Patent Grant
12015603
Computing devices can utilize communication networks to exchange data. Companies and organizations operate computer networks that interconnect a number of computing devices to support operations or to provide services to third parties. The computing systems can be located in a single geographic location or located in multiple, distinct geographic locations (e.g., interconnected via private or public communication networks). Specifically, data centers or data processing centers, herein generally referred to as a “data center,” may include a number of interconnected computing systems to provide computing resources to users of the data center. The data centers may be private data centers operated on behalf of an organization or public data centers operated on behalf, or for the benefit of, the general public.
To facilitate increased utilization of data center resources, virtualization technologies allow a single physical computing device to host one or more virtual machine instances that appear and operate as independent computing devices to users of a data center. With virtualization, the single physical computing device can create, maintain, delete, or otherwise manage virtual machines in a dynamic manner. In turn, users can request computer resources from a data center, including single computing devices or a configuration of networked computing devices, and be provided with varying numbers of virtual machine resources.
In some scenarios, virtual machine instances may be configured according to a number of virtual machine instance types to provide specific functionality. For example, various computing devices may be associated with different combinations of operating systems or operating system configurations, virtualized hardware resources and software applications to enable a computing device to provide different desired functionalities, or to provide similar functionalities more efficiently. These virtual machine instance type configurations are often contained within a device image, which includes static data containing the software (e.g., the OS and applications together with their configuration and data files, etc.) that the virtual machine will run once started. The device image is typically stored on the disk used to create or initialize the instance. Thus, a computing device may process the device image in order to implement the desired software configuration.
Generally, aspects of the present disclosure relate to serverless code execution and, in a particular example, a software as a service (SaaS) model hosted (at least partially) in a serverless code execution system. Serverless code execution systems can group together invocations that occur under a same account (or under a same account and for each function, or variation thereof) for efficiency purposes. Typically, there is not a security concern, as all invokes for a specific account can be assumed to share trust among one another. In the SaaS use case, all calls may be under the same account (the SaaS provider, referred to as “SaaS provider” or “tenant of serverless code execution system”), but it may be desirable to separate the calls. For instance, a calling party may not be the SaaS provider, but instead an end user of the SaaS provider (referred to as “sub-tenant” or “sub-tenants”). Alternatively, the SaaS provider may call a service on behalf of the end user. This application allows invocations to be grouped according to the SaaS end user, thus providing increased security when using serverless functions to provide SaaS resources.
The SaaS providers may define and invoke code without needing to own or manage servers by using, e.g., a serverless code execution system (which may itself be operated by another SaaS provider). In this context, the SaaS provider may act as a “second level” SaaS provider, providing software as a service utilizing a SaaS service provided by another SaaS provider, like a cloud services provider. Generally, as a first approach for providing a SaaS platform, the SaaS provider could define a single serverless function hosted by the serverless code execution system to serve each sub-tenant using a same serverless function in execution environments (which could be, e.g., VM instances or containers (with appropriate software packages)), but there may be a possibility of data persistence between separate calls to a same execution environment, thereby possibly exposing persistent data to unauthorized entities. For instance, if the SaaS provider uses a non-differentiated function on their account of the serverless code execution system, the serverless code execution system may use an idle environment (referred to as “warm”) for each call, therefore the SaaS provider does not incur higher costs to run the SaaS platform on the serverless execution environment (e.g., greater efficiency), and the serverless execution environment does not incur a high overhead of creating a new environment, which makes execution both faster and more efficient. In this case, the SaaS provider also enjoys the faster and more efficient execution of the serverless function. Therefore, this approach may offer higher operational efficiency and better utilization of infrastructure but could introduce security concerns. For instance, the serverless code execution system may generally be configured to provide isolation between functions, which functions may themselves be associated with a respective user account. Accordingly, by providing isolation between functions, the serverless code execution system may provide isolation between data of different accounts. Under this scenario, a SaaS provider using a single non-differentiated function may service calls for multiple end users with the same function, and thus without isolation between those calls. Accordingly, if a vulnerability existed within the function, inherent security provided by the serverless code execution system may be bypassed, and malicious requests might be able to access the service code or state used to process requests from other sub-tenants of the SaaS provider (thereby possibly exposing other sub-tenant data) and increases the attack surface as the service can have permissions to access data for all the sub-tenants of the SaaS provider. However, data nondisclosure between the various sub-tenants may be highly valued. As an alternative second approach, the SaaS provider could define dedicated infrastructure per sub-tenant on the serverless code execution system to serve each sub-tenant using their respective dedicated infrastructure. This would help minimize the security concerns but would result in increased operational complexity and poor utilization of infrastructure. Therefore, neither approach is satisfactory.
