Patent Application
20240385866
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). In some examples, 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 as “bootstrapping a data center” or performing a “region build”) may include provisioning and configuring infrastructure resources and deploying code to those resources (e.g., for 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 ease of use. Improvements can be made.
Embodiments of the present disclosure relate to techniques for managing operations of a region build based on different constructs. Conventional systems may rely on “capabilities” as a mechanism to drive bootstrapping operations. A “capability” refers to a flag or other notification that indicates that a resource or particular functionality is available. These capabilities have been used to determine when dependencies are met in order to determine when to initiate additional bootstrapping operations. The limited nature of capabilities presents a number of drawbacks with respect to tracking the progress of a region build and/or identifying when to initiate bootstrapping operations. A new construct, “skills,” may be used to address these drawbacks.
At least one embodiment is directed to a computer-implemented method. The method may include managing, by a computing system, a plurality of skills corresponding to a plurality of services to be deployed by a cloud infrastructure orchestration system during a process associated with building a data center. In some embodiments, a first skill of the plurality of skills indicates a dependency on a second skill of the plurality of skills. Each skill of the plurality of skills may be associated with a corresponding skill state of a plurality of skill states. The method may further include maintaining, by the computing system, an association between the second skill of the plurality of skills and a corresponding capability of a plurality of capabilities associated with the plurality of services to be deployed. The method may include identifying, by the computing system, that the corresponding capability associated with the second skill is available. The method may include transitioning, by the computing system, the second skill of the plurality of skills from a first state of the plurality of skill states to a second state of the plurality of skill states based at least in part on the association between the second skill and the corresponding capability. The method may include tracking, by the computing system, progress of the cloud infrastructure orchestration system through the process associated with building the data center. In some embodiments, the tracking may be performed based at least in part on transitioning the second skill from the first state to the second state.
The method may further include any suitable combination of identifying an additional capability of the plurality of capabilities, determining that the additional capability lacks an association with the plurality of skills, generating a shadow skill that represents the additional capability, and adding the shadow skill to the plurality of skills managed by the computing system.
In some embodiments, identifying the additional capability comprises obtaining historical publishing data indicating a set of capabilities historical published by the cloud infrastructure orchestration system. In some embodiments, the set of capabilities comprise the additional capability.
In some embodiments, identifying that the corresponding capability associated with the second skill is available comprises identifying that the corresponding capability was published by a capabilities service of the cloud infrastructure orchestration service.
The method may further comprise managing a user interface configured to present skill metadata associated with the second skill of the plurality of skills. In some embodiments, the skill metadata comprises at least one of: a current state, a skill version, a set of one or more associated capabilities, an associated service of the plurality of services, and contact information associated with entities corresponding to the associated service.
The method may comprise transitioning, by the computing system, the first skill from a third state to a fourth state based at least in part on receiving, by the computing system, a first indication that the second skill is installed. In some embodiments, the method may comprise identifying, by the computing system and based at least in part on the association, an additional capability associated with the first skill. In response to receiving the indication that the first skill is installed, the computing system may transmit a second indication that the capability associated with the first skill is available.
In some embodiments, the first indication that the second skill is installed is received from an orchestrator of the cloud infrastructure orchestration system, and the second indication that the capability associated with the first skill is transmitted to a capabilities service of the cloud infrastructure orchestration system.
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 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.
Embodiments of the present disclosure relate to techniques for performing an automated region build (e.g., bootstrapping (e.g., provisioning and/or deploying) resources (e.g., infrastructure component, artifacts, etc.) for any suitable number of services within a region (e.g., a geographical location associated with one or more data centers)). Bootstrapping operations can be 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 maintained various versions of configuration files and/or software artifacts and attempted to intelligently and automatically identify a particular version set with which a region build is to be performed. As a region was built, the orchestrator utilized 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. Embodiments of the present disclosure provide improvements over the previous implementations.
Today, during Large Scale Events (LSEs) (e.g., events in which a substantial error 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.
The techniques discussed herein include utilizing a new construct (e.g., “skills”) which may be used with, or in lieu of, previously utilized 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. A skills service (e.g., referred to as “Puffin”) may provide authoritative registry for services. Various user interfaces managed by the service may be utilized to define, maintain, and manage skills that each service offers, as well as their dependency relationships with other services. Puffin 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).
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).
Puffin is designed to remove operational overhead, improve information accuracy, surface critical data including the ability to present interconnected service skills dependencies in a visual graph. These techniques improve error detection and contributing cause analysis process, improve understanding of the service, build, and/or event, reduce risk of error and/or recovery time, among other benefits.
A “region” is a logical abstraction corresponding to a geographical location. A region can include any suitable number of one or more execution targets. In some embodiments, an execution target could correspond to a data center.
An “execution target” refers to a unit of change for executing a release. 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.). For most 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).
“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 config” 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 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.
“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 “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 “Telemetry Service” may be a service or system that manages/monitors various alarms and corresponding alarm states.
A “Service Plan and Manifest” (SPAM) refers to a deterministic specification of the process for building a service. In some embodiments, a SPAM details a combination and order of releases needed to build the service. A manifest of the SPAM may define all resources to be used, while the service plan specifies a plan of execution based on dependencies (expressed via skills).
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
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, both of which will be described in further detail below) that may be configured to manage bootstrapping tasks (provisioning and deployment) for a given service and an Orchestrator (e.g., a multi-flock orchestrator, also described in further detail below) configured to initiate/manage region builds (e.g., bootstrapping operations corresponding to multiple services in a region).
