform a static flock analysis of the recompiled flock configs (and/or SPAMs). As part of the static flock analysis, Orchestrator 310 may parse the flock configs (and/or SPAMs) (e.g., using a library associated with a declarative infrastructure provisioner (e.g., Terraform®, or the like)) to identify dependencies. Data generated by the static flock analysis (e.g., “SFA data,” including the identified dependencies) may be stored for subsequent use. From the analysis and the dependencies identified (e.g., the SFA data), Orchestrator 310 may generate any suitable number of data structures (e.g., directed acyclic graphs) that identify an order for releases identified in the flock configs (or from any suitable portion of one or more service plans, such as from a flock config entity of the service plan). A DAG that is generated based on a flock config (and/or any portion of a SPAM including, but not limited to flock config entity 800 of
In some embodiments, Build Dependency Graph 338 may be a region-level dependency graph that includes every release that may be needed (or that is needed) for every service to be bootstrapped within the region/data center. Each node in the Build Dependency Graph 338 may correspond to bootstrapping any suitable portion of a service. By way of example, each node of the Build Dependency Graph 338 may correspond to a single release. The specific bootstrapping order (e.g., the order of release execution) may be identified based at least in part on the dependencies. In some embodiments, the dependencies may be expressed as an attribute of the node and/or indicated via edges of the graph that connect the nodes. Orchestrator 310 may traverse the Build Dependency Graph 338 (e.g., beginning at a starting node) to drive the operations of the region build. Any suitable portion of a service DAG and/or the Build Dependency Graph 338 may be presented via one or more user interfaces (e.g., one or more interfaces provided by any suitable component of CIOS 102 of
In some embodiments, Orchestrator 310 may utilize a cycle detection algorithm to detect the presence of a cycle (e.g., service A depends on service B and vice versa). Orchestrator 310 can identify orphaned capabilities dependencies. For example, Orchestrator 310 can identify orphaned nodes of the Build Dependency Graph 338 that do not connect to any other nodes. Orchestrator 310 may identify falsely published capabilities (e.g., when a capability was prematurely published, and the corresponding functionality is not actually yet available). Orchestrator 310 can detect from the graph that one or more instances of publishing the same capability exist. In some embodiments, any suitable number of these errors may be detected and Orchestrator 310 (or another suitable component such as CIOS Central 304) may be configured to notify or otherwise present this information to users (e.g., via an electronic notification, a user interface, or the like). In some embodiments, Orchestrator 310 may be configured to force delete/recreate resources to break circular dependencies and may once again provide instructions to CIOS Central 304 to perform bootstrapping operations for those resources and/or corresponding flock configs.
A starting node of the Build Dependency Graph 338 may correspond to building the ViBE 316 (or individual services within the ViBE), a second node may correspond to bootstrapping DNS. The steps 11-16 may correspond to deploying (via deployment orchestrator 317, an example of the deployment orchestrator 218 of
Orchestrator 310 may continue traversing the Build Dependency Graph 338 to identify that one or more releases corresponding to deploying DNS 322 are to be executed. Steps 17-22 may be executed to deploy DNS 322 (an example of the DNS 212 of
At step 22, a capability (or skill) may be published and/or stored indicating that DNS 322 is available. In some embodiments, CIOS Regional 314 and/or Deployment Orchestrator 317 may initially communicate the availability of the capability or skill (e.g., to Capabilities Service 318 or Puffin Regional 342, respectively). If a skill is published, Puffin Regional 342 may transmit data to Capabilities Service 318 to indicate one or more corresponding capabilities are published. Upon detecting the publishing of a capability (e.g., via data provided by Capabilities Service 318, perhaps triggered based on skill-related data provided by Puffin Regional 342), Orchestrator 310 may recommence traversal of the Build Dependency Graph 338. On this traversal, the Orchestrator 310 may identify that any suitable portion of an instance of CIOS Regional (e.g., an example of CIOS Regional 314) is to be deployed to the VIBE 316. In some embodiments, steps 17-22 may be substantially repeated with respect to deploying CIOS Regional (ViBE) 326 (an instance of CIOS Regional 314, CIOS Regional 110 of
Upon detecting the CIOS Regional (ViBE) 326 is available, Orchestrator 310 may recommence traversal of the Build Dependency Graph 338. On this traversal, the Orchestrator 310 may identify that a deployment orchestrator (e.g., Deployment Orchestrator 330, an example of the Deployment Orchestrator 317) is to be deployed to the ViBE 316. In some embodiments, steps 16-21 may be substantially repeated with respect to deploying Deployment Orchestrator 330. Information that identifies a capability may be transmitted to the Capabilities Service 318 (e.g., by CIOS Regional 314, worker 320, and/or Puffin Regional 342), indicating that Deployment Orchestrator 330 is available.
After Deployment Orchestrator 330 is deployed, ViBE 316 may be considered available for processing subsequent requests. Upon detecting Deployment Orchestrator 330 is available, Orchestrator 310 may instruct subsequent bootstrapping requests to be routed to ViBE components rather than utilizing host region components (components of host region 332). Thus, Orchestrator 310 can continue traversing the Build Dependency Graph 338, at each node instructing release execution to the ViBE 316 via CIOS Central 304. CIOS Central 304 may transmit release requests CIOS Regional (ViBE) 326 to effectuate release execution as instructed by Orchestrator 310.
At any suitable point during this process, Target Region 334 may become available. Indication that the Target Region is available may be identifiable from region data for the Target Region 334 being provided by the user 303 (e.g., as an update to the region data). The availability of Target Region 334 may depend on establishing a network connection between the Target Region 334 and external networks (e.g., the Internet). The network connection may be supported over a public network (e.g., the Internet), but use software security tools (e.g., IPSec) to provide one or more encrypted tunnels (e.g., IPSec tunnels such as tunnel 336) from the VIBE 316 to Target Region 334. As used herein, “IPSec” refers to a protocol suite for authenticating and encrypting network traffic over a network that uses Internet Protocol (IP) and can include one or more available implementations of the protocol suite (e.g., Openswan, Libreswan, strongSwan, etc.). The network may connect the VIBE 316 to the service enclave of the Target Region 334.
Prior to establishing the IPSec tunnels, the initial network connection to the Target Region 334 may be on a connection (e.g., an out-of-band VPN tunnel) sufficient to allow bootstrapping of networking services until an IPSec gateway may be deployed on an asset (e.g., bare-metal asset) in the Target Region 334. To bootstrap the Target Region's network resources, Deployment Orchestrator 330 can deploy the IPSec gateway at the asset within Target Region 334. The Deployment Orchestrator 330 may then deploy VPN hosts at the Target Region 334 configured to terminate IPSec tunnels from the ViBE 316. Once services (e.g., Deployment Orchestrator 330, Service A, etc.) in the VIBE 316 can establish an IPSec connection with the VPN hosts in the Target Region 334, bootstrapping operations from the ViBE 316 to the Target Region 334 may begin.
In some embodiments, the bootstrapping operations may begin with services in the ViBE 316 provisioning resources in the Target Region 334 to support hosting instances of core services as they are deployed from the ViBE 316. For example, a host provisioning service may provision hypervisors on infrastructure (e.g., bare-metal hosts) in the Target Region 334 to allocate computing resources for VMs. When the host provisioning service completes allocation of physical resources in the Target Region 334, the host provisioning service may publish information indicating a capability that indicates that the physical resources in the Target Region 334 have been allocated. The capability may be published to Capabilities Service 318 via CIOS Regional (ViBE) 326 (e.g., by Worker 328).
With the hardware allocation of the Target Region 334 established and posted to Capabilities Service 318, CIOS Regional (ViBE) 326 can orchestrate the deployment of instances of core services from the VIBE 316 to the Target Region 334. This deployment may be similar to the processes described above for building the ViBE 316, but using components of the ViBE (e.g., CIOS Regional (ViBE) 326, Worker 328, Deployment Orchestrator 330) instead of components of the Host Region 332 service enclave (e.g., CIOS Regional 314 and Deployment Orchestrator 317). The deployment operations may generally correspond to steps 17-22 described above.
As a service is deployed from the ViBE 316 to the Target Region 334, the DNS record associated with that service may correspond to the instance of the service in the VIBE 316. The DNS record associated with the service may be updated at any suitable time to complete deployment of the service to the Target Region 334. Said another way, the instance of the service in the ViBE 316 may continue to receive traffic (e.g., requests) until the DNS record is updated. A service may deploy partially into the Target Region 334 and publish information indicating a capability (e.g., to Capabilities Service 318) that the service is partially deployed. For example, a service running in the ViBE 316 may be deployed into the Target Region 334 with a corresponding compute instance, load balancer, and associated applications and other software, but may need to wait for database data to migrate to the Target Region 334 before being completely deployed. The DNS record (e.g., managed by DNS 322) may still be associated with the service in the ViBE 316. Once data migration for the service is complete, the DNS record may be updated to point to the operational service deployed in the Target Region 334. The deployed service in the Target Region 334 may then receive traffic (e.g., requests) for the service, while the instance of the service in the ViBE 316 may no longer receive traffic for the service.
At any suitable time during method 300, Puffin Regional 209 may receive and/or obtain alarm data from one or more alarm services (e.g., the alarm service(s) 344, an example of the alarm service(s) 122 of
In some embodiments, service metadata 402 may include any suitable data corresponding to a service. Service metadata 402 may include any suitable attribute and corresponding value of a service, while skill metadata 404 may similarly include any suitable attribute and corresponding value of a skill. An association between service metadata 402 and skill metadata 404 may indicate a relationship between a service and a skill (e.g., that the service is expected to publish the skill during build or run time). As depicted in
Skill metadata 404 may include any suitable number of data structures (e.g., data structures 410-420). In some embodiments, skill data structure 410 may include attributes and values corresponding to any suitable combination of a skill ID, a skill name, a skill fleet, a major version, an isDeprecated indicator, one or more capabilities (e.g., a set of capability identifiers), a useInstead indicator, a compartment ID, a producer ID, a namespace ID, and a recovery ring level. In some embodiments, the values stored for compartment ID, producer ID, and/or namespace ID in the skill data structure 410 may match the compartment ID, service name, or namespace name of service metadata 402, respectively. A match between one or more of the values of these attributes may be used as an association between skill metadata 404 and service metadata 402 (indicating that the corresponding service is expected to publish the skill at some point).
Skill version data structure 412 may be associated with skill data structure 410 based at least in part on matching values of skill ID of skill version data structure 412 and ID of skill data structure 410. Skill version data structure 412 may include attributes and values corresponding to any suitable combination of an ID (for a skill version), a skill ID (e.g., a unique identifier of the skill), a major version and/or a minor version that individually or collectively identify a particular implementation of the skill, a patch version (e.g., a version identifier that identifies a skill to be used to correct a previously erroneous skill version), a deprecated indicator (indicating whether the skill is deprecated or not), a health check attribute (that references one or more instances of alarm data of one or more instances of health check data structure 414), an installation state (indicating a state of installation such as declared, selected, installing, installed, embargoed, retired, uninstalling), a health state (e.g., indicating the health of the skill such as unknown, healthy, unhealthy, etc.), and an observability attribute. The observability attribute may be used to store any suitable data identifying operations or datapoints required to gather telemetry, alarm, and/or log data for the skill version. Skill version data structure 412 may be associated with health check data structure 414 which may be configured to maintain any suitable number of alarm labels that is/are associated with the skill. By way of example, the healthCheck attribute of skill version data structure 412 may reference any suitable number of health check data structures corresponding to one or more instances of health check data structure 414.