On the other hand, systems and methods of the present disclosure may enable the serverless code execution system to support a multi-tenant mode for serverless functions of a multi-tenant platform (for SaaS providers) on the serverless code execution system. Generally, a multi-tenant mode for serverless functions may utilize a shared model to build multi-tenanted applications (therefore avoiding dedicated infrastructure per sub-tenant), while minimizing the security concerns by provisioning a fresh execution environment to process requests from each sub-tenant using sub-tenant-specific execution environments (therefore avoiding exposing persistent data to unauthorized entities). Furthermore, multi-tenant mode of the serverless code execution system may manage credentials corresponding to a requesting sub-tenant, so that the invoked serverless function may access other tenant-level services that support multi-tenant architectures, such as Amazon™'s DynamoDB or other databases. With multi-tenant mode, an attacker cannot persist beyond the sub-tenant-specific execution environment and will not have permissions to access data for other sub-tenants (whether persistent data or in other tenant-level services).
Generally, SaaS providers may provide software services to end users. For instance, SaaS providers may provide software services on a subscription basis, or as a part of being a customer of a SaaS provider. In particular, certain services offered by SaaS providers may be hosted on the serverless execution environment as serverless functions. In this case, the SaaS providers may be a direct user (e.g., a customer) of the serverless execution environment (referred to as “tenants”), while end users of the SaaS providers may be sub-tenants of SaaS providers with respect to the serverless execution environment. In this manner, the serverless execution environment may provide sub-tenants the services of the serverless functions, as defined and uploaded by the SaaS providers to the serverless execution environment. In some cases, the sub-tenants of the SaaS providers may be enterprise end users (e.g., for an entity) that have their own sub-tenants (e.g., users associated with the entity, referred to as sub-sub-tenants). Generally, the serverless execution environment may handle calls from sub-sub-tenants of SaaS providers on a sub-sub-tenant basis or as-if the sub-sub-tenants are requesting calls on behalf of the enterprise end user (sub-tenant).
Generally, the serverless code execution system may manage execution of code on an on-demand basis. Furthermore, the serverless code execution system may provide a network-accessible service enabling users (e.g., developers of the SaaS providers) to submit or designate computer-executable code to be executed by execution environments on the serverless code execution system. Each set of code on the serverless code execution system may define a “function,” and implement specific functionality corresponding to that function when executed on an execution environment of the serverless code execution system. Individual executions of code of the function on the serverless code execution system may be referred to as an “execution” of the function. The serverless code execution system can further enable users to trigger execution of a function based on a variety of potential events, such as transmission of an application programming interface (“API”) call or a specially formatted hypertext transport protocol (“HTTP”) packet. Thus, users (generally) or sub-tenants (of SaaS providers in particular) may utilize the serverless code execution system to execute any specified executable code “on-demand,” without requiring configuration or maintenance of the underlying hardware or infrastructure on which the code is executed. Further, the serverless code execution system may be configured to execute functions in a rapid manner (e.g., in under 100 milliseconds [ms]), thus enabling execution of functions in “real-time” (e.g., with little or no perceptible delay to an end user). To enable this rapid execution, the serverless code execution system can include one or more execution environments that are “pre-warmed” or pre-initialized (e.g., booted into an operating system and executing a complete or substantially complete runtime environment) and configured to enable execution of user-defined code, such that the code may be rapidly executed in response to a request to execute the code, without delay caused by initializing the execution environment. Thus, when an execution of a function is triggered, the code corresponding to that function can be executed within a pre-initialized execution environment in a very short amount of time.