CIOS enables region 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 also supports automated discovery of flocks (e.g., service resources such as flock config(s) corresponding to any suitable number of services), artifacts, resources, and dependencies. 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).
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, either directly or indirectly (e.g., via RRDD 104). CIOS Central 108 may be configured to compile flock configs to inject region data as variables within the 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. 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 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 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 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) may be configured to drive region build efforts. In some embodiments, Orchestrator 106 can manage information that describes what flock/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 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 and artifacts to be used for a region build. Some, or all, of the flock configs may be configured to be region agnostic. That is, the flock configs 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 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. Flock configs can reference region data through variables/parameters without requiring hard-coded identification of region data. The flock configs 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 are parsed to identify dependencies between resources, execution targets, phases, and flocks, and in particular to identify circular dependencies that need to be removed. 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, a service plan and manifest (SPAM) may be utilized. A service plan and manifest may provide a more deterministic specification of a build description for a service than previously provided by a single flock config. 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 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 corresponding to each service to be deployed in the region) allow service teams to describe the corresponding operations 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. As a specific example, one or more visualization can present a region-level DAG including only external coordination (e.g., an order of operations corresponding to all of the services to be deployed in the region) while omitting operations that are internal with respect to each service. This graph, for example, may depict nodes corresponding to one service's capabilities or skills on which other services depend, while excluding nodes corresponding to capability/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 (previously defined by one or more corresponding flock configs) that are needed to build a service, with potentially multiple execution units being defined. Each release may be associated with a set of execution target checkpoints (e.g., one execution target checkpoint for each execution target in a phase), each of which may be used to specify the expected capabilities (and/or skills) that should be available before the time of the release and the capabilities (and/or skills) 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 compose a larger 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. 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, 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 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.
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 (not depicted) may utilize an application programming interface provided the Puffin Service (including Puffin Central 118 and Puffin Regional 120) when an alarm is triggered. The Puffin Service may present, via one or more user interfaces, information related to the health of a skill based on these triggered alarms 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.
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 116. Virtual bootstrap environment (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 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
At step 1, 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 and/or SPAMs 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 and/or SPAMs 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
At step 1, 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 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 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 needed to build a single service. In embodiments in which one or more SPAMs are utilized, 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.
At step 7, Orchestrator 310 may request CIOS Central 304 to recompile each of the flock configs associated with the version set or identified by a SPAM of the 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 analysis of the recompiled flock configs. As part of the static analysis, Orchestrator 310 may parse the flock configs (e.g., using a library associated with a declarative infrastructure provisioner (e.g., Terraform, or the like)) to identify dependencies between flocks. From the analysis and the dependencies identified, Orchestrator 310 can generate Build Dependency Graph 338. Build Dependency Graph 338 may be an acyclic directed graph that identifies an order by which flocks are to be bootstrapped (and/or changes indicated in flock configs are to be applied) to the new region. Each node in the graph may correspond to bootstrapping any suitable portion of a particular flock. The specific bootstrapping order 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 graph (e.g., beginning at a starting node) to drive the operations of the region build.
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.
In some embodiments, the Orchestrator 310 may generate dependency build graph 338 from a set of one or more SPAMs (e.g., SPAMs of the SPAM set). Each of the SPAMs may identify a deterministic process for building a single service, including upstream and downstream dependencies on one or more other resources, services, or features being available, or based on an event (each of which may be expressed through publishing a capability and/or skill). Accordingly, in some embodiments, the dependency build graph 338 is generated through a static flock analysis of one or more flock configs to infer at least some dependencies while, in other embodiments, the dependency build graph 338 is generated in accordance with the build process explicitly defined within a SPAM set.
A starting node 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). Upon detecting this capability (e.g., via data provided by Capabilities Service 318) or skill (e.g., via data provided by Puffin Regional 342) is available, 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, 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 334 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.
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, a minor version, a patch version, a deprecated indicator, a health check indicator, an installation state, a health state, and an observability attribute. 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.
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
As depicted, user interface 500 may include user interface element 502 (e.g., depicted as a drop-down menu, however, other user interface elements are contemplated). User interface element 502 may be prepopulated with any suitable number of skills names obtained from any suitable number of predefined instances of skills metadata 404. Each entry selectable from user interface element 502 may correspond to a different instance of skill metadata 404. By default, user interface element 502 may present a selection of “all” indicating an option to present service names (or any suitable portion of skill metadata 404) corresponding to every unique instance of skill metadata 404. Each instance of skill metadata 404 may correspond to every previously defined skill. User interface element 502 may be one of a set of user interface elements (e.g., user interface elements 504, which include user interface elements corresponding to availability scope, skill groups, impact region level, publishing service, region, skill state, and skill health). It should be appreciated that selections available via one user interface element of the user interface elements 504 may depend on values selected via one or more other user interface element(s) of the user interface elements 504. In some embodiments, some user interface elements may be disabled or enabled depending on values selected via one or more other user interface elements. As a non-limiting example, values for skill state and skill health may not be entered via the corresponding user interface elements depicted unless a value has been selected via the user interface element corresponding to the region. User interface 500 may include any suitable filtering options for filtering the entries within area 510. By way of example, one or more keywords may be provided via search box 506. Upon selecting search button 508, the entries within area 506 may be updated to include entries that relate, match, or otherwise correspond to the keywords provided via search box 506.