In some embodiments, the health check data structure 414 may include any suitable combination of an alarm identifier (alarm ID, indicating a unique identifier for the alarm), an alarm label name (a name of the alarm), a compartment identifier (compartment ID, indicating a compartment to which the alarm is scoped), a continuation token (a token with which alarm transition history may be obtained), namespace identifier (namespace ID, indicating a particular namespace to which the alarm is scoped), and a status value (indicating a health status corresponding to the alarm). Alarm data corresponding to multiple alarms may be maintained in the health check data structure 414. By way of example, alarm ID may include a list of multiple alarm IDs corresponding to a list of alarm label names stored within the alarm label name attribute. The compartment ID attribute may also be a list of compartment IDs corresponding to the alarms and labels of the alarm ID and alarm label name ID attributes of the health check data structure 414. In some embodiments, multiple sets of attributes alarmID, alarmLabelName, compartmentID, continuationToken, and status may be stored, with each set of attributes corresponding to a single alarm.
In some embodiments, health check data structure 414 may store data corresponding to one or more alarm service(s) (e.g., the alarm service(s) 344 of
Skill data structure 410 may be associated with skill metadata data structure 416. Skill metadata data structure 416 may include attributes and values for any suitable combination of an ID (for an instance of the skill metadata data structure 416), a Jira queue, an owner contact, an org leader, and a phonebook ID. A phonebook ID may be an identifier corresponding to a separate system that is configured to store contact data. Skill metadata data structure 416 may be used to store any suitable contact data (e.g., name, email, address, phone number, etc.) for an entity (e.g., a service team member) that is associated with the skill and the service with which the skill is associated.
Skill data structure 410 may be associated with skill consumer data structure 418. Skill consumer data structure 418 may include attributes and values for any suitable combination of an ID (for the skill consumer), a type, a status, a consuming region, a version requirement, a consuming skill ID, a consuming service ID. Skill consumer data structure 418 may be configured to store any suitable information on services and/or skills which depend on the skill defined by skill metadata 404.
Skill data structure 410 may be associated with skill group data structure 420. Skill group data structure may include attributes and values for any suitable combination of an ID (for the skill group), a skill group name, and a set of one or more skill IDs associated with the skill group.
Each of the data structures 406-420 may be stored in one or more data stores and a data structure may be identified and obtained (e.g., via a lookup and/or query operation) based at least in part on a value stored in another data structure through the associations discussed above. By way of example, all skills associated with a service may be identified through a query of the data store(s) for all skill data structures that are associated with a producer ID matching the ID from service data structure 406 of service metadata 402.
Although a number and particular combination of data structures are presented in
Each data structure of
Any suitable number of instances of skill metadata 404 (corresponding to individual skills) may be associated with a single instance of service metadata 402 and may be used to represent a process of deploying the service in which the order of deployment tasks is represented via the instances of skill metadata 404. Each skill corresponding to an instance of skill metadata 404 for a service may be tracked, updated, or otherwise analyzed to present information regarding the deployment process for the service, to drive deployment of the service, to validate a build plan or the Build Dependency Graph 338 of
A SPAM may be represented by a combination of the data structures (e.g., data structures 502-508) depicted in
In some embodiments, SPAM data structure 502 may include any suitable data corresponding to a SPAM. Any suitable portion of SPAM data structure 502 may be included in service plan data structure 504 and/or service manifest 506. As depicted in
The service plan data structure 504 may represent a service plan and the entities included in a service plan. Service plan data structure 504 may include a “buildMilestones” entity with a corresponding value that includes an ordered list of build milestone identifiers (e.g., names, alphanumeric strings, etc.). The “buildMilestones” attribute may identify, include, or otherwise correspond to the build milestones entity 600 of
Code segment 602 identifies a build milestone entitled “absent,” a corresponding description, and a list of capability publications indicating the capabilities that should (and in some instances, must) be published prior to transitioning to this build milestone (also referred to as “capability dependencies” or the capabilities on which this build milestone depends). The list of capability publications, in this instance, is empty, indicating that no capability publications are expected prior transitioning to the build milestone “absent.”
Code segment 604 identifies a build milestone entitled “service-partial,” a corresponding description, and a list of capability publications indicating the capabilities that should (and in some instances, must) be published prior to transitioning to this build milestone. The list of capability publications, in this instance, includes “serviceA_namespace”, indicating that publication of the “serviceA_namespace” capability is expected/required before to transitioning to the build milestone “service-partial” may occur.
Code segment 606 identifies a build milestone entitled “service-available,” a corresponding description, and a list of capability publications indicating the capabilities that should (and in some instances, must) be published prior to transitioning to this build milestone. The list of capability publications, in this instance, includes “serviceA_backend,” indicating that publication of the “serviceA_backend” capability is expected/required before transitioning to the build milestone “service-available” may occur.
Code segment 608 identifies a build milestone entitled “complete,” a corresponding description, and a list of capability publications indicating the capabilities that should (and in some instances, must) be published prior to transitioning to this build milestone. The list of capability publications, in this instance, is empty indicating that no capability publications are expected prior to transitioning to the build milestone “complete” may occur.
In some embodiments, each build milestone specifies the capabilities publications that the service should have published before reaching a particular build milestone. A set of build milestones may indicate a high-level overview of a process for building a service and may be utilized/consumed by external consumers (e.g., other services that depend on the service to which the build milestones relate). Build milestones may be defined and utilized to express portions of functionality are available for the service. This may allow other service builds to proceed when the functionality on which the other service depends is available, rather than waiting for the service in question to become fully available. Build milestones may be used for coordination between services. When building a service does not involve coordination with other services, the service plan for that service may include no build milestones or a number of default build milestones (e.g., “absent” and “complete”). In some embodiments, the build milestones defined in every service plan to be used for a region build may be used to generate a high-level graph and/or sequencing diagram. This may provide service teams a graph view of simplified complexity with which the region build process may be more easily understood and synthesized. As a non-limiting example, a graph/diagram generated using the build milestones for each corresponding service may include a reduced number of nodes (e.g., 3 per service, 4 per service, depending on the service's build milestone implementation) from the Build Dependency Graph 338 of
Returning to
As depicted in
Each execution unit may include one or more external capability dependencies. By way of example, execution unit 702 specifies external capability dependencies on a set of external capability dependencies as depicted at 705. These external capability dependencies may include one or more capabilities that should (or in some instances, must) be published prior to transitioning from one build milestone (e.g., the “absent” build milestone) to another (e.g., the “service-partial” build milestone). The set of external capability dependencies may be the union of external capabilities requirements for all releases defined in the step section of the corresponding execution unit. As depicted in
Any suitable number of external capability dependencies may be specified. In some embodiments, an execution step may include no external capability dependencies.
Each execution unit may indicate one or more capabilities that are expected to be published when execution of the releases corresponding to the execution unit have been completed. By way of example, execution unit 702 specifies a set of capability publications at 707 indicating a superset of all capabilities that are expected to have been published once execution of the releases indicated in step section 706 have been completed. The capability publications may be additionally or alternatively defined as being associated with the build milestone to which the execution relates.
Each execution unit may include any suitable number of steps (or groups of steps) that, when executed, move the service from one build milestone to another. By way of example, execution unit 702 specifies step section 706 which includes an InfraAppPair step type. An InfraAppPair step specifies one or more infrastructure releases expressed using an alias for the ET (e.g., ET: Alias flock_DP/phase_DP/alarms_et) and flock/phase execution target (ET) transition (e.g., Transition: absent→DP_complete_alarms_infra). Each release reference may denote, for each ETAlias, the ET checkpoint transition being made with the release. In some embodiments, the Orchestrator (e.g., Orchestrator 106 of
Other step types may be utilized. For example, a parallel step type may be used if region build phases have no dependencies between one another and may be executed in parallel (e.g., substantially simultaneously, concurrently, and/or overlapping execution) should their external dependencies be resolved at substantially the same time. A serial step type may be used if two distinct phases (e.g., with distinct names) have a direct dependency between one another (e.g., the corresponding releases of which are expected to be executed serially).
All of the expected publications of a build milestone (e.g., the build milestone that is transitioned to) may be published when all of the releases of a corresponding execution unit that caused the transition are complete. By way of example, the capability “serviceA_namespace” may be published upon transitioning to build milestone “service-partial” as indicated in Code segment 604 of
As another example, execution unit 704 defines a transition from build milestone “service-partial” to build milestone “service-available. As depicted, execution unit 704 includes step section 708 which includes multiple InfraAppPair step types, each of which includes steps corresponding to one or more infrastructure releases and application releases. By way of example, an infra step type of the InfraAppPair step type at 712 includes a step corresponding to execution a release, where the execution of the release is expressed via an ET checkpoint transition (e.g., absent→CP_complete_region_infra) as depicted at 715. InfraAppPair step types (e.g., the InfraAppPairs step types depicted at 712 and 714) may be grouped and ordered using a serial step type as indicated at 710. The serial step type indicated at 710 may be used to indicate that the infrastructure releases and application releases corresponding to InfraAppPair 712 (each release/step being expressed via an ET checkpoint transition as depicted at 715) must be executed prior to executing the infrastructure releases and application releases corresponding to InfraAppPair 714. Although not depicted, other step types are contemplated. By way of example, a parallel step type (e.g., indicated with “Parallel”) may be used in lieu of the serial step type at 710 to indicate that execution of the infrastructure releases and application releases of InfraAppPair 712 may be performed in parallel (e.g., concurrently) with the infrastructure releases and application releases of InfraAppPair 714. In some embodiments, an InfraAppPair identifier (e.g., InfraAppPair 712) may be used to indicate a set of one or more infrastructure releases of a corresponding “infra” section of the InfraAppPair, must be executed prior to the application release of a corresponding “app” section of the InfraAppPair. These step types may be nested in any suitable manner to indicate sequential or concurrent execution of one or more releases. The steps of the execution units defined within execution unit entity 700 may be used to specify a deterministic execution order of releases (e.g., expressed with ET checkpoint transitions corresponding to a release execution).
Checkpoints section 810 may define any suitable number of checkpoints. These checkpoints may be grouped by type (e.g., “Infra” indicating an infrastructure change type, “App” indicating an application change type), as depicted, or each checkpoint may indicate a corresponding change type. In some embodiments, the order by which the checkpoints are provided within checkpoints section 810 may define an order by which the checkpoints are executed. In some embodiments, when the checkpoints indicate a corresponding change type, infrastructure change related releases may be ordered ahead of any application change related releases, even when an application change related release is listed within checkpoints section 810 in a position ahead of an infrastructure release. Each checkpoint may indicate a corresponding flock configuration file as depicted at 812, external and/or internal capability dependencies as depicted at 814, and capability publications as depicted at 816 for each release. Providing these mappings within the flock config entity 800 enables the execution unit entity 700 of
One of the challenges of previous build implementations is understanding what progress should happen each time a release is executed against a particular phase and change type of a flock, particularly when the phase has optional capability dependencies. For each release that the Orchestrator (e.g., Orchestrator 106 of
The service plan 902 may include any suitable combination of the build milestones entity 600 of
Build milestones 906-912 may individually be associated with a set of external capabilities on which transitioning to the build milestone depends. These capabilities may include the expected published capabilities that are relevant for external services (e.g., service 914, including the other services of the region build). As a non-limiting example, build milestone 906 may depend on capabilities set 916 (including one or more capabilities) as defined in a corresponding execution unit transition specifying a transition to build milestone 906. Build milestones 906-912 may be associated with the publication of capabilities that are required to start/continue the installation of another service. By way of example build milestone 908 may be associated with capabilities set 918, including one or more capabilities that are expected to be published prior to transitioning to build milestone 908. In some embodiments, build milestones may be used to generate a high-level sequencing diagram that may be used to identify progress in a region build.