Generally, an “execution environment” may be a virtual machine instance or a container. Containers may be software containers, sometimes referred to as “OS-level virtualization” and hosted on a worker (sometimes referred to as a “host” or “host computing device”). Each execution environment may be divided by a virtualization boundary to ensure data security between respective execution environments. For example, each execution environment may exist within a partitioned user space on the worker, which logically partitions resources of the worker among execution environments on the worker. Each user space may, for example, represent a “chroot” jail.
In accordance with embodiments of the present disclosure, access to network services, such as serverless functions or network resources used by those functions, can be managed by use of identity and access management (IAM) roles and IAM policies. For instance, IAM roles and policies may define access (or not) to computer systems or resources based on an identity of a device requesting access to computer systems or resources. IAM policies may be defined by SaaS providers to indicate which sub-tenants (based on sub-tenant identity or a IAM role of the sub-tenant) may access (or not) computer systems or resources associated with the SaaS providers hosted by the serverless code execution system. In particular, the IAM policies may indicate which sub-tenants may invoke serverless functions associated with the SaaS providers. Moreover, an invoked serverless function may assume the role of a sub-tenant when interacting with network resources, thereby enabling access to sub-tenant-specific network resources.
In aspects of the present disclosure, the serverless code execution system may include one or more data stores including information for a set of IAM policies defining access to a plurality of serverless functions hosted by the serverless code execution system. A set of serverless functions of the plurality of serverless functions may be associated with a SaaS provider. The serverless code execution system may also include a plurality of worker devices hosting a plurality of execution environments. Each execution environment may be associated with a serverless function. A set of execution environments may be associated with the set of serverless functions. The set of execution environments may be partitioned based on sub-tenants of the SaaS provider. Generally, the serverless code execution system may only allow a specific sub-tenant to call a serverless function (per an associated IAM policy) and the serverless code execution system may call the serverless function on an execution environment associated with the that specific sub-tenant. In this manner, the SaaS provider may only need to manage one serverless function (thereby avoiding maintenance costs and additional infrastructure costs), while ensuring data security, as calls of sub-tenants may be portioned among sub-tenant-specific environments (such as use the sub-tenant-specific execution environment for the specific sub-tenant). Therefore, the serverless code execution system may not invoke, for a third party (e.g., another sub-tenant), the same serverless function on the sub-tenant-specific execution environment assigned to the sub-tenant, or serverless code execution system may not invoke, for the sub-tenant, a serverless function on a different sub-tenant-specific execution environment (thereby, increasing data security).
For instance, the serverless code execution system may receive a call to execute a serverless function, where the call includes a serverless function identifier and a sub-tenant identifier, determine a sub-tenant, from any number of sub-tenants, based on the sub-tenant identifier; in response to determining the sub-tenant, identify a sub-tenant-specific execution environment of the set of execution environments that is associated with the sub-tenant, where other calls to execute the serverless function from any of the other sub-tenants are blocked from being invoked on the sub-tenant-specific execution environment; and in response to identifying the sub-tenant-specific execution environment, invoke the serverless function on the sub-tenant-specific execution environment. In this manner, the one or more computing devices of the serverless code execution system may confirm whether a sub-tenant is authorized to access the serverless function and, if so, execute the serverless function on a sub-tenant-specific execution environment in a secure manner. Moreover, as the serverless code execution system may scale down (or up), the SaaS provider may receive the benefits of operational efficiency while maintaining data security.