As skill metadata may be added or changed over time, user interface 500 may include refresh option 512. Upon selecting refresh option 512, Puffin Central 118 may be configured to read, parse, or otherwise update skill metadata presented via user interface 500. Any suitable previous selections provided via user interface elements 504, 506, and/or 508 may be applied to the updated skill metadata and corresponding entries may be provided anew via area 510. Area 510 may be scrollable and/or the user interface 500 may include presentation options (e.g., presentation option 512) for configuring paging options in which a particular number (e.g., up to 100 entries) may be initially presented within area 510. Navigational options 514 and 516 may be provided to navigate to a next or previous page, respectively.
The particular data presented via area 510 may be customizable via user interface element 518. Selection of user interface element 518 may cause a window or pop up to be presented with which columns corresponding to particular skills metadata attributes may be selected or deselected for display. In some embodiment, user interface 500 may include user interface option 520. Upon selecting user interface option 520, the data presented via area 510 may be formatted according to a predefined format and saved to a file. In some embodiments, the data may be downloaded (e.g., saved locally at the user's device) in any suitable format. The user may be presented an additional window or interface for selecting a storage location and/or format for the downloaded data.
In some embodiments, selecting navigational link 524 may navigate the user interface 600 of
Area 602 may present any suitable combination of attributes and corresponding values according to a predefined format. As a non-limiting example, area 602 includes a created date, an updated data, a compartment identifier, a unique system identifier (e.g., OCID), an impact ring level, a namespace type, one or more health alarm labels associated with the selected skill, and a description.
Area 604 may provide one or more user interface elements corresponding to selecting filtering options. Values selected via the user interface elements of area 604 may be used to update or modify user interface 600 to include the attribute and values associated with the version and/or region associated with the selected skill. User interface 600 may include user interface element 606, which may be configured to display an indication of the health state associated with the skill (e.g., a health state stored in skill version data structure 412 of
User interface 600 may include refresh option 610. Selection of this option may cause Puffin Central 118 to obtain and present anew values corresponding to the attributes depicted in
User interface 600 may include area 612 which may be configured to present any suitable combination of attributes and corresponding values from skill version data structure 412. Option 613 may be select to expand an area of user interface 600 to present the data of areas 616 and 622. Area 616 may present a health dependency tree generated with respect to the selected skill. In some embodiments, the health dependency tree (e.g., a directed acyclic graph, a portion of the Build Dependency Graph 338, etc.) may be generated and/or by the Puffin Service in response to receiving indication (e.g., from an alarm service) that one or more alarms associated with the selected skill has been triggered. As a non-limiting example, BSCP Skill 2 may be identified by the Puffin Service as being unhealthy (e.g., due to receiving an indication that a particular alarm has been triggered). The health dependency tree presented in area 616 may be generated based at least in part on traversing upwards or downwards in a dependency graph generated based on all of the service metadata 402 instances and skill metadata 404 instances corresponding to every service and skill associated with the same build, run, or region associated with BSCP Skill 2.
Through traversing upward and downwards in the dependency graph and determining the corresponding health state of nodes of the graph corresponding to other skills, one or more skills may be identified as being the probable cause of the health state of BSCP Skill 2. By way of example, the Puffin Service may traverse the dependency graph upwards to identify IDDP Skill 1, v.1.0.0.1 is also unhealthy, but a skill higher up the graph and consumed by IDDP Skill 1 (meaning a skill on which IDDP Skill 1 depends) is healthy. Based at least in part on determining that IDDP Skill 1 is unhealthy and the highest skill in the dependency graph starting from a node corresponding to BSCP Skill 2, IDDP Skill 1 may be identified as the probable cause for the current health state associated with BSCP Skill 2. Similarly, additional affected skills may be determined lower in the dependency graph (e.g., based on health states that consume (depend on) one or more of the skills (e.g., BSCP Skill 2) which depend on the skill identified as being the probable cause of the health state indicated at user interface element 606. Area 616 may identify any suitable number of skill consumers (skills which depend on probable cause skill, IDDP Skill 1, v.1.0.0.1) as “level 1 Impacts” indicating skills which directly depend on the probable cause skill. Area 616 may further identify any suitable number of skill consumers (e.g., skills which ultimately and indirectly depend on the probable cause skill) within area 616. The skills which are further downstream than the level 1 impacts may be referred to as “level 2 Impacts.”
In some embodiments, area 622 may include any suitable additional data related to contributing cause analysis (e.g., identifying a probable cause or probable causes) for the unhealthy state of the currently selected skill. In some embodiments, the user may select option 614 to rerun the trace (e.g., the operations performed by the Puffin Service for traversing the dependency graph and checking each nodes health status to determine one or more skills which are likely a contributing cause of the current health state of the selected skill). In some embodiments, area 622 may enable any suitable portion of contact information corresponding to one or more entities (e.g., a service team lead, a software engineer associated with the service, etc.). Selecting one of the options provided within area 622 may cause contact information to be copied and/or utilized for communicating the unhealthy status and/or any suitable portion of the contributing cause analysis data. By way of example, selecting option 624 may cause previously specified contact information to be utilized to request a service team associated with IDDP Skill 1, v.1.0.0.1 to report to a designated location for troubleshooting the current state of their corresponding skill.