Each build milestone may be associated with a corresponding execution unit. By way of example, build milestone 906 may be associated with execution unit 920 (corresponding to an instance of execution unit entity 700 of
Using the entities of the service plan, one or more acyclic graphs may be generated. As a non-limited example, a directed acyclic graph defining the service build may be generated. This DAG may be referred to as a “service DAG” and may include any suitable number of nodes representing a corresponding release and an order by which those releases are to be executed to build that service. The nodes themselves, or edges between nodes, may be associated with external and/or internal capability dependencies. In some embodiments, a graph, list, sequence diagram, or any suitable data structure may be generated for a service and/or for any suitable number of services of the region build using the build milestones corresponding to the service(s). This data structure may be referred to as a “milestone plan.” As yet another example, the Build Dependency Graph 338 of
In some embodiments, the service manifest 904 may be utilized to specify the flock versions and artifact versions that will be used to create releases for the execution targets specified in the service plan 902. The service manifest 904 may be used to validate the service plan 902 based at least in part on identifying that each release identified in the service plan 902 is included within the service manifest 904. In some embodiments, each service manifest item (e.g., service manifest item 924) may be mapped to a version set item such that service manifests may be used to validate a version set used by CIOS 102 to perform a region build. As a non-limiting example, a SPAM set may be constructed all SPAMs corresponding to services that are to be bootstrapped within a region/data center. The manifests of the SPAM set may be used to validate a version set, should one be used, to ensure that all flock config files and artifacts referenced in the SPAM set are included in the version set to be used to build the region.
An execution target may be associated with a tenancy and region (e.g., unstable-tenancy/region1, stable-tenancy/region2, prod-tenancy/region3) as depicted in
Each execution target (e.g., ET-1) may be associated with one or more execution target (ET) checkpoints (e.g., ETCKPT-1 and ETCKPT-2). Phases (e.g., phase 1, phase 2, etc.), execution targets (e.g., ET-1-ET-13), execution target checkpoints may be defined and/or specified within flock config entity 800 of
In some embodiments, Orchestrator 310 of
In some embodiments, at step 1, upon selecting the option publish a skill an instance of skill version data structure 412 of
In some embodiments, monitoring the health of a skill may include monitoring for indications that one or more alarms associated with the skill (e.g., alarms indicated with the alarmLabelName attribute of health check data structure 414 of
At step 5, the installation state may be updated to an “embargoed” state (e.g., by the Orchestrator, the Puffin Service, and/or based on user input) to indicate that health monitoring should continue but that only skills of the same producing service should treat the embargoed skill as being installed. In some embodiments, the installation state of the skill may revert to “installed.”
In some embodiments, a skill version may be retired (e.g., via user input) at step 6. While in the retired state, the skill version may not (or cannot) be utilized by other skills and/or in any build or run. In some embodiments, the skill version's installation state may not be modified once the skill has transitioned to the retired state.
In some embodiments, a skill version's installation state may transition from an “installed” state” to an “uninstalling” state based at least in part on operations performed by the orchestrator and/or by user input. In some embodiments, the Orchestrator 106 may determine service deployments are to be reversed. In these situations, the Orchestrator 106 may “unwind” installation of one or more services. During these operations, when the service is being uninstalled at step 7, the skill version associated may be updated to indicate a state of “uninstalling.” When the service associated with the skill version has been successfully uninstalled, the skill version's installation state may be updated to “selected” at step 8.
A number of transitions between the various states and substates are contemplated. The lifecycle states and transitions depicted in
Method 1200 may begin at 1210, where Puffin Regional 1206 may be seeded by Puffin Central 1202 with all pre-defined skills, versions, and consumers. In some embodiments, Puffin Central 1202 may utilize an application programming interface, function call, or another suitable method for communicating the metadata corresponding to each skill that has been previously defined (e.g., user-generated and/or system generated skills, the latter being referred to herein as “shadow skills”) to Puffin Regional 1206. In some embodiments, Puffin Central 1202 may send identifiers corresponding to each skill (and their skill version) with which the corresponding instance(s) of skills metadata may be retrieved by Puffin Regional 1206. In some embodiments, Puffin Central 1202 may be configured to identify and transmit skills metadata and/or identifiers (e.g., skill ID, major version, minor version, etc.) for skills which are to be utilized for building a region corresponding to Puffin Regional 1206. In some embodiments, the skill state for each of these skills may indicate that the skills are selected, but not yet installed. The state of a skill may be expressed with any suitable combination of the installationState and/or healthState attributes of a corresponding skill version data structure (e.g., the skill version data structure 412 of
Operations 1211 may include any suitable operations for building a target set and ordered execution plan. By way of example, at 1212, Orchestrator 106 may perform any suitable operations for identifying respective skill states for every skill, version, and consumer for the region. This may include identifying installation and/or health states of each skill (e.g., based at least in part on the installationState and healthState attributes of skill version data structure 412 of
At 1214, a target set and/or ordered execution plan may be generated. In some embodiments, building a target set may include any suitable combination of identifying and/or obtaining 1) a version set of flock configs (a “golden set” corresponding to a specific set of flock configs individually identified by specific version identifiers and corresponding to a set of services to be deployed in the region), 2) a Service Plan and Manifest (SPAM) set (e.g., aggregate particular SPAMs, associated with specific version identifiers and corresponding to a set of services to be deployed in the region), 3) a set of artifacts (e.g., program code associated with specific version identifiers, to be utilized/executed for provisioning infrastructure and/or deploying software within the region), or the like. As described above in connection with
Once built, the ordered execution plan may be utilized by Orchestrator 1204 to execute a region build. By way of example, at 1216, the Orchestrator 1204 may identify, for a current step, all skills on which the current step depends. As described below, Puffin Regional 1206 may maintain compatibility between skills and capabilities. Thus, in embodiments in which at least some capabilities are used to indicate availability of a particular service, resource, or functionality, Puffin Regional 1206 may generate shadow skills for those capabilities (e.g., prior to a region build) with which corresponding skill states may be used to track the current state of the capabilities represented by those shadow skills. In some embodiments, Puffin Regional 1206 may be configured to obtain capabilities data from storage, from Capabilities Service 112 of
At 1218, Orchestrator 1204 may query Puffing Regional 1206 for a current state corresponding to each skill on which the current step depends. A skill may be identified based at least in part on any suitable combination of skill ID, major version identifier, and/or minor version identifier, and/or according to any suitable combination of attribute values that are configured to be unique across skills. At the start of region build (e.g., at a first step, a first node of the Build Dependency Graph 338, a first operation of an ordered list of operations, etc.), the current step may lack association to any upstream skill. If no dependencies are identified for the current step, the method 1200 may continue to 1220 without executing the operations at 1218.
At 1220, in scenarios in which the Orchestrator 106 is returned corresponding skill states for one or more upstream skills (e.g., skills on which the current step depends) that indicate one or more upstream skills are not in a particular state (e.g., “INSTALLED”) and/or substate (e.g., “HEALTHY”), the Orchestrator 106 may execute operations to indicate a failure. In some embodiments, the current state of these skills may be viewed at similar user interfaces as the one depicted in
At 1222, at any suitable time, the Orchestrator 1204 may identify the upstream skills are installed and healthy based on the skill states obtained from Puffin Regional 1206. In response to identifying all upstream skills are installed and healthy, Orchestrator 1204 may transmit data for the skill(s) associated with the current step indicating the current state of those skill(s) is “INSTALLING.” Transmitting such data may cause Puffin Regional 1206 to update the installation state attribute of the skills version data structure 412 of
At 1224, Orchestrator 1204 may execute operations to cause CIOS Central 1208 to initiate one or more releases. In some embodiments, CIOS Central 1208 may instruct an instance of CIOS Regional within the region (e.g., CIOS Regional 110 of
At 1228, if the release was successful, Orchestrator 1204 may transmit data to Puffin Regional 1206 indicating that the skill(s) associated with the current step are now installed. Any suitable operations executed (e.g., by Orchestrator 1204) to update (e.g., via Puffin Regional 1206) a skill state to indicate that the skill was installed may be referred to as “publishing a skill.” In response to receiving this data, Puffin Region 1206 may update the skill(s)′ installation state to a value corresponding to the “INSTALLED” state. In some embodiments, Puffin Regional 1206 may be configured to transmit any suitable data (e.g., to Capabilities Service 112 of
At 1230, in some embodiments, Puffin Regional 1206 may be configured to commence operations for monitoring the installed skill(s)′ health state. In some embodiments, this may include monitoring for one or more alarms (indicated by the alarm labels of health check data structure 414 of
At 1232, Orchestrator 1204 may transition to the next step in the ordered execution plan (e.g., to a next node of the Build Dependency Graph 338). The operations described at 1216-1232 may be performed any suitable number of times, corresponding to each step in the ordered execution plan. When a last step has already been reached in the plan, the Orchestrator 1504 may conclude the region build at 1232.
At step 1, at any suitable time, Puffin Regional 1304 may receive or obtain an indication that capability A has been published. Puffin Regional 1304 may be configured to manage or otherwise maintain any suitable records for all known skills (e.g., user defined and/or system generated skills, the latter being referred to as a “shadow skill”). By way of example only, Puffin Regional 1304 may manage skills table 1310 and skill versions table 1312. In some embodiments, skill table 1310 may include identifiers and/or skill data structures (e.g., each corresponding to skill data structure 410 of
At step 2, if a shadow skill is generated at step 1, Puffin Regional 1304 may generate a skill version data structure 414 for shadow skill A. In some embodiments, the value for the data structure attributes associated with shadow skill A may be set to values according to a predefined protocol. In some embodiments, a skill's version may be used to track runtime information of the skill (e.g., whether the skill is installed and/or heathy). The term “skills” may be utilized herein to refer to any suitable combination of user-defined skills and/or system-generated shadow skills.
At step 3, at any suitable time, Puffin Regional 1304 may execute an application programming interface (API) call to Puffin Central 1306 to inform Puffin Central 1306 of Skill A's existence. In some embodiments, the data provided via this API call may include any suitable portion of skill's A metadata as generated and/or modified by Puffin Regional 1304. Puffin Regional 1704 may present any suitable information corresponding to shadow skill A via any suitable user interface on demand. An example of one example user interface is discussed in more detail in U.S. patent application entitled “Data Center Orchestration Management Techniques,” filed on 2024, the entire contents of which are incorporated by reference for all purposes.