In at least some embodiments, the serverless functions may try to retrieve data and use services from network resources that are particular to a sub-tenant. However, by default, the execution environments may execute under authentication of the SaaS provider. Providing the SaaS provider access to the sub-tenant-specific resources may reduce security of those resources and may be undesirable. This application provides a solution, whereby sub-tenant-specific execution environments can be authenticated as a sub-tenant (e.g., assume an IAM role of the sub-tenant). This allows those execution environments (and only those execution environments, not other execution environments of other SaaS sub-tenants) to access sub-tenant-specific resources in a secure manner. For instance, the sub-tenant-specific execution environment may interact with one or more tenant services to access sub-tenant data, in accordance with an authentication token indicating the sub-tenant. For instance, the sub-tenant-specific execution environment may assume the role of the sub-tenant using the authentication token to request data and/or services from tenant-level services, such as Amazon™'s DynamoDB. In this manner, the sub-tenant-specific execution environment may only be exposed to sub-tenant-specific information or functionality, as the sub-tenant-specific execution environment may be viewed as the sub-tenant by third party systems. The sub-tenant-specific execution environment may receive the authentication token from a worker that hosts the sub-tenant-specific execution environment, or the worker may modify outbound (e.g., requests from sub-tenant-specific execution environment to other services) to include the authentication token for the sub-tenant-specific execution environment. The authentication token may be based on the sub-tenant identifier and may modify session tags of the sub-tenant-specific execution environment. Moreover, in certain embodiments, the serverless code execution system may be a multi-tenant cloud services provider that maintains a set of execution environments. Each execution environment may be associated with a serverless function. The serverless function may be associated with a software as a service (SaaS) provider that is a tenant of the cloud services provider. The SaaS provider may provide services to a plurality of sub-tenants. The set of execution environments may be partitioned based on sub-tenants of the SaaS provider. In response to receiving a call to execute a serverless function, where the call includes a serverless function identifier and a sub-tenant identifier; the system may identify a sub-tenant-specific execution environment of the set of execution environments that is associated with the sub-tenant identifier; and invoke the serverless function on the sub-tenant-specific execution environment.
The serverless code execution system, to identify the sub-tenant-specific execution environment associated with the sub-tenant, may determine whether any execution environment of the set of execution environments are associated with the sub-tenant identifier. In this manner, the serverless code execution system may condition access based on sub-tenant identifier. Moreover, the serverless code execution system may determine whether any execution environment of the set of execution environments are associated with the sub-tenant identifier and the serverless function identifier. In this manner, the serverless code execution system may still condition access based on sub-tenant identifier, but also ensure the execution environment is defined to perform the serverless function (e.g., is capable of being updated to execute the corresponding code, or already has the corresponding code). Furthermore, the serverless code execution system may determine whether any execution environment of the set of execution environments are associated with the sub-tenant identifier, the serverless function identifier, and a version identifier. In this manner, the serverless code execution system may still condition access based on sub-tenant identifier, but also ensure the execution environment is defined to perform the correct version of the serverless function (e.g., is capable of being updated to execute the corresponding correct version of the code, or already has the corresponding correct version of the code). For instance, as the serverless code execution system may execute functions in a rapid manner, determining particular execution environments for version and function with respect to sub-tenant may assist in rapidly providing function processing and results.
The serverless code execution system may, in response to determining none of the set of execution environments are associated with the sub-tenant identifier (and/or the serverless function identifier or version identifier), instantiate the sub-tenant-specific execution environment. In this manner, the serverless code execution system may determine none of the set is current assigned to be used by the sub-tenant, so a new sub-tenant-specific execution environment for this particular sub-tenant is needed to be provisioned and used for this sub-tenant. As a part of instantiating a new sub-tenant-specific execution environment, an authentication token (discussed above) may be passed the sub-tenant-specific execution environment (or a worker hosting the sub-tenant-specific execution environment), so that the sub-tenant-specific execution environment assumes the role of the sub-tenant. As discussed above, the authentication token may secure sub-tenant data in third party systems, thereby increasing security of sub-tenant data within the serverless code execution system.
In particular, to instantiate the sub-tenant-specific execution environment, the serverless code execution system may select a non-tenant-specific execution environment in a warm state to be modified into the sub-tenant-specific execution environment, or create the sub-tenant-specific execution environment. For instance, a non-tenant-specific execution environment may be an execution environment that is not a part of any set of execution environments associated with any SaaS provider. Restated, the non-tenant-specific execution environment may be an execution environment that is not associated with a multi-tenant mode of the serverless code execution system. In this manner, the multi-tenant mode may quickly modify an already warm execution environment to invoke the serverless function and server a response. For instance, the warm non-tenant-specific execution environment may be selected as it has a basic configuration to be modified to be used for the sub-tenant-specific execution environment, or the non-tenant-specific execution environment may have various commonalities with a configuration needed to modify one or more parameters, etc. to become the sub-tenant-specific execution environment. In this manner, process time may be decreased and the serverless code execution system may respond more rapidly than if a new sub-tenant-specific execution environment had to be created. In the case a new sub-tenant-specific execution environment has to be created, the serverless code execution system may create a new execution environment as discussed below on a worker and assign the new execution environment to the sub-tenant, so that the new execution environment is a sub-tenant-specific execution environment.