In some embodiments, additional options are provided within area 626. These additional options may correspond to tracking alarm labels, viewing a dependency graph (e.g., a graph similar to the one generated and presented within areas 616 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 alarmLabel 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 800 may begin at 810, where Puffin Regional 806 may be seeded by Puffin Central 802 with all pre-defined skills, versions, and consumers. In some embodiments, Puffin Central 802 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 806. In some embodiments, Puffin Central 802 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 806. In some embodiments, Puffin Central 802 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 806. 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 811 may include any suitable operations for building a target set and ordered execution plan. By way of example, at 812, 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 814, 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 804 to execute a region build. By way of example, at 816, the Orchestrator 804 may identify, for a current step, all skills on which the current step depends. As described below, Puffin Regional 806 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 806 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. In some embodiments, Puffin Regional 806 may be configured to obtain capabilities data from storage, from Capabilities Service 112 of
At 818, Orchestrator 804 may query Puffing Regional 806 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 800 may continue to 820 without executing the operations at 818.
At 820, 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 822, at any suitable time, the Orchestrator 804 may identify the upstream skills are installed and healthy based on the skill states obtained from Puffin Regional 806. In response to identifying all upstream skills are installed and healthy, Orchestrator 804 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 806 to update the installation state attribute of the skills version data structure 412 of
At 824, Orchestrator 804 may execute operations to cause CIOS Central 808 to initiate one or more releases. In some embodiments, CIOS Central 808 may instruct an instance of CIOS Regional within the region (e.g., CIOS Regional 110 of
At 828, if the release was successful, Orchestrator 804 may transmit data to Puffin Regional 806 indicating that the skill(s) associated with the current step are now installed. Any suitable operations executed (e.g., by Orchestrator 804) to update (e.g., via Puffin Regional 806) 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 806 may update the skill(s)′ installation state to a value corresponding to the “INSTALLED” state. In some embodiments, Puffin Regional 806 may be configured to transmit any suitable data (e.g., to Capabilities Service 112 of
At 830, in some embodiments, Puffin Regional 806 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 832, Orchestrator 804 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 816-832 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 804 may conclude the region build at 832.
At step 1, at any suitable time, Puffin Regional 904 may receive or obtain an indication that capability A has been published. Puffin Regional 904 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 904 may manage skills table 910 and skill versions table 912. In some embodiments, skill table 910 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 904 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 904 may execute an application programming interface (API) call to Puffin Central 906 to inform Puffin Central 906 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 904. Puffin Regional 904 may present any suitable information corresponding to shadow skill A via any suitable user interface on demand. An example of one user interface is discussed in more detail below with respect to
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 906 and/or Puffing Regional 904 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 906 may be utilized for shadow skill A to be claimed by Service 1.
The method 1000 may begin at 1012, where Orchestrator 1002 may publish/transmit capability data indicating the availability of one or more capabilities (e.g., a capability referred to as “capability A”). In some embodiments, publishing/transmitting this data may utilize an application programming interface call exposed by Puffin Regional 1004 for obtaining capability data updates.
In response to receiving the data at 1012, Puffin Regional 1004 may be configured to perform database update 1014. In some embodiments, database update 1014 may be a single database update that includes any suitable combination of the updates discussed in connection with 1016 and/or 1018.
At 1016, Puffin Regional 1004 may add capability A to PR DB 1010. In some embodiments, adding capability A to PR DB 1010 may include generating one or more data structures. In some embodiments, a data structure may be generated that is specific to the capability and includes any suitable combination of attributes including, but not limited, any suitable combination of a capability identifier, a capability name, a createdAt attribute (indicating a time at which the capability was created), an updatedAt attribute (e.g., indicating a time at which the capability was last updated), a version identifier, an eventNumber, an isDeprecated flag, a namespace, or the like.
At 1016, Puffin Regional 1004 may add shadow skill A to PR DB 1010. In some embodiments, Puffin Regional 1004 may generate shadow skill A based at least in part on generating any suitable combination of the data structures of skills metadata 404 of
At 1020, Puffin Regional 1004 may communicate the data corresponding to shadow skill A to Puffin Central 1006 (e.g., via a predefined shadow skill API exposed by Puffin Central 1006).
At any suitable time or based on the receipt of the information provided at 1020, at 1022, Puffin Central 1006 may be configured to store the data corresponding to shadow skill A in PC DB 1008. Storing this data in PC DB 1008 may enable Puffin Central 1006 to present the information corresponding to shadow skill A at one or more interfaces provided/managed by Puffin Central 1006. By way of example, Puffin Central 1006 may present the data corresponding to shadow skill A via user interface 1100, discussed below in more detail with respect to
At any suitable time, user 1009 may provide input via user interface 1100 or any suitable interface managed by Puffin Central 1006 to claim shadow skill A. Claiming a shadow skill is intended to refer to causing the shadow skill (corresponding to a set of data structures that define the shadow skill) to be associated with a particular service (e.g., a service designated by user input provided at the user interface 1100 by user 1009). User input, including at least an identifier associated with the service for which the shadow skill A is being claimed, may be transmitted to Puffin Central 1006 at 1024. In some embodiments, Puffin Central 1006 may update the data corresponding to the shadow skill in PC DB 1008 in response to receiving the data at 1024, or at any suitable time.
At 1026, user 1009 may edit any suitable attribute of the shadow skill using various user interface elements of one or more user interfaces managed by Puffin Central 1006. Puffin Central 1006 may store the association received at 1024 and/or any suitable updates received at 1026 within PC DB 1008 at 1028. This update may cause Puffin Central 1006 to exclude shadow skill A from the list of unclaimed shadow skills presented at the user interfaces it manages.