As a non-limiting use case example, Service 2 may have once depended on capability A, but is not associated with a flock config and/or SPAM that utilizes skills to express the process for building Service 2. Based at least in part on the existence of shadow skill A, Service 2 may register a dependency against shadow skill A at step 4, enabling a dependency of Service 2 on capability A to be expressed using a skill (shadow skill A) instead of capability A. The use of the shadow skill enables Puffing Central 1306 and/or Puffing Regional 1304 to track region build process using a single construct, skills, which include attributes that enable the tracking functionality previously lacking with respect to capabilities.
At step 5, perhaps after Service 1 is associated with an ordered execution plan that is executed in terms of skills, rather than capabilities, one or more user interfaces of Puffin Central 1306 may be utilized for shadow skill A to be claimed by Service 1.
An order of corresponding ET checkpoints may be specified (e.g., within checkpoints section 810 of
Each ET checkpoint (e.g., any suitable ET checkpoint of checkpoint data 1402 and/or checkpoint data 1404) may be associated with any suitable number of external dependencies and/or any suitable number of internal dependencies. An ET checkpoint may be referred to herein as a “checkpoint,” for brevity. As depicted in
Each ET checkpoint (e.g., any suitable ET checkpoint of checkpoint data 1402 and/or checkpoint data 1404) may be associated with any suitable number of capability publications. Capability publications refer to capabilities that are to be published upon successful execution of the release corresponding to the checkpoint. An example capability publication is defined at 816 of
Referring once more to
In some embodiments, each flock 1502 may correspond to a group of resources (e.g., resources to be provisioned and/or deployed to build a given service). Flock config 1504 may be a data entity (e.g., flock config entity 800 of
Flock 1502 (an example of flock 1000 of
CIOS Central 1514 may prepare releases (e.g., release 1512) based at least in part on an ET checkpoint transition (e.g., a transition provided in execution unit entity 700 of
CIOS Central 1514 may execute a release by executing operations to effectuate a release corresponding to the ET checkpoint transition by CIOS Regional 1516 (an example of CIOS Regional 110 of
Execution target entity 1600 may include an ordered list of ET checkpoints defined in ET checkpoint section 1602. Each ET checkpoint being associated with an unordered collection of build flag names. By way of example, build flag section 1604 may include any suitable number of build flags (e.g., string(s)/value(s) corresponding to one or more build flags), each build flag corresponding to an ET checkpoint related to an infrastructure release. For example, ET checkpoint “service-certs” of build flag section 1604 (corresponding to a first ET checkpoint specified in an infrastructure ET checkpoint section of a flock config entity similar to flock config entity 800 of
An execution target (e.g., execution target 1510) may initially be associated with a default ET checkpoint (e.g., a checkpoint corresponding to “absent,” or another default value). The default ET checkpoint may be explicitly defined (e.g., via checkpoint section 1604) or assumed and associated with the ET by default, despite not being explicitly defined in checkpoint section 1604. A default ET checkpoint (e.g., an ET checkpoint corresponding to “absent” or another default value) may indicate a state of the execution target prior to any infrastructure (and/or application) releases being performed, or at least successfully so. As CIOS Central (e.g., CIOS Central 1514, an example of CIOS Central 108 of
In some embodiments, posting the build flag may include transmitting, by the CIOS Central 108 any suitable combination of an identifier of the build flag (e.g., “certificate-storage”), an ET identifier (e.g., a name of the ET such as “service-region-target_region_example” where “target_region_example” is the value assigned to the injectable variable $ {Target_Region}), an identifier for the infrastructure-related ET checkpoint (e.g., “service-certs”), a corresponding value for the build flag (e.g., “true,” “1,” etc.), and/or a build flag type (e.g., a type that indicates whether the build flag corresponds to an infrastructure-related ET checkpoint (e.g., an ET checkpoint of checkpoint section 1604) or an application-related ET checkpoint (e.g., an ET checkpoint of checkpoint section 1606). In some embodiments, the type of build flag (e.g., infrastructure versus application) may be implicitly identified based at least in part on the type of release (e.g., infrastructure versus application).
In some embodiments, posting a build flag may include the build flag provider identifying the type of release being executed (e.g., infrastructure versus application). Identifying the current checkpoint of the ET (e.g., “service-certs”), identifying (e.g., from a predefined build flag configuration corresponding to table 1702) a corresponding build flag identifier (e.g., “certificate-storage”), and generating an association (or setting a value already stored for that build flag identifier) that indicates the build flag has been posted. The association may include generated and/or updated by the build flag provider may include any suitable combination of an identifier of the build flag, an ET identifier, an identifier for ET checkpoint, a build flag type (e.g., infrastructure, application, etc.), and/or a corresponding value for the build flag indicating whether the build flag has been posted. In some embodiments, existence of an association may be considered indication that the build flag has been posted (e.g., in embodiments in which the build flag provider maintains a list of posted build flags).
The build flag provider may be configured to persist any suitable portion of the data in any suitable storage to maintain knowledge that the build flag has been posted. By way of example, the build flag provider may maintain a list (or other suitable data structure) of build flags which have been posted. As another example, to maintain knowledge of whether a build flag has been posted, the build flag provider may generate and/or update an association (e.g., via an object, a table, a record, a field, an attribute, a container, or any suitable data structure or storage) with any suitable combination of an identifier of the build flag, an ET identifier, an identifier for the current ET checkpoint, a build flag type, and/or a corresponding value for the build flag. The build flag provider may be queried at any suitable time to provide current values of the build flag for any suitable ET checkpoint. In response to such a query, the build flag provider may be configured to return “false” (or a similar value) for any build flag which has not been posted and “true (or a similar value for any build flags which have been posted. In some embodiments, a query may be directed to a particular build flag or for all build flags associated with an ET checkpoint. In some embodiments, a response to a query may include a list of the set of posted build flags (e.g., build flags that are associated with a value of “true,” etc.) or a list of all build flags and their corresponding values (e.g., true, false, etc.).
In some embodiments, the build flag provider may utilize a checkpoint definition indicating known ET checkpoints and corresponding build flags (e.g., the checkpoint section 1604) to identify known build flags (e.g., the build flags identified in table 1702). In some embodiments, the build flag provider may be configured to return an error code if a request is received for a build flag that is not associated with the ET (e.g., a build flag corresponding to the ET, but different from the build flags identified in table 1702, or in checkpoint section 1604). In some embodiments, the data stored by the build flag provider may be accessed via program code and/or function call (e.g., a get function that retrieves a value for the build flag, an “is_available” function that returns true when the build flag has been posted, etc.) to determine a true/false value indicating whether the build flag has been posted.
An execution target may be initially associated with a default checkpoint (e.g., “absent”) and a null set of build flags as depicted at 1708 and may incrementally accumulate build flags as releases (e.g., infrastructure and/or application releases) are successfully executed against the ET and the ET is transitioned to different checkpoints. Each successful release may cause an update the current checkpoint associated with the ET and an accumulation of one or more build flags corresponding to the current checkpoint (e.g., via posting the one or more build flags corresponding to the current checkpoint).
In some embodiments, while the current checkpoint of the execution target is set to “absent” (referred to as an “absent” state), the execution target may be presumed to have had no infrastructure releases performed against it, or at least successfully so. While in this state (e.g., while the current checkpoint is set to “absent”), any query for the build flags indicated in table 1702 (e.g., the build flags defined in checkpoint section 1604) received by the build flag provider may cause the build flag provider to consult stored data (e.g., a list of posted build flags, lookup the build flag identifier in a previous record and return an associated value, etc.) and return a value of “false,” indicating the build flag has not been posted. The build flags and/or corresponding values persisted by the build flag provider while the current checkpoint corresponds to “absent” (e.g., an infrastructure-related ET checkpoint of “absent”) are depicted at 1708. While the current checkpoint associated with the ET (e.g., referred to as “the state” of the ET) is set to “absent,” a query for any of the build flags “certificate-storage,” “partial,” or “available,” may cause the build flag provider to return a value of “false” (or an equivalent value, such as “0”) as depicted at 1708.
Upon transitioning the ET to a current checkpoint corresponding to the “service-certs” checkpoint depicted in table 1702, the build flag (e.g., “certificate-storage”) may be posted (e.g., by CIOS Central 108 or by the build flag provider in the manner described above). For example, the string “certificate-storage” may be transmitted (e.g., by CIOS Central 108) with any suitable combination of the ET identifier, an identifier for the infrastructure-related ET checkpoint (e.g., “service-certs”), a value of “true,” and/or a build flag type (e.g., “Infra,” indicating that the build flag is associated with an infrastructure-related ET checkpoint). The build flags and/or corresponding values persisted by the build flag provider while the current checkpoint corresponds to “service-certs” (e.g., an infrastructure-related ET checkpoint of “service-certs”) are depicted at 1710. Any suitable function configured to access the data stored by the build flag provider may obtain the values for each build flag as depicted at 1710 when the current checkpoint is set to “service-certs”. While the current checkpoint is set to “service-certs,” receiving a query for the build flag “certificate-storage,” may cause the build flag provider to return a value of “true (or an equivalent value, such as “1”), while queries for the build flags “partial,” or “available,” may cause the build flag provider to return a value of “false” (or an equivalent value, such as “0”) as depicted at 1710.
Upon transitioning the ET to a current checkpoint corresponding to the “service-partial” checkpoint depicted in table 1702, the build flag “partial” may be posted in one of the manners described above (e.g., via a transmission by CIOS Central 108 or by the build flag provider based on determining the current checkpoint for the ET). For example, the string “partial” may be transmitted (e.g., by CIOS Central 108) with any suitable combination of the ET identifier, an identifier for the infrastructure-related ET checkpoint (e.g., “service-partial”), a corresponding value of “true,” and/or a build flag type that indicates the build flag is associated with an infrastructure-related ET checkpoint. The build flags and/or corresponding values persisted by the build flag provider while the current checkpoint corresponds to “service-partial” (e.g., an infrastructure-related ET checkpoint of “service-partial”) are depicted at 1712. Any suitable function configured to access the data stored by the build flag provider may obtain the values for each build flag as depicted at 1712 when the current checkpoint is set to “service-partial”. While the current checkpoint associated with the ET is set to “service-partial,” receiving a query for the build flag “certificate-storage” or “partial” may cause the build flag provider to return a value of “true (or an equivalent value, such as “1”), while receiving a query for the build flag “available,” may cause the build flag provider to return a value of “false” (or an equivalent value, such as “0”) as depicted at 1712.
Upon transitioning the ET to a current checkpoint corresponding to the “service-available” checkpoint depicted in table 1702, the build flag “available” may be posted in one of the manners described above (e.g., via a transmission by CIOS Central 108 or by the build flag provider based on determining the current checkpoint for the ET). For example, the string “available” may be transmitted (e.g., by CIOS Central 108) with any suitable combination of the ET identifier, an identifier for the infrastructure-related ET checkpoint (e.g., “service-partial”), a corresponding value of “true,” and/or a build flag type that indicates the build flag is associated with an infrastructure-related ET checkpoint. The build flags and/or corresponding values persisted by the build flag provider while the current checkpoint corresponds to “service-available” (e.g., an infrastructure-related ET checkpoint of “service-available”) are depicted at 1714. Any suitable function configured to access the data stored by the build flag provider may obtain the values for each build flag as depicted at 1714 when the current checkpoint is set to “service-available”. While the current checkpoint associated with the ET is set to “service-available,” receiving a query for the build flag “certificate-storage,” “partial,” or “available” may cause the build flag provider to return a value of “true (or an equivalent value, such as “1”) as depicted at 1714.