The serverless code execution system may, in response to determining at least one execution environment of the set of execution environments are associated with the sub-tenant identifier (and, optionally, the serverless function identifier and/or the version identifier), select an execution environment of the at least one execution environment to be the sub-tenant-specific execution environment. In this manner, the serverless code execution system may condition access based on at least the sub-tenant identifier and process the call faster than creating a new sub-tenant-specific execution environment. Moreover, of all execution environments associated with the sub-tenant identifier, the serverless code execution system may prefer to select an execution environment that has a same serverless function identifier and a same version identifier, then an execution environment that has a same serverless function identifier and a different version identifier (to be updated to the correct version of the function), and then an execution environment that has a different serverless function identifier and a different version identifier (to be updated to this serverless function and this version thereof). In this manner, serverless code execution system may invoke the serverless function as fast as possible, while making as few modifications to already existing environments associated with the sub-tenant.
In another embodiment, the serverless code execution system may, before selecting the execution environment of the at least one execution environment to be the sub-tenant-specific execution environment, determine whether any of the at least one execution environment are available to handle the request. That is, even if there is at least one execution environment associated with the sub-tenant, only those that are available (e.g., warm and not in use) may be selected from to be invoked.
As will be appreciated by one of skill in the art in light of the present disclosure, the embodiments disclosed herein improve the ability of computing systems, such as serverless compute systems, to support SaaS providers (e.g., tenants of the serverless compute systems) with sub-tenants in a manner that supports generalized functions with restricted access to sub-tenant-specific data or services, thereby providing increased functionality and security. Moreover, the presently disclosed embodiments address technical problems inherent within computing systems; specifically, the difficulties in providing SaaS providers via serverless compute systems. For instance, there may be tradeoffs between efficiency and security. As discussed above, one the one hand, if execution environments are grouped together to serve multiple sub-tenants, the SaaS provider may have less to manage and the serverless code execution system may process calls faster and more efficiently, meanwhile sub-tenant data may be exposed to malicious requests. On the other hand, using isolated execution environments may provide stronger data security, while requiring higher infrastructure utilization and maintenance. These technical problems are addressed by the various technical solutions described herein, including a cloud computing service configured to provide sub-tenant-specific execution environments. Thus, the present disclosure represents an improvement on serverless code execution systems and computing systems in general.
The foregoing aspects and many of the attendant advantages of this disclosure will become more readily appreciated as the same become better understood by reference to the following description, when taken in conjunction with the accompanying drawings.
The illustrative environment 100 further includes one or more auxiliary services 106, which can interact with the serverless code execution system 110 to implement desired functionality on behalf of a user. Auxiliary services 106 can correspond to network-connected computing devices, such as servers, which generate data accessible to the serverless code execution system 110 or otherwise communicate to the serverless code execution system 110. For example, the auxiliary services 106 can include web services (e.g., associated with the user computing devices 102, with the serverless code execution system 110, or with third parties), databases, really simple syndication (“RSS”) readers, social networking sites, or any other source of network-accessible service or data source. In some instances, auxiliary services 106 may be invoked by code execution on the serverless code execution system 110, such as by API calls to the auxiliary services 106. In some instances, auxiliary services 106 may be associated with the serverless code execution system 110, e.g., to provide billing or logging services to the serverless code execution system 110. In some instances, auxiliary services 106 actively transmit information, such as API calls or other task-triggering information, to the serverless code execution system 110. In other instances, auxiliary services 106 may be passive, such that data is made available for access by the serverless code execution system 110. For example, components of the serverless code execution system 110 may periodically poll such passive data sources, and trigger execution of code within the serverless code execution system 110 based on the data provided. While depicted in
The client devices 102, auxiliary services 106, and serverless code execution system 110 may communicate via a network 104, which may include any wired network, wireless network, or combination thereof. For example, the network 104 may be a personal area network, local area network, wide area network, over-the-air broadcast network (e.g., for radio or television), cable network, satellite network, cellular telephone network, or combination thereof. As a further example, the network 104 may be a publicly accessible network of linked networks, possibly operated by various distinct parties, such as the Internet. In some embodiments, the network 104 may be a private or semi-private network, such as a corporate or university intranet. The network 104 may include one or more wireless networks, such as a Global System for Mobile Communications (GSM) network, a Code Division Multiple Access (CDMA) network, a Long Term Evolution (LTE) network, or any other type of wireless network. The network 104 can use protocols and components for communicating via the Internet or any of the other aforementioned types of networks. For example, the protocols used by the network 104 may include Hypertext Transfer Protocol (HTTP), HTTP Secure (HTTPS), Message Queue Telemetry Transport (MQTT), Constrained Application Protocol (CoAP), and the like. Protocols and components for communicating via the Internet or any of the other aforementioned types of communication networks are well known to those skilled in the art and, thus, are not described in more detail herein.