As depicted, user interface 1100 may include area 1102 which may be configured to present any suitable number of shadow skills and corresponding metadata. Each entry presented within area 1102 may correspond to a different shadow skill (e.g., one of the shadow skills and corresponding data stored in PC DB 1008 as discussed above in connection with
As shadow skill metadata may be added or changed over time, user interface 1100 may include refresh option 1104. Upon receiving an indication that refresh option 1104 has been selected, Puffin Central (e.g., Puffin Central 1006 of
User interface 1100 may include any suitable filtering options for filtering the entries within area 1102. By way of example, one or more keywords may be provided via search box 1112. Upon selecting search button 1114, the entries within area 1102 may be updated to include entries that relate, match, or otherwise correspond to the user input provided via search box 1112.
In some embodiments, selecting option 1116 may present one or more additional options corresponding to a particular shadow skill. By way of example, selecting option 1116 may present the user with an option for claiming the corresponding shadow skill. In some embodiments, selecting option 1116 may cause a pop-up window to be displayed or selection option 1116 may navigate the user to a user interface at which a service identifier corresponding to the service for which the shadow skill is being claimed may be provided. In some embodiments, selecting option 1126 may navigate the user to a user interface similar to user interface 600 of
The method 1200 may begin at 1202, where a plurality of skills is managed (e.g., by Puffin Central 120 and/or Puffin Regional 118). In some embodiments, the plurality of skills correspond to a plurality of services to be deployed by a cloud infrastructure orchestration system (e.g., CIOS 102) during a process associated with building a data center. In some embodiments, a first skill (e.g., skill metadata 404 of
At 1204, an association may be maintained between the second skill of the plurality of skills and a corresponding capability of a plurality of capabilities associated with the plurality of services to be deployed. By way of example, a Skill Data Structure (e.g., Skill Data Structure 410) may store a set of capabilities identifiers (e.g., via the “capabilities” attributes) that indicate which capabilities the skill is to replace. These capability identifiers may further indicate which capabilities are to be published on receipt of one or more skill state transitions and/or which published capabilities may indicate a state transition of the corresponding skill.
At 1206, Puffin Service may identify that the corresponding capability associated with the second skill is available. In some embodiments, the identification may include receiving an indication that the capability has been published (e.g., from Orchestrator 106, from Capabilities Service 112, from CIOS Regional 110, from worker 330/338, etc.).
At 1208, Puffin Service may transition the second skill of the plurality of skills from a first state of the plurality of skill states (e.g., “SELECTED”) to a second state of the plurality of skill states (“INSTALLED”) based at least in part on the association between the second skill and the corresponding capability.
At 1210, Puffin Service may track progress of the cloud infrastructure orchestration system through the process associated with building the data center. In some embodiments, the tracking may be performed based at least in part on transitioning the second skill from the first state to the second state. By way of example, Puffin Service may begin tracking health of a skill based at least in part on transitioning the second skill to “INSTALLED,” by otherwise identifying that a current state of the second skill is associated with an installed state, or by identifying an indication, in general, that the second skill has been installed.
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 1306 can include a local peering gateway (LPG) 1310 that can be communicatively coupled to a secure shell (SSH) VCN 1312 via an LPG 1310 contained in the SSH VCN 1312. The SSH VCN 1312 can include an SSH subnet 1314, and the SSH VCN 1312 can be communicatively coupled to a control plane VCN 1316 via the LPG 1310 contained in the control plane VCN 1316. Also, the SSH VCN 1312 can be communicatively coupled to a data plane VCN 1318 via an LPG 1310. The control plane VCN 1316 and the data plane VCN 1318 can be contained in a service tenancy 1319 that can be owned and/or operated by the IaaS provider.
The control plane VCN 1316 can include a control plane demilitarized zone (DMZ) tier 1320 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 1320 can include one or more load balancer (LB) subnet(s) 1322, a control plane app tier 1324 that can include app subnet(s) 1326, a control plane data tier 1328 that can include database (DB) subnet(s) 1330 (e.g., frontend DB subnet(s) and/or backend DB subnet(s)). The LB subnet(s) 1322 contained in the control plane DMZ tier 1320 can be communicatively coupled to the app subnet(s) 1326 contained in the control plane app tier 1324 and an Internet gateway 1334 that can be contained in the control plane VCN 1316, and the app subnet(s) 1326 can be communicatively coupled to the DB subnet(s) 1330 contained in the control plane data tier 1328 and a service gateway 1336 and a network address translation (NAT) gateway 1338. The control plane VCN 1316 can include the service gateway 1336 and the NAT gateway 1338.
The control plane VCN 1316 can include a data plane mirror app tier 1340 that can include app subnet(s) 1326. The app subnet(s) 1326 contained in the data plane mirror app tier 1340 can include a virtual network interface controller (VNIC) 1342 that can execute a compute instance 1344. The compute instance 1344 can communicatively couple the app subnet(s) 1326 of the data plane mirror app tier 1340 to app subnet(s) 1326 that can be contained in a data plane app tier 1346.