Table 1704 represents an example build flag configuration and values corresponding to three execution target (ET) checkpoints. Each of ET checkpoints of table 1704 may correspond to a different application-related ET checkpoint (e.g., an ET checkpoint corresponding to successful execution of an application-related release herein referred to as an “application-related ET checkpoint”). As depicted, table 1704 includes the checkpoints explicitly identified in checkpoint section 1606 of
In some embodiments, while the current checkpoint of the execution target is set to “absent” (referred to as an “absent” state), corresponding to the “absent” checkpoint depicted in table 1704, the execution target may be presumed to have had no application releases performed against it, or at least successfully so. While in this state (e.g., while the current checkpoint is set to “absent”), any query for the build flags indicated in table 1704 (e.g., the build flags defined in checkpoint section 1606) received by the build flag provider may cause the build flag provider to consult stored data (e.g., a list of posted build flags, lookup the build flag identifier in a previous record and return an associated value, etc.) and return a value of “false,” indicating the build flag has not been posted. The build flags and/or corresponding values persisted by the build flag provider while the current checkpoint corresponds to “absent” (e.g., an infrastructure-related ET checkpoint of “absent”) are depicted at 1716. While the current checkpoint associated with the ET (e.g., referred to as “the state” of the ET) is set to “absent,” a query for any of the build flags “partial” and/or “available,” may cause the build flag provider to return a value of “false” (or an equivalent value, such as “0”) as depicted at 1716.
Upon transitioning the ET to a current checkpoint corresponding to the checkpoint “service-partial” depicted in table 1704, the build flag “partial” may be posted in one of the manners described above (e.g., via a transmission by CIOS Central 108 or by the build flag provider based on determining the current checkpoint for the ET). For example, the string “partial” may be transmitted (e.g., by CIOS Central 108) with any suitable combination of the ET identifier, an identifier for the application-related ET checkpoint (e.g., “service-partial”), a corresponding value of “true,” and/or a build flag type that indicates the build flag is associated with an application-related ET checkpoint. The build flags and/or corresponding values persisted by the build flag provider while the current checkpoint corresponds to the application-related checkpoint “service-partial” are depicted at 1718. Any suitable function configured to access the data stored by the build flag provider may obtain the values for each build flag as depicted at 1718 when the current checkpoint is set to “service-partial” (e.g., the application-related ET checkpoint “service-partial” depicted by table 1704). While the current checkpoint associated with the ET is set to “service-partial,” as depicted in table 1704, receiving a query for the build flag “partial” may cause the build flag provider to return a value of “true (or an equivalent value, such as “1”), while receiving a query for the build flag “available,” may cause the build flag provider to return a value of “false” (or an equivalent value, such as “0”) as depicted at 1718.
Upon transitioning the ET to a current checkpoint corresponding to the checkpoint “service-available” depicted in table 1704, the build flag “available” may be posted in one of the manners described above (e.g., via a transmission by CIOS Central 108 or by the build flag provider based on determining the current checkpoint for the ET). For example, the string “available” may be transmitted (e.g., by CIOS Central 108) with any suitable combination of the ET identifier, an identifier for the application-related ET checkpoint (e.g., “service-available”), a corresponding value of “true,” and/or a build flag type that indicates the build flag is associated with an application-related ET checkpoint. The build flags and/or corresponding values depicted at 1720 are persisted by the build flag provider while the current checkpoint corresponds to application-related checkpoint “service-available” of table 1704. Any suitable function configured to access the data stored by the build flag provider may obtain the values for each build flag as depicted at 1720 when the current checkpoint is set to “service-available” as depicted in table 1704. While the current checkpoint associated with the ET is set to “service-available,” receiving a query for the build flag “partial” and/or “available” may cause the build flag provider to return a value of “true (or an equivalent value, such as “1”) as depicted at 1720.
Code segment 1804 includes code at line 1818 that declares a resource (e.g., a build flag), “enable_alarms,” that is associated with an attribute “name,” having a corresponding value “enable_tel_alarms.” At line 1820, the expression 1822 may be used to determine whether the build flag “enable_tel_alarms” is available, or in other words, that the build flag “enable_tel_alarms” has been posted. Evaluation of the expression 1822 may provide a value of “true,” when the build flag “enable_tel_alarms” has been posted, and a value of “false” when that build flag has not been posted. The tertiary operator (“?”) and the value identified for expression 1822 may be used to set “count” to 1 when the build flag “enable_tel_alarms” has been posted, and to “0” when the build flag “enable_tel_alarms” has not been posted. As described above, the “count” may be used as a condition that encapsulates other code. In the example provided in code segment 1804, “count” may be used in conditional logic to ensure that a set of operations are not executed or evaluated unless the build flag “enable_tel_alarms” has been posted.
Utilizing capabilities as depicted in code segment 1802, provides disadvantages over utilizing build flags as depicted in code segment 1804. For example, the expressions 1814 and 1816 of line 812 of code segment 1802 are based on current capability availability (e.g., capability publications) determined at run time. In contrast, the expression 1822 of code segment 1804 may be determined at release creation time based on the ET checkpoint targeted in the release. Therefore, expression 1822 may be evaluated earlier than expressions 1814 and 1816, and on a more consistent, and deterministic basis. For example, due to non-deterministic behavior occurring in past implementations of capabilities, expressions 1814 and 1816 may never evaluate to 1. Or in other words, due to non-deterministic capabilities implementations, it may never be the case that the “serviceA_capability1” and “serviceA_capability_scaled” capabilities are both available. Therefore, code segment 1804 and the use of build flags provide advantages over the use of capabilities (e.g., when using such components to provide conditional logic to decide program code execution flow).
Method 1900 may begin at 1912 where orchestrator 1902 may create a release (e.g., an infrastructure release). In some embodiments, the orchestrator 1902 may traverse Dependency Build Graph 338 of
At 1914, a process for configuring the release may be performed. In some embodiments, the process for configuring the release may include, at 1916, validating that the current checkpoint and target checkpoints exist in CIOS Central.FlockConfig 1908 (in the ongoing example, a flock config entity 800 of
The process for configuring the release may further include validating the checkpoint transition (e.g., to determine whether the checkpoint transition is valid) at 1918. Validating the checkpoint transition (e.g., in the ongoing example, DP_initial_region_infra→DP_complete_region_infra) may include accessing CIOS Central.ET 1910, an example of execution target 1600 of
At 1920, a process for planning the release may be performed. At 1922, if the ET is blocked (e.g., external and/or internal capability dependencies of the target checkpoint have not been met), CIOS Central 1904 may be configured to wait until the ET is unblocked (e.g., external and/or internal capability dependencies of the target checkpoint have been met).
At 1924, after the ET is identified as not being blocked, the checkpoint transition may be validated. Validating the checkpoint transition corresponding to the release may include performing similar or the same operations that were described above at 1918. If the checkpoint transition is invalid, the release may fail, and a corresponding indication may be provided back to orchestrator 1902. No further processing of the release may be performed and this execution of method 1900 may conclude. If the checkpoint transition is valid, the method 1900 may continue to 1926. In some embodiments, any suitable build flag data associated with build flags corresponding to CIOS Central.ET 1910 may be returned to CIOS Central 1904. In some embodiments, the build flag data may include any suitable data discussed as being associated with a build flag of an ET as described above in connection with
At 1926, data corresponding to a planned release may be transmitted to CIOS Regional 1906, to indicate the release has passed validation checks. In some embodiments, transmitting the data at 1926 may cause the release and any suitable portion of the build flag data corresponding to the current checkpoint to be transmitted to CIOS Regional 1906. In some embodiments, the transmitted build flag data may include a build flag name and corresponding value for each build flag indicating whether each build flag has been posted.
At 1928, orchestrator 1902, may transmit instructions to Shepherd Central 1904 to performing a process 1930 for applying the release.
At 1932, if the ET is blocked (e.g., external and/or internal capability dependencies of the target checkpoint are not currently met), CIOS Central 1904 may be configured to wait until the ET is unblocked (e.g., the external and/or internal capability dependencies of the target checkpoint are identified as being met).
At 1934, after the ET is identified as not being blocked, the checkpoint transition may be validated. Validating the checkpoint transition corresponding to the release may include performing similar or the same operations that were described above at 1918, and again at 1924. If the checkpoint transition is invalid, the release may fail, and a corresponding indication may be provided back to orchestrator 1902. No further processing of the release may be performed and this execution of method 1900 may conclude. If the checkpoint transition is valid, the method 1900 may continue to 1936. In some embodiments, any suitable build flag data associated with build flags corresponding to CIOS Central.ET 1910 may be returned to CIOS Central 1904 at 1934.
At 1936, instructions may be sent by CIOS Central 1904 to CIOS Regional 1906 to apply the release. At any suitable time, CIOS Regional 1906 may provide status to CIOS Central 1904 indicating whether the release was executed successfully.
At 1938, if the status obtained from CIOS Regional 1906 indicates that the release was executed successfully, CIOS Central 1904 may update the current checkpoint for CIOS Central.ET 1910 and update the build flags for the ET to post a build flag corresponding to the now, current checkpoint (e.g., the originally target checkpoint to which the ET has been transitioned).
At 1940, if the status obtained from CIOS Regional 1906 indicates that executing the release failed. CIOS Central 1904 may execute any suitable instructions for failing the release. In some embodiments, CIOS Central 1904 may transmit data to orchestrator 1902 indicating that execution of the release failed.
The method 2000 may begin at 2002, where a service plan may be obtained (e.g., by orchestrator 102 of
At 2004, a directed acyclic graph (e.g., Dependency Build Graph 338 of
At 2006, the release may be executed at an execution target of the one or more execution targets as part of the second process for bootstrapping the plurality of services at the one or more execution targets of the cloud-computing environment. In some embodiments, the release may be executed according to the second release execution order based at least in part on traversing the directed acyclic graph.
At 2008, a state of the execution target (ET) (e.g., a current checkpoint, a current infrastructure-related checkpoint, a current application-related checkpoint, a build flag data for one or more build flags corresponding to the execution target, or any suitable a combination of the above) may be tracked. In some embodiments, tracking the state of the ET is based at least in part on executing the release at the execution target as part of the second process for bootstrapping the plurality of services at the one or more execution targets of the cloud-computing environment. In some embodiments, tracking the state of the ET may comprise updating the state of the execution target (e.g., a current checkpoint, a current infrastructure-related checkpoint, a current application-related checkpoint, a build flag data for one or more build flags corresponding to the execution target, or any suitable a combination of the above) based at least in part on identifying the release was successfully executed.
In some embodiments, the service plan further specifies an ordered list of execution target checkpoints comprising a first execution target checkpoint and a second execution target checkpoint. The first execution target checkpoint may be associated with execution of a first release of the one or more releases associated with the first process for building the service. In some embodiments, the second execution target checkpoint may be associated with execution of a second release of the one or more releases associated with the first process for building the service.
In some embodiments, the state of the execution target may be associated with an execution target checkpoint, the execution target checkpoint may be associated with one or more build flags. In some embodiments, each build flag of the one or more build flags indicates that execution of a corresponding release associated with a corresponding execution target checkpoint has been successfully executed.