The serverless code execution system 110 is depicted in
Further, the serverless code execution system 110 may be implemented directly in hardware or software executed by hardware devices and may, for instance, include one or more physical or virtual servers implemented on physical computer hardware configured to execute computer executable instructions for performing various features that will be described herein. The one or more servers may be geographically dispersed or geographically co-located, for instance, in one or more data centers. In some instances, the one or more servers may operate as part of a system of rapidly provisioned and released computing resources, often referred to as a “cloud computing environment.”
In the example of
In
To enable interaction with the serverless code execution system 110, the system 110 includes multiple frontends 120, which enable interaction with the serverless code execution system 110. In an illustrative embodiment, the frontends 120 serve as a “front door” to the other services provided by the serverless code execution system 110, enabling users (via user computing devices 102) to provide, request execution of, and view results of computer executable source code. The frontends 120 include a variety of components to enable interaction between the serverless code execution system 110 and other computing devices. For example, each frontend 120 may include a request interface providing user computing devices 102 with the ability to upload or otherwise communication user-specified code and associated data sets to the serverless code execution system 110 (e.g., in the form of executable code or a disk image) and to thereafter request execution of that code. In one embodiment, the request interface communicates with external computing devices (e.g., user computing devices 102, auxiliary services 106, etc.) via a graphical user interface (GUI), CLI, or API. The frontends 120 process the requests and makes sure that the requests are properly authorized. For example, the frontends 120 may determine whether the user associated with the request is authorized to access the source code specified in the request.
References to source code as used herein may refer to any program code (e.g., a program, routine, subroutine, thread, etc.) written in a specific program language. In the present disclosure, the terms “source code,” “user code,” and “program code,” may be used interchangeably. Source code which has been compiled for execution on a specific device is generally referred to herein as “machine code.” Both “source code” and “machine code” are representations of the same instructions, which may be collectively referred to as “code.” Such code may be executed to achieve a specific function, for example, in connection with a particular web application or mobile application developed by the user. As noted above, individual collections of code (e.g., to achieve a specific function) are referred to herein as “tasks” or “functions,” while specific executions of that code are referred to as “task executions,” “function executions,” “code executions,” or simply “executions.” Source code for a task may be written, by way of non-limiting example, in JavaScript (e.g., node.js), Java, Python, and/or Ruby (and/or another programming language). Tasks may be “triggered” for execution on the serverless code execution system 110 in a variety of manners. In one embodiment, a user or other computing device may transmit a request to execute a task may, which can generally be referred to as “call” to execute of the task (e.g., a “task call,” a “function call,” etc.). Such calls may include an identifier of the task to be executed and one or more arguments to be used for executing the task. A request interface of the frontend 120 may receive calls to execute tasks as Hypertext Transfer Protocol Secure (HTTPS) requests from a user. Also, any information (e.g., headers and parameters) included in the HTTPS request may also be processed and utilized when executing a task. As discussed above, any other protocols, including, for example, HTTP, MQTT, and CoAP, may be used to transfer the message containing a task call to the request interface.
Prior to calling for execution of a task, an end user may submit (e.g., to a frontend 120) for the task and associated data to be used to execute the task. In one embodiment, the code is provided in the form of an executable code file or a disk image containing the code and other data that the code may use during execution. Illustratively, creation of a task may result in the frontend 120 creating metadata for the task, which defines for example the user creating the task, the executable code file/the disk image used to facilitate execution of the task, trigger conditions for the task, and the like. In one embodiment, tasks may be versioned, with task metadata identifying the available versions and at least some other metadata for a task may vary across versions. For example, different versions may be associated with different executable code files or disk images. Metadata is illustratively stored in the task metadata store 130.