The data plane VCN 1318 can include the data plane app tier 1346, a data plane DMZ tier 1348, and a data plane data tier 1350. The data plane DMZ tier 1348 can include LB subnet(s) 1322 that can be communicatively coupled to the app subnet(s) 1326 of the data plane app tier 1346 and the Internet gateway 1334 of the data plane VCN 1318. The app subnet(s) 1326 can be communicatively coupled to the service gateway 1336 of the data plane VCN 1318 and the NAT gateway 1338 of the data plane VCN 1318. The data plane data tier 1350 can also include the DB subnet(s) 1330 that can be communicatively coupled to the app subnet(s) 1326 of the data plane app tier 1346.
The Internet gateway 1334 of the control plane VCN 1316 and of the data plane VCN 1318 can be communicatively coupled to a metadata management service 1352 that can be communicatively coupled to public Internet 1354. Public Internet 1354 can be communicatively coupled to the NAT gateway 1338 of the control plane VCN 1316 and of the data plane VCN 1318. The service gateway 1336 of the control plane VCN 1316 and of the data plane VCN 1318 can be communicatively coupled to cloud services 1356.
In some examples, the service gateway 1336 of the control plane VCN 1316 or of the data plane VCN 1318 can make application programming interface (API) calls to cloud services 1356 without going through public Internet 1354. The API calls to cloud services 1356 from the service gateway 1336 can be one-way: the service gateway 1336 can make API calls to cloud services 1356, and cloud services 1356 can send requested data to the service gateway 1336. But, cloud services 1356 may not initiate API calls to the service gateway 1336.
In some examples, the secure host tenancy 1304 can be directly connected to the service tenancy 1319, which may be otherwise isolated. The secure host subnet 1308 can communicate with the SSH subnet 1314 through an LPG 1310 that may enable two-way communication over an otherwise isolated system. Connecting the secure host subnet 1308 to the SSH subnet 1314 may give the secure host subnet 1308 access to other entities within the service tenancy 1319.
The control plane VCN 1316 may allow users of the service tenancy 1319 to set up or otherwise provision desired resources. Desired resources provisioned in the control plane VCN 1316 may be deployed or otherwise used in the data plane VCN 1318. In some examples, the control plane VCN 1316 can be isolated from the data plane VCN 1318, and the data plane mirror app tier 1340 of the control plane VCN 1316 can communicate with the data plane app tier 1346 of the data plane VCN 1318 via VNICs 1342 that can be contained in the data plane mirror app tier 1340 and the data plane app tier 1346.
In some examples, users of the system, or customers, can make requests, for example create, read, update, or delete (CRUD) operations, through public Internet 1354 that can communicate the requests to the metadata management service 1352. The metadata management service 1352 can communicate the request to the control plane VCN 1316 through the Internet gateway 1334. The request can be received by the LB subnet(s) 1322 contained in the control plane DMZ tier 1320. The LB subnet(s) 1322 may determine that the request is valid, and in response to this determination, the LB subnet(s) 1322 can transmit the request to app subnet(s) 1326 contained in the control plane app tier 1324. If the request is validated and requires a call to public Internet 1354, the call to public Internet 1354 may be transmitted to the NAT gateway 1338 that can make the call to public Internet 1354. Metadata that may be desired to be stored by the request can be stored in the DB subnet(s) 1330.
In some examples, the data plane mirror app tier 1340 can facilitate direct communication between the control plane VCN 1316 and the data plane VCN 1318. 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 1318. Via a VNIC 1342, the control plane VCN 1316 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 1318.
In some embodiments, the control plane VCN 1316 and the data plane VCN 1318 can be contained in the service tenancy 1319. In this case, the user, or the customer, of the system may not own or operate either the control plane VCN 1316 or the data plane VCN 1318. Instead, the IaaS provider may own or operate the control plane VCN 1316 and the data plane VCN 1318, both of which may be contained in the service tenancy 1319. 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 1354, which may not have a desired level of threat prevention, for storage.
In other embodiments, the LB subnet(s) 1322 contained in the control plane VCN 1316 can be configured to receive a signal from the service gateway 1336. In this embodiment, the control plane VCN 1316 and the data plane VCN 1318 may be configured to be called by a customer of the IaaS provider without calling public Internet 1354. 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 1319, which may be isolated from public Internet 1354.
The control plane VCN 1416 can include a control plane DMZ tier 1420 (e.g., the control plane DMZ tier 1320 of
The control plane VCN 1416 can include a data plane mirror app tier 1440 (e.g., the data plane mirror app tier 1340 of
The Internet gateway 1434 contained in the control plane VCN 1416 can be communicatively coupled to a metadata management service 1452 (e.g., the metadata management service 1352 of
In some examples, the data plane VCN 1418 can be contained in the customer tenancy 1421. In this case, the IaaS provider may provide the control plane VCN 1416 for each customer, and the IaaS provider may, for each customer, set up a unique compute instance 1444 that is contained in the service tenancy 1419. Each compute instance 1444 may allow communication between the control plane VCN 1416, contained in the service tenancy 1419, and the data plane VCN 1418 that is contained in the customer tenancy 1421. The compute instance 1444 may allow resources, that are provisioned in the control plane VCN 1416 that is contained in the service tenancy 1419, to be deployed or otherwise used in the data plane VCN 1418 that is contained in the customer tenancy 1421.