In some embodiments, the service is a first service and at least one release of the set of releases associated with the second process is associated with a second service. In some embodiments, a dependency of the at least one release associated with the second process on successful execution of the release associated with the first service is expressed based at least in part on a build flag of the one or more build flags associated with the execution target checkpoint.
In some embodiments, a release plan is generated that defines the second process for bootstrapping the plurality of services at the one or more execution targets of the cloud-computing environment. In some embodiments, the release plan is generated based at least in part on traversing the directed acyclic graph.
In some embodiments, tracking the state of the execution target comprises updating the state (e.g., the current checkpoint of execution target 1510) with a value corresponding to an execution target checkpoint (e.g., a current ET checkpoint of the execution target).
As noted above, infrastructure as a service (IaaS) is one particular type of cloud computing. IaaS can be configured to provide virtualized computing resources over a public network (e.g., the Internet). In an IaaS model, a cloud computing provider can host the infrastructure components (e.g., servers, storage devices, network nodes (e.g., hardware), deployment software, platform virtualization (e.g., a hypervisor layer), or the like). In some cases, an IaaS provider may also supply a variety of services to accompany those infrastructure components (example services include billing software, monitoring software, logging software, load balancing software, clustering software, etc.). Thus, as these services may be policy-driven, IaaS users may be able to implement policies to drive load balancing to maintain application availability and performance.
In some instances, IaaS customers may access resources and services through a wide area network (WAN), such as the Internet, and can use the cloud provider's services to install the remaining elements of an application stack. For example, the user can log in to the IaaS platform to create virtual machines (VMs), install operating systems (OSs) on each VM, deploy middleware such as databases, create storage buckets for workloads and backups, and even install enterprise software into that VM. Customers can then use the provider's services to perform various functions, including balancing network traffic, troubleshooting application issues, monitoring performance, managing disaster recovery, etc.
In most cases, a cloud computing model will require the participation of a cloud provider. The cloud provider may, but need not be, a third-party service that specializes in providing (e.g., offering, renting, selling) IaaS. An entity might also opt to deploy a private cloud, becoming its own provider of infrastructure services.
In some examples, IaaS deployment is the process of putting a new application, or a new version of an application, onto a prepared application server or the like. It may also include the process of preparing the server (e.g., installing libraries, daemons, etc.). This is often managed by the cloud provider, below the hypervisor layer (e.g., the servers, storage, network hardware, and virtualization). Thus, the customer may be responsible for handling (OS), middleware, and/or application deployment (e.g., on self-service virtual machines (e.g., that can be spun up on demand)) or the like.
In some examples, IaaS provisioning may refer to acquiring computers or virtual hosts for use, and even installing needed libraries or services on them. In most cases, deployment does not include provisioning, and the provisioning may need to be performed first.
In some cases, there are two different challenges for IaaS provisioning. First, there is the initial challenge of provisioning the initial set of infrastructure before anything is running. Second, there is the challenge of evolving the existing infrastructure (e.g., adding new services, changing services, removing services, etc.) once everything has been provisioned. In some cases, these two challenges may be addressed by enabling the configuration of the infrastructure to be defined declaratively. In other words, the infrastructure (e.g., what components are needed and how they interact) can be defined by one or more configuration files. Thus, the overall topology of the infrastructure (e.g., what resources depend on which, and how they each work together) can be described declaratively. In some instances, once the topology is defined, a workflow can be generated that creates and/or manages the different components described in the configuration files.
In some examples, an infrastructure may have many interconnected elements. For example, there may be one or more virtual private clouds (VPCs) (e.g., a potentially on-demand pool of configurable and/or shared computing resources), also known as a core network. In some examples, there may also be one or more inbound/outbound traffic group rules provisioned to define how the inbound and/or outbound traffic of the network will be set up and one or more virtual machines (VMs). Other infrastructure elements may also be provisioned, such as a load balancer, a database, or the like. As more and more infrastructure elements are desired and/or added, the infrastructure may incrementally evolve.
In some instances, continuous deployment techniques may be employed to enable deployment of infrastructure code across various virtual computing environments. Additionally, the described techniques can enable infrastructure management within these environments. In some examples, service teams can write code that is desired to be deployed to one or more, but often many, different production environments (e.g., across various different geographic locations, sometimes spanning the entire world). However, in some examples, the infrastructure on which the code will be deployed must first be set up. In some instances, the provisioning can be done manually, a provisioning tool may be utilized to provision the resources, and/or deployment tools may be utilized to deploy the code once the infrastructure is provisioned.
The VCN 2106 can include a local peering gateway (LPG) 2110 that can be communicatively coupled to a secure shell (SSH) VCN 2112 via an LPG 2110 contained in the SSH VCN 2112. The SSH VCN 2112 can include an SSH subnet 2114, and the SSH VCN 2112 can be communicatively coupled to a control plane VCN 2116 via the LPG 2110 contained in the control plane VCN 2116. Also, the SSH VCN 2112 can be communicatively coupled to a data plane VCN 2118 via an LPG 2110. The control plane VCN 2116 and the data plane VCN 2118 can be contained in a service tenancy 2119 that can be owned and/or operated by the Iaas provider.
The control plane VCN 2116 can include a control plane demilitarized zone (DMZ) tier 2120 that acts as a perimeter network (e.g., portions of a corporate network between the corporate intranet and external networks). The DMZ-based servers may have restricted responsibilities and help keep breaches contained. Additionally, the DMZ tier 2120 can include one or more load balancer (LB) subnet(s) 2122, a control plane app tier 2124 that can include app subnet(s) 2126, a control plane data tier 2128 that can include database (DB) subnet(s) 2130 (e.g., frontend DB subnet(s) and/or backend DB subnet(s)). The LB subnet(s) 2122 contained in the control plane DMZ tier 2120 can be communicatively coupled to the app subnet(s) 2126 contained in the control plane app tier 2124 and an Internet gateway 2134 that can be contained in the control plane VCN 2116, and the app subnet(s) 2126 can be communicatively coupled to the DB subnet(s) 2130 contained in the control plane data tier 2128 and a service gateway 2136 and a network address translation (NAT) gateway 2138. The control plane VCN 2116 can include the service gateway 2136 and the NAT gateway 2138.
The control plane VCN 2116 can include a data plane mirror app tier 2140 that can include app subnet(s) 2126. The app subnet(s) 2126 contained in the data plane mirror app tier 2140 can include a virtual network interface controller (VNIC) 2142 that can execute a compute instance 2144. The compute instance 2144 can communicatively couple the app subnet(s) 2126 of the data plane mirror app tier 2140 to app subnet(s) 2126 that can be contained in a data plane app tier 2146.
The data plane VCN 2118 can include the data plane app tier 2146, a data plane DMZ tier 2148, and a data plane data tier 2150. The data plane DMZ tier 2148 can include LB subnet(s) 2122 that can be communicatively coupled to the app subnet(s) 2126 of the data plane app tier 2146 and the Internet gateway 2134 of the data plane VCN 2118. The app subnet(s) 2126 can be communicatively coupled to the service gateway 2136 of the data plane VCN 2118 and the NAT gateway 2138 of the data plane VCN 2118. The data plane data tier 2150 can also include the DB subnet(s) 2130 that can be communicatively coupled to the app subnet(s) 2126 of the data plane app tier 2146.
The Internet gateway 2134 of the control plane VCN 2116 and of the data plane VCN 2118 can be communicatively coupled to a metadata management service 2152 that can be communicatively coupled to public Internet 2154. Public Internet 2154 can be communicatively coupled to the NAT gateway 2138 of the control plane VCN 2116 and of the data plane VCN 2118. The service gateway 2136 of the control plane VCN 2116 and of the data plane VCN 2118 can be communicatively coupled to cloud services 2156.
In some examples, the service gateway 2136 of the control plane VCN 2116 or of the data plane VCN 2118 can make application programming interface (API) calls to cloud services 2156 without going through public Internet 2154. The API calls to cloud services 2156 from the service gateway 2136 can be one-way: the service gateway 2136 can make API calls to cloud services 2156, and cloud services 2156 can send requested data to the service gateway 2136. But cloud services 2156 may not initiate API calls to the service gateway 2136.
In some examples, the secure host tenancy 2104 can be directly connected to the service tenancy 2119, which may be otherwise isolated. The secure host subnet 2108 can communicate with the SSH subnet 2114 through an LPG 2110 that may enable two-way communication over an otherwise isolated system. Connecting the secure host subnet 2108 to the SSH subnet 2114 may give the secure host subnet 2108 access to other entities within the service tenancy 2119.
The control plane VCN 2116 may allow users of the service tenancy 2119 to set up or otherwise provision desired resources. Desired resources provisioned in the control plane VCN 2116 may be deployed or otherwise used in the data plane VCN 2118. In some examples, the control plane VCN 2116 can be isolated from the data plane VCN 2118, and the data plane mirror app tier 2140 of the control plane VCN 2116 can communicate with the data plane app tier 2146 of the data plane VCN 2118 via VNICs 2142 that can be contained in the data plane mirror app tier 2140 and the data plane app tier 2146.
In some examples, users of the system, or customers, can make requests, for example create, read, update, or delete (CRUD) operations, through public Internet 2154 that can communicate the requests to the metadata management service 2152. The metadata management service 2152 can communicate the request to the control plane VCN 2116 through the Internet gateway 2134. The request can be received by the LB subnet(s) 2122 contained in the control plane DMZ tier 2120. The LB subnet(s) 2122 may determine that the request is valid, and in response to this determination, the LB subnet(s) 2122 can transmit the request to app subnet(s) 2126 contained in the control plane app tier 2124. If the request is validated and requires a call to public Internet 2154, the call to public Internet 2154 may be transmitted to the NAT gateway 2138 that can make the call to public Internet 2154. Metadata that may be desired to be stored by the request can be stored in the DB subnet(s) 2130.
In some examples, the data plane mirror app tier 2140 can facilitate direct communication between the control plane VCN 2116 and the data plane VCN 2118. For example, changes, updates, or other suitable modifications to configuration may be desired to be applied to the resources contained in the data plane VCN 2118. Via a VNIC 2142, the control plane VCN 2116 can directly communicate with, and can thereby execute the changes, updates, or other suitable modifications to configuration to, resources contained in the data plane VCN 2118.
In some embodiments, the control plane VCN 2116 and the data plane VCN 2118 can be contained in the service tenancy 2119. In this case, the user, or the customer, of the system may not own or operate either the control plane VCN 2116 or the data plane VCN 2118. Instead, the IaaS provider may own or operate the control plane VCN 2116 and the data plane VCN 2118, both of which may be contained in the service tenancy 2119. This embodiment can enable isolation of networks that may prevent users or customers from interacting with other users', or other customers', resources. Also, this embodiment may allow users or customers of the system to store databases privately without needing to rely on public Internet 2154, which may not have a desired level of threat prevention, for storage.
In other embodiments, the LB subnet(s) 2122 contained in the control plane VCN 2116 can be configured to receive a signal from the service gateway 2136. In this embodiment, the control plane VCN 2116 and the data plane VCN 2118 may be configured to be called by a customer of the IaaS provider without calling public Internet 2154. Customers of the IaaS provider may desire this embodiment since database(s) that the customers use may be controlled by the IaaS provider and may be stored on the service tenancy 2119, which may be isolated from public Internet 2154.