In other examples, the customer of the IaaS provider may have databases that live in the customer tenancy 1421. In this example, the control plane VCN 1416 can include the data plane mirror app tier 1440 that can include app subnet(s) 1426. The data plane mirror app tier 1440 can reside in the data plane VCN 1418, but the data plane mirror app tier 1440 may not live in the data plane VCN 1418. That is, the data plane mirror app tier 1440 may have access to the customer tenancy 1421, but the data plane mirror app tier 1440 may not exist in the data plane VCN 1418 or be owned or operated by the customer of the IaaS provider. The data plane mirror app tier 1440 may be configured to make calls to the data plane VCN 1418 but may not be configured to make calls to any entity contained in the control plane VCN 1416. The customer may desire to deploy or otherwise use resources in the data plane VCN 1418 that are provisioned in the control plane VCN 1416, and the data plane mirror app tier 1440 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 1418. In this embodiment, the customer can determine what the data plane VCN 1418 can access, and the customer may restrict access to public Internet 1454 from the data plane VCN 1418. The IaaS provider may not be able to apply filters or otherwise control access of the data plane VCN 1418 to any outside networks or databases. Applying filters and controls by the customer onto the data plane VCN 1418, contained in the customer tenancy 1421, can help isolate the data plane VCN 1418 from other customers and from public Internet 1454.
In some embodiments, cloud services 1456 can be called by the service gateway 1436 to access services that may not exist on public Internet 1454, on the control plane VCN 1416, or on the data plane VCN 1418. The connection between cloud services 1456 and the control plane VCN 1416 or the data plane VCN 1418 may not be live or continuous. Cloud services 1456 may exist on a different network owned or operated by the IaaS provider. Cloud services 1456 may be configured to receive calls from the service gateway 1436 and may be configured to not receive calls from public Internet 1454. Some cloud services 1456 may be isolated from other cloud services 1456, and the control plane VCN 1416 may be isolated from cloud services 1456 that may not be in the same region as the control plane VCN 1416. For example, the control plane VCN 1416 may be located in “Region 1,” and cloud service “Deployment 13,” may be located in Region 1 and in “Region 2.” If a call to Deployment 13 is made by the service gateway 1436 contained in the control plane VCN 1416 located in Region 1, the call may be transmitted to Deployment 13 in Region 1. In this example, the control plane VCN 1416, or Deployment 13 in Region 1, may not be communicatively coupled to, or otherwise in communication with, Deployment 13 in Region 2.
The control plane VCN 1516 can include a control plane DMZ tier 1520 (e.g., the control plane DMZ tier 1320 of
The data plane VCN 1518 can include a data plane app tier 1546 (e.g., the data plane app tier 1346 of
The untrusted app subnet(s) 1562 can include one or more primary VNICs 1564(1)-(N) that can be communicatively coupled to tenant virtual machines (VMs) 1566(1)-(N). Each tenant VM 1566(1)-(N) can be communicatively coupled to a respective app subnet 1567(1)-(N) that can be contained in respective container egress VCNs 1568(1)-(N) that can be contained in respective customer tenancies 1570(1)-(N). Respective secondary VNICs 1572(1)-(N) can facilitate communication between the untrusted app subnet(s) 1562 contained in the data plane VCN 1518 and the app subnet contained in the container egress VCNs 1568(1)-(N). Each container egress VCNs 1568(1)-(N) can include a NAT gateway 1538 that can be communicatively coupled to public Internet 1554 (e.g., public Internet 1354 of
The Internet gateway 1534 contained in the control plane VCN 1516 and contained in the data plane VCN 1518 can be communicatively coupled to a metadata management service 1552 (e.g., the metadata management system 1352 of
In some embodiments, the data plane VCN 1518 can be integrated with customer tenancies 1570. 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 1546. Code to run the function may be executed in the VMs 1566(1)-(N), and the code may not be configured to run anywhere else on the data plane VCN 1518. Each VM 1566(1)-(N) may be connected to one customer tenancy 1570. Respective containers 1571(1)-(N) contained in the VMs 1566(1)-(N) may be configured to run the code. In this case, there can be a dual isolation (e.g., the containers 1571(1)-(N) running code, where the containers 1571(1)-(N) may be contained in at least the VM 1566(1)-(N) that are contained in the untrusted app subnet(s) 1562), 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 1571(1)-(N) may be communicatively coupled to the customer tenancy 1570 and may be configured to transmit or receive data from the customer tenancy 1570. The containers 1571(1)-(N) may not be configured to transmit or receive data from any other entity in the data plane VCN 1518. Upon completion of running the code, the IaaS provider may kill or otherwise dispose of the containers 1571(1)-(N).
In some embodiments, the trusted app subnet(s) 1560 may run code that may be owned or operated by the IaaS provider. In this embodiment, the trusted app subnet(s) 1560 may be communicatively coupled to the DB subnet(s) 1530 and be configured to execute CRUD operations in the DB subnet(s) 1530. The untrusted app subnet(s) 1562 may be communicatively coupled to the DB subnet(s) 1530, but in this embodiment, the untrusted app subnet(s) may be configured to execute read operations in the DB subnet(s) 1530. The containers 1571(1)-(N) that can be contained in the VM 1566(1)-(N) of each customer and that may run code from the customer may not be communicatively coupled with the DB subnet(s) 1530.
In other embodiments, the control plane VCN 1516 and the data plane VCN 1518 may not be directly communicatively coupled. In this embodiment, there may be no direct communication between the control plane VCN 1516 and the data plane VCN 1518. However, communication can occur indirectly through at least one method. An LPG 1510 may be established by the IaaS provider that can facilitate communication between the control plane VCN 1516 and the data plane VCN 1518. In another example, the control plane VCN 1516 or the data plane VCN 1518 can make a call to cloud services 1556 via the service gateway 1536. For example, a call to cloud services 1556 from the control plane VCN 1516 can include a request for a service that can communicate with the data plane VCN 1518.
The control plane VCN 1616 can include a control plane DMZ tier 1620 (e.g., the control plane DMZ tier 1320 of
The data plane VCN 1618 can include a data plane app tier 1646 (e.g., the data plane app tier 1346 of
The untrusted app subnet(s) 1662 can include primary VNICs 1664(1)-(N) that can be communicatively coupled to tenant virtual machines (VMs) 1666(1)-(N) residing within the untrusted app subnet(s) 1662. Each tenant VM 1666(1)-(N) can run code in a respective container 1667(1)-(N) and be communicatively coupled to an app subnet 1626 that can be contained in a data plane app tier 1646 that can be contained in a container egress VCN 1668. Respective secondary VNICs 1672(1)-(N) can facilitate communication between the untrusted app subnet(s) 1662 contained in the data plane VCN 1618 and the app subnet contained in the container egress VCN 1668. The container egress VCN can include a NAT gateway 1638 that can be communicatively coupled to public Internet 1654 (e.g., public Internet 1354 of
The Internet gateway 1634 contained in the control plane VCN 1616 and contained in the data plane VCN 1618 can be communicatively coupled to a metadata management service 1652 (e.g., the metadata management system 1352 of
In some examples, the pattern illustrated by the architecture of block diagram 1600 of
In other examples, the customer can use the containers 1667(1)-(N) to call cloud services 1656. In this example, the customer may run code in the containers 1667(1)-(N) that requests a service from cloud services 1656. The containers 1667(1)-(N) can transmit this request to the secondary VNICs 1672(1)-(N) that can transmit the request to the NAT gateway that can transmit the request to public Internet 1654. Public Internet 1654 can transmit the request to LB subnet(s) 1622 contained in the control plane VCN 1616 via the Internet gateway 1634. In response to determining the request is valid, the LB subnet(s) can transmit the request to app subnet(s) 1626 that can transmit the request to cloud services 1656 via the service gateway 1636.
It should be appreciated that IaaS architectures 1300, 1400, 1500, 1600 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 1702 provides a mechanism for letting the various components and subsystems of computer system 1700 communicate with each other as intended. Although bus subsystem 1702 is shown schematically as a single bus, alternative embodiments of the bus subsystem may utilize multiple buses. Bus subsystem 1702 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 1704, which can be implemented as one or more integrated circuits (e.g., a conventional microprocessor or microcontroller), controls the operation of computer system 1700. One or more processors may be included in processing unit 1704. These processors may include single core or multicore processors. In certain embodiments, processing unit 1704 may be implemented as one or more independent processing units 1732 and/or 1734 with single or multicore processors included in each processing unit. In other embodiments, processing unit 1704 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 1704 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) 1704 and/or in storage subsystem 1718. Through suitable programming, processor(s) 1704 can provide various functionalities described above. Computer system 1700 may additionally include a processing acceleration unit 1706, which can include a digital signal processor (DSP), a special-purpose processor, and/or the like.
I/O subsystem 1708 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 1700 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 1700 may comprise a storage subsystem 1718 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 1704 provide the functionality described above. Storage subsystem 1718 may also provide a repository for storing data used in accordance with the present disclosure.
As depicted in the example in
System memory 1710 may also store an operating system 1716. Examples of operating system 1716 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 1700 executes one or more virtual machines, the virtual machines along with their guest operating systems (GOSs) may be loaded into system memory 1710 and executed by one or more processors or cores of processing unit 1704.
System memory 1710 can come in different configurations depending upon the type of computer system 1700. For example, system memory 1710 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 1710 may include a basic input/output system (BIOS) containing basic routines that help to transfer information between elements within computer system 1700, such as during start-up.
Computer-readable storage media 1722 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 1700 including instructions executable by processing unit 1704 of computer system 1700.
Computer-readable storage media 1722 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 1722 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 1722 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 1722 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 1700.
Machine-readable instructions executable by one or more processors or cores of processing unit 1704 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 1724 provides an interface to other computer systems and networks. Communications subsystem 1724 serves as an interface for receiving data from and transmitting data to other systems from computer system 1700. For example, communications subsystem 1724 may enable computer system 1700 to connect to one or more devices via the Internet. In some embodiments communications subsystem 1724 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 1724 can provide wired network connectivity (e.g., Ethernet) in addition to or instead of a wireless interface.
In some embodiments, communications subsystem 1724 may also receive input communication in the form of structured and/or unstructured data feeds 1726, event streams 1728, event updates 1730, and the like on behalf of one or more users who may use computer system 1700.
By way of example, communications subsystem 1724 may be configured to receive data feeds 1726 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 1724 may also be configured to receive data in the form of continuous data streams, which may include event streams 1728 of real-time events and/or event updates 1730, 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 1724 may also be configured to output the structured and/or unstructured data feeds 1726, event streams 1728, event updates 1730, 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 1700.
Computer system 1700 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 1700 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. 63/503,143, filed on May 18, 2023, entitled “Techniques for Validating and Tracking Region Build Skills,” the disclosure of which is herein incorporated by reference in its entirety for all purposes.
| Number | Date | Country | |
|---|---|---|---|
| 63503143 | May 2023 | US |