The control plane VCN 2216 can include a control plane DMZ tier 2220 (e.g., the control plane DMZ tier 2120 of
The control plane VCN 2216 can include a data plane mirror app tier 2240 (e.g., the data plane mirror app tier 2140 of
The Internet gateway 2234 contained in the control plane VCN 2216 can be communicatively coupled to a metadata management service 2252 (e.g., the metadata management service 2152 of
In some examples, the data plane VCN 2218 can be contained in the customer tenancy 2221. In this case, the IaaS provider may provide the control plane VCN 2216 for each customer, and the IaaS provider may, for each customer, set up a unique compute instance 2244 that is contained in the service tenancy 2219. Each compute instance 2244 may allow communication between the control plane VCN 2216, contained in the service tenancy 2219, and the data plane VCN 2218 that is contained in the customer tenancy 2221. The compute instance 2244 may allow resources, which are provisioned in the control plane VCN 2216 that is contained in the service tenancy 2219, to be deployed or otherwise used in the data plane VCN 2218 that is contained in the customer tenancy 2221.
In other examples, the customer of the IaaS provider may have databases that live in the customer tenancy 2221. In this example, the control plane VCN 2216 can include the data plane mirror app tier 2240 that can include app subnet(s) 2226. The data plane mirror app tier 2240 can reside in the data plane VCN 2218, but the data plane mirror app tier 2240 may not live in the data plane VCN 2218. That is, the data plane mirror app tier 2240 may have access to the customer tenancy 2221, but the data plane mirror app tier 2240 may not exist in the data plane VCN 2218 or be owned or operated by the customer of the IaaS provider. The data plane mirror app tier 2240 may be configured to make calls to the data plane VCN 2218 but may not be configured to make calls to any entity contained in the control plane VCN 2216. The customer may desire to deploy or otherwise use resources in the data plane VCN 2218 that are provisioned in the control plane VCN 2216, and the data plane mirror app tier 2240 can facilitate the desired deployment, or other usage of resources, of the customer.
In some embodiments, the customer of the IaaS provider can apply filters to the data plane VCN 2218. In this embodiment, the customer can determine what the data plane VCN 2218 can access, and the customer may restrict access to public Internet 2254 from the data plane VCN 2218. The IaaS provider may not be able to apply filters or otherwise control access of the data plane VCN 2218 to any outside networks or databases. Applying filters and controls by the customer onto the data plane VCN 2218, contained in the customer tenancy 2221, can help isolate the data plane VCN 2218 from other customers and from public Internet 2254.
In some embodiments, cloud services 2256 can be called by the service gateway 2236 to access services that may not exist on public Internet 2254, on the control plane VCN 2216, or on the data plane VCN 2218. The connection between cloud services 2256 and the control plane VCN 2216 or the data plane VCN 2218 may not be live or continuous. Cloud services 2256 may exist on a different network owned or operated by the IaaS provider. Cloud services 2256 may be configured to receive calls from the service gateway 2236 and may be configured to not receive calls from public Internet 2254. Some cloud services 2256 may be isolated from other cloud services 2256, and the control plane VCN 2216 may be isolated from cloud services 2256 that may not be in the same region as the control plane VCN 2216. For example, the control plane VCN 2216 may be located in “Region 1,” and cloud service “Deployment 21,” may be located in Region 1 and in “Region 2.” If a call to Deployment 18 is made by the service gateway 2236 contained in the control plane VCN 2216 located in Region 1, the call may be transmitted to Deployment 18 in Region 1. In this example, the control plane VCN 2216, or Deployment 18 in Region 1, may not be communicatively coupled to, or otherwise in communication with, Deployment 18 in Region 2.
The control plane VCN 2316 can include a control plane DMZ tier 2320 (e.g., the control plane DMZ tier 2120 of
The data plane VCN 2318 can include a data plane app tier 2346 (e.g., the data plane app tier 2146 of
The untrusted app subnet(s) 2362 can include one or more primary VNICs 2364(1)-(N) that can be communicatively coupled to tenant virtual machines (VMs) 2366(1)-(N). Each tenant VM 2366(1)-(N) can be communicatively coupled to a respective app subnet 2367(1)-(N) that can be contained in respective container egress VCNs 2368(1)-(N) that can be contained in respective customer tenancies 2370(1)-(N). Respective secondary VNICs 2372(1)-(N) can facilitate communication between the untrusted app subnet(s) 2362 contained in the data plane VCN 2318 and the app subnet contained in the container egress VCNs 2368(1)-(N). Each container egress VCNs 2368(1)-(N) can include a NAT gateway 2338 that can be communicatively coupled to public Internet 2354 (e.g., public Internet 2154 of
The Internet gateway 2334 contained in the control plane VCN 2316 and contained in the data plane VCN 2318 can be communicatively coupled to a metadata management service 2352 (e.g., the metadata management system 2152 of
In some embodiments, the data plane VCN 2318 can be integrated with customer tenancies 2370. This integration can be useful or desirable for customers of the IaaS provider in some cases such as a case that may desire support when executing code. The customer may provide code to run that may be destructive, may communicate with other customer resources, or may otherwise cause undesirable effects. In response to this, the IaaS provider may determine whether to run code given to the IaaS provider by the customer.
In some examples, the customer of the IaaS provider may grant temporary network access to the IaaS provider and request a function to be attached to the data plane app tier 2346. Code to run the function may be executed in the VMs 2366(1)-(N), and the code may not be configured to run anywhere else on the data plane VCN 2318. Each VM 2366(1)-(N) may be connected to one customer tenancy 2370. Respective containers 2371(1)-(N) contained in the VMs 2366(1)-(N) may be configured to run the code. In this case, there can be a dual isolation (e.g., the containers 2371(1)-(N) running code, where the containers 2371(1)-(N) may be contained in at least the VM 2366(1)-(N) that are contained in the untrusted app subnet(s) 2362), which may help prevent incorrect or otherwise undesirable code from damaging the network of the IaaS provider or from damaging a network of a different customer. The containers 2371(1)-(N) may be communicatively coupled to the customer tenancy 2370 and may be configured to transmit or receive data from the customer tenancy 2370. The containers 2371(1)-(N) may not be configured to transmit or receive data from any other entity in the data plane VCN 2318. Upon completion of running the code, the IaaS provider may kill or otherwise dispose of the containers 2371(1)-(N).
In some embodiments, the trusted app subnet(s) 2360 may run code that may be owned or operated by the IaaS provider. In this embodiment, the trusted app subnet(s) 2360 may be communicatively coupled to the DB subnet(s) 2330 and be configured to execute CRUD operations in the DB subnet(s) 2330. The untrusted app subnet(s) 2362 may be communicatively coupled to the DB subnet(s) 2330, but in this embodiment, the untrusted app subnet(s) may be configured to execute read operations in the DB subnet(s) 2330. The containers 2371(1)-(N) that can be contained in the VM 2366(1)-(N) of each customer and that may run code from the customer may not be communicatively coupled with the DB subnet(s) 2330.
In other embodiments, the control plane VCN 2316 and the data plane VCN 2318 may not be directly communicatively coupled. In this embodiment, there may be no direct communication between the control plane VCN 2316 and the data plane VCN 2318. However, communication can occur indirectly through at least one method. An LPG 2310 may be established by the IaaS provider that can facilitate communication between the control plane VCN 2316 and the data plane VCN 2318. In another example, the control plane VCN 2316 or the data plane VCN 2318 can make a call to cloud services 2356 via the service gateway 2336. For example, a call to cloud services 2356 from the control plane VCN 2316 can include a request for a service that can communicate with the data plane VCN 2318.
The control plane VCN 2416 can include a control plane DMZ tier 2420 (e.g., the control plane DMZ tier 2120 of
The data plane VCN 2418 can include a data plane app tier 2446 (e.g., the data plane app tier 2146 of
The untrusted app subnet(s) 2462 can include primary VNICs 2464(1)-(N) that can be communicatively coupled to tenant virtual machines (VMs) 2466(1)-(N) residing within the untrusted app subnet(s) 2462. Each tenant VM 2466(1)-(N) can run code in a respective container 2467(1)-(N) and be communicatively coupled to an app subnet 2426 that can be contained in a data plane app tier 2446 that can be contained in a container egress VCN 2468. Respective secondary VNICs 2472(1)-(N) can facilitate communication between the untrusted app subnet(s) 2462 contained in the data plane VCN 2418 and the app subnet contained in the container egress VCN 2468. The container egress VCN can include a NAT gateway 2438 that can be communicatively coupled to public Internet 2454 (e.g., public Internet 2154 of
The Internet gateway 2434 contained in the control plane VCN 2416 and contained in the data plane VCN 2418 can be communicatively coupled to a metadata management service 2452 (e.g., the metadata management system 2152 of
In some examples, the pattern illustrated by the architecture of block diagram 2400 of
In other examples, the customer can use the containers 2467(1)-(N) to call cloud services 2456. In this example, the customer may run code in the containers 2467(1)-(N) that requests a service from cloud services 2456. The containers 2467(1)-(N) can transmit this request to the secondary VNICs 2472(1)-(N) that can transmit the request to the NAT gateway that can transmit the request to public Internet 2454. Public Internet 2454 can transmit the request to LB subnet(s) 2422 contained in the control plane VCN 2416 via the Internet gateway 2434. In response to determining the request is valid, the LB subnet(s) can transmit the request to app subnet(s) 2426 that can transmit the request to cloud services 2456 via the service gateway 2436.
It should be appreciated that IaaS architectures 2100, 2200, 2300, 2400 depicted in the figures may have other components than those depicted. Further, the embodiments shown in the figures are only some examples of a cloud infrastructure system that may incorporate an embodiment of the disclosure. In some other embodiments, the IaaS systems may have more or fewer components than shown in the figures, may combine two or more components, or may have a different configuration or arrangement of components.
In certain embodiments, the IaaS systems described herein may include a suite of applications, middleware, and database service offerings that are delivered to a customer in a self-service, subscription-based, elastically scalable, reliable, highly available, and secure manner. An example of such an IaaS system is the Oracle Cloud Infrastructure (OCI) provided by the present assignee.
Bus subsystem 2502 provides a mechanism for letting the various components and subsystems of computer system 2500 communicate with each other as intended. Although bus subsystem 2502 is shown schematically as a single bus, alternative embodiments of the bus subsystem may utilize multiple buses. Bus subsystem 2502 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. For example, such architectures may include an Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus, which can be implemented as a Mezzanine bus manufactured to the IEEE P1386.1 standard.
Processing unit 2504, which can be implemented as one or more integrated circuits (e.g., a conventional microprocessor or microcontroller), controls the operation of computer system 2500. One or more processors may be included in processing unit 2504. These processors may include single core or multicore processors. In certain embodiments, processing unit 2504 may be implemented as one or more independent processing units 2532 and/or 2534 with single or multicore processors included in each processing unit. In other embodiments, processing unit 2504 may also be implemented as a quad-core processing unit formed by integrating two dual-core processors into a single chip.
In various embodiments, processing unit 2504 can execute a variety of programs in response to program code and can maintain multiple concurrently executing programs or processes. At any given time, some or all of the program code to be executed can be resident in processor(s) 2504 and/or in storage subsystem 2518. Through suitable programming, processor(s) 2504 can provide various functionalities described above. Computer system 2500 may additionally include a processing acceleration unit 2506, which can include a digital signal processor (DSP), a special-purpose processor, and/or the like.
I/O subsystem 2508 may include user interface input devices and user interface output devices. User interface input devices may include a keyboard, pointing devices such as a mouse or trackball, a touchpad or touch screen incorporated into a display, a scroll wheel, a click wheel, a dial, a button, a switch, a keypad, audio input devices with voice command recognition systems, microphones, and other types of input devices. User interface input devices may include, for example, motion sensing and/or gesture recognition devices such as the Microsoft Kinect® motion sensor that enables users to control and interact with an input device, such as the Microsoft Xbox® 360 game controller, through a natural user interface using gestures and spoken commands. User interface input devices may also include eye gesture recognition devices such as the Google Glass® blink detector that detects eye activity (e.g., ‘blinking’ while taking pictures and/or making a menu selection) from users and transforms the eye gestures as input into an input device (e.g., Google Glass®). Additionally, user interface input devices may include voice recognition sensing devices that enable users to interact with voice recognition systems (e.g., Siri® navigator), through voice commands.
User interface input devices may also include, without limitation, three dimensional (3D) mice, joysticks or pointing sticks, gamepads and graphic tablets, and audio/visual devices such as speakers, digital cameras, digital camcorders, portable media players, webcams, image scanners, fingerprint scanners, barcode reader 3D scanners, 3D printers, laser rangefinders, and eye gaze tracking devices. Additionally, user interface input devices may include, for example, medical imaging input devices such as computed tomography, magnetic resonance imaging, position emission tomography, medical ultrasonography devices. User interface input devices may also include, for example, audio input devices such as MIDI keyboards, digital musical instruments and the like.
User interface output devices may include a display subsystem, indicator lights, or non-visual displays such as audio output devices, etc. The display subsystem may be a cathode ray tube (CRT), a flat-panel device, such as that using a liquid crystal display (LCD) or plasma display, a projection device, a touch screen, and the like. In general, use of the term “output device” is intended to include all possible types of devices and mechanisms for outputting information from computer system 2500 to a user or other computer. For example, user interface output devices may include, without limitation, a variety of display devices that visually convey text, graphics and audio/video information such as monitors, printers, speakers, headphones, automotive navigation systems, plotters, voice output devices, and modems.
Computer system 2500 may comprise a storage subsystem 2518 that provides a tangible non-transitory computer-readable storage medium for storing software and data constructs that provide the functionality of the embodiments described in this disclosure. The software can include programs, code modules, instructions, scripts, etc., that when executed by one or more cores or processors of processing unit 2504 provide the functionality described above. Storage subsystem 2518 may also provide a repository for storing data used in accordance with the present disclosure.
As depicted in the example in
System memory 2510 may also store an operating system 2516. Examples of operating system 2516 may include various versions of Microsoft Windows®, Apple Macintosh®, and/or Linux operating systems, a variety of commercially-available UNIX® or UNIX-like operating systems (including without limitation the variety of GNU/Linux operating systems, the Google Chrome® OS, and the like) and/or mobile operating systems such as iOS, Windows® Phone, Android® OS, BlackBerry® OS, and Palm® OS operating systems. In certain implementations where computer system 2500 executes one or more virtual machines, the virtual machines along with their guest operating systems (GOSs) may be loaded into system memory 2510 and executed by one or more processors or cores of processing unit 2504.
System memory 2510 can come in different configurations depending upon the type of computer system 2500. For example, system memory 2510 may be volatile memory (such as random-access memory (RAM)) and/or non-volatile memory (such as read-only memory (ROM), flash memory, etc.) Different types of RAM configurations may be provided including a static random-access memory (SRAM), a dynamic random-access memory (DRAM), and others. In some implementations, system memory 2510 may include a basic input/output system (BIOS) containing basic routines that help to transfer information between elements within computer system 2500, such as during start-up.
Computer-readable storage media 2522 may represent remote, local, fixed, and/or removable storage devices plus storage media for temporarily and/or more permanently containing, storing, computer-readable information for use by computer system 2500 including instructions executable by processing unit 2504 of computer system 2500.
Computer-readable storage media 2522 can include any appropriate media known or used in the art, including storage media and communication media, such as but not limited to, volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage and/or transmission of information. This can include tangible computer-readable storage media such as RAM, ROM, electronically erasable programmable ROM (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disk (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other tangible computer readable media.
By way of example, computer-readable storage media 2522 may include a hard disk drive that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive that reads from or writes to a removable, nonvolatile magnetic disk, and an optical disk drive that reads from or writes to a removable, nonvolatile optical disk such as a CD ROM, DVD, and Blu-Ray® disk, or other optical media. Computer-readable storage media 2522 may include, but is not limited to, Zip® drives, flash memory cards, universal serial bus (USB) flash drives, secure digital (SD) cards, DVD disks, digital video tape, and the like. Computer-readable storage media 2522 may also include, solid-state drives (SSD) based on non-volatile memory such as flash-memory based SSDs, enterprise flash drives, solid state ROM, and the like, SSDs based on volatile memory such as solid-state RAM, dynamic RAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, and hybrid SSDs that use a combination of DRAM and flash memory-based SSDs. The disk drives and their associated computer-readable media may provide non-volatile storage of computer-readable instructions, data structures, program modules, and other data for computer system 2500.
Machine-readable instructions executable by one or more processors or cores of processing unit 2504 may be stored on a non-transitory computer-readable storage medium. A non-transitory computer-readable storage medium can include physically tangible memory or storage devices that include volatile memory storage devices and/or non-volatile storage devices. Examples of non-transitory computer-readable storage medium include magnetic storage media (e.g., disk or tapes), optical storage media (e.g., DVDs, CDs), various types of RAM, ROM, or flash memory, hard drives, floppy drives, detachable memory drives (e.g., USB drives), or other type of storage device.
Communications subsystem 2524 provides an interface to other computer systems and networks. Communications subsystem 2524 serves as an interface for receiving data from and transmitting data to other systems from computer system 2500. For example, communications subsystem 2524 may enable computer system 2500 to connect to one or more devices via the Internet. In some embodiments communications subsystem 2524 can include radio frequency (RF) transceiver components for accessing wireless voice and/or data networks (e.g., using cellular telephone technology, advanced data network technology, such as 3G, 4G or EDGE (enhanced data rates for global evolution), WiFi (IEEE 802.11 family standards, or other mobile communication technologies, or any combination thereof)), global positioning system (GPS) receiver components, and/or other components. In some embodiments communications subsystem 2524 can provide wired network connectivity (e.g., Ethernet) in addition to or instead of a wireless interface.
In some embodiments, communications subsystem 2524 may also receive input communication in the form of structured and/or unstructured data feeds 2526, event streams 2528, event updates 2530, and the like on behalf of one or more users who may use computer system 2500.
By way of example, communications subsystem 2524 may be configured to receive data feeds 2526 in real-time from users of social networks and/or other communication services such as Twitter® feeds, Facebook® updates, web feeds such as Rich Site Summary (RSS) feeds, and/or real-time updates from one or more third party information sources.
Additionally, communications subsystem 2524 may also be configured to receive data in the form of continuous data streams, which may include event streams 2528 of real-time events and/or event updates 2530, that may be continuous or unbounded in nature with no explicit end. Examples of applications that generate continuous data may include, for example, sensor data applications, financial tickers, network performance measuring tools (e.g., network monitoring and traffic management applications), clickstream analysis tools, automobile traffic monitoring, and the like.
Communications subsystem 2524 may also be configured to output the structured and/or unstructured data feeds 2526, event streams 2528, event updates 2530, and the like to one or more databases that may be in communication with one or more streaming data source computers coupled to computer system 2500.
Computer system 2500 can be one of various types, including a handheld portable device (e.g., an iPhone® cellular phone, an iPad® computing tablet, a PDA), a wearable device (e.g., a Google Glass® head mounted display), a PC, a workstation, a mainframe, a kiosk, a server rack, or any other data processing system.
Due to the ever-changing nature of computers and networks, the description of computer system 2500 depicted in the figure is intended only as a specific example. Many other configurations having more or fewer components than the system depicted in the figure are possible. For example, customized hardware might also be used and/or particular elements might be implemented in hardware, firmware, software (including applets), or a combination. Further, connection to other computing devices, such as network input/output devices, may be employed. Based on the disclosure and teachings provided herein, a person of ordinary skill in the art will appreciate other ways and/or methods to implement the various embodiments.
Although specific embodiments have been described, various modifications, alterations, alternative constructions, and equivalents are also encompassed within the scope of the disclosure. Embodiments are not restricted to operation within certain specific data processing environments but are free to operate within a plurality of data processing environments. Additionally, although embodiments have been described using a particular series of transactions and steps, it should be apparent to those skilled in the art that the scope of the present disclosure is not limited to the described series of transactions and steps. Various features and aspects of the above-described embodiments may be used individually or jointly.
Further, while embodiments have been described using a particular combination of hardware and software, it should be recognized that other combinations of hardware and software are also within the scope of the present disclosure. Embodiments may be implemented only in hardware, or only in software, or using combinations thereof. The various processes described herein can be implemented on the same processor or different processors in any combination. Accordingly, where components or services are described as being configured to perform certain operations, such configuration can be accomplished, e.g., by designing electronic circuits to perform the operation, by programming programmable electronic circuits (such as microprocessors) to perform the operation, or any combination thereof. Processes can communicate using a variety of techniques including but not limited to conventional techniques for inter process communication, and different pairs of processes may use different techniques, or the same pair of processes may use different techniques at different times.
The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. It will, however, be evident that additions, subtractions, deletions, and other modifications and changes may be made thereunto without departing from the broader spirit and scope as set forth in the claims. Thus, although specific disclosure embodiments have been described, these are not intended to be limiting. Various modifications and equivalents are within the scope of the following claims.
The use of the terms “a” and “an” and “the” and similar referents in the context of describing the disclosed embodiments (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including,” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. The term “connected” is to be construed as partly or wholly contained within, attached to, or joined together, even if there is something intervening. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate embodiments and does not pose a limitation on the scope of the disclosure unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the disclosure.
Disjunctive language such as the phrase “at least one of X, Y, or Z,” unless specifically stated otherwise, is intended to be understood within the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present.
Preferred embodiments of this disclosure are described herein, including the best mode known for carrying out the disclosure. Variations of those preferred embodiments may become apparent to those of ordinary skill in the art upon reading the foregoing description. Those of ordinary skill should be able to employ such variations as appropriate and the disclosure may be practiced otherwise than as specifically described herein. Accordingly, this disclosure includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the disclosure unless otherwise indicated herein.
All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.
In the foregoing specification, aspects of the disclosure are described with reference to specific embodiments thereof, but those skilled in the art will recognize that the disclosure is not limited thereto. Various features and aspects of the above-described disclosure may be used individually or jointly. Further, embodiments can be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the specification. The specification and drawings are, accordingly, to be regarded as illustrative rather than restrictive.
This non-provisional application claims priority to U.S. Provisional Patent Application No. 63/503,145, filed on May 18, 2023, entitled “Region Build Orchestration using Skills and Capabilities,” the disclosure of which is herein incorporated by reference in its entirety for all purposes.
| Number | Date | Country | |
|---|---|---|---|
| 63503145 | May 2023 | US |