On submitting an executable code file or a disk image, the executable code file or image is illustratively stored (e.g., by the frontend 120) in the configuration data store 174. In one embodiment, each executable code file is stored as a text file. In another embodiment, each image is stored as a set of layers and a manifest identifying the layers making up the disk image. Separate storage of layers and a manifest may enable, for example, deduplication of layers. For example, where two images share a layer, the configuration data store 174 may store only a single copy of that layer. Deduplication may be conducted, for example, based on a digital fingerprint of a layer. Illustratively, each layer may be identified in the store 174 based on a digital fingerprint, such as a hash value, message authentication code (MAC) or the like, which fingerprint is calculable based on the contents of the layer. Accordingly, when two layers share a fingerprint, the system 110 may conclude that the two layers are identical and thus store only a single copy of that layer. As noted above, layers may associated with software that is versioned, such that a first layer corresponds to a first version of software and a second layer corresponds to a second version of software. For ease of reference, the present disclosure refers to such layers as themselves being versioned. However, while the system 110 may in some cases maintain versioning information for layers directly, it may additionally or alternatively maintain versioning information for software, along with information mapping such software versions to particular layers (e.g., a first layer corresponds to version 1 of a particular software, a second layer corresponds to version 2, etc.). In some cases, each disk image is additionally or alternatively stored as an unlayered image, such as one or more files providing a block-level representation of a file system. For example, the system 110 may “flatten” a layered disk image by using the layers to create a file system, and then saving a non-layered representation of that file system to the configuration data store 174. In some cases, the non-layered representation may be divided into a number of distinct chunks, which may be deduplicated within the data store 174. Generation and handling of file system chunks is discussed in more detail in U.S. patent application Ser. No. 17/105,250, filed Nov. 25, 2020 and entitled “LOW LATENCY ACCESS TO DATA SETS USING SHARED DATA SET PORTIONS” (the “'250 Applications”) the entirety of which is hereby incorporated by reference.
Both the task metadata store 130 and the configuration data store 174 can correspond to any persistent data store. In one embodiment, the task metadata store 130 and the configuration data store 174 are implemented as logical storage on a cloud storage service, such as an object storage system. An example of such an object storage system is AMAZON™'s SIMPLE STORAGE SERVICE™ (or “S3™”).
After a user has created a task on the serverless code execution system 110, the system 110 may accept calls to execute that task. To calls to execute a task, the frontend 120 can include an execution queue, which can maintain a record of requested task executions. Illustratively, the number of simultaneous task executions by the serverless code execution system 110 is limited, and as such, new task executions initiated at the serverless code execution system 110 (e.g., via an API call, via a call from an executed or executing task, etc.) may be placed on the execution queue and processed, e.g., in a first-in-first-out order. In some embodiments, the serverless code execution system 110 may include multiple execution queues, such as individual execution queues for each user account. For example, users of the serverless code execution system 110 may desire to limit the rate of task executions on the serverless code execution system 110 (e.g., for cost reasons). Thus, the serverless code execution system 110 may utilize an account-specific execution queue to throttle the rate of simultaneous task executions by a specific user account. In some instances, the serverless code execution system 110 may prioritize task executions, such that task executions of specific accounts or of specified priorities bypass or are prioritized within the execution queue. In other instances, the serverless code execution system 110 may execute tasks immediately or substantially immediately after receiving a call for that task, and thus, the execution queue may be omitted.
As noted above, tasks may be triggered for execution at the serverless code execution system 110 based on explicit calls from user computing devices 102 (e.g., as received at a request interface). In some embodiments when SaaS providers are tenants and end users of the SaaS providers are sub-tenants, calls may not be sent from an entity that owns a specific task. For instance, the tasks may be owned by SaaS providers, and sub-tenants may transmit calls to the serverless execution system 110 to invoke the tasks. Alternatively or additionally, tasks may be triggered for execution at the serverless code execution system 110 based on data retrieved from one or more auxiliary services 106. To facilitate interaction with auxiliary services 106, the frontend 120 can include a polling interface, which operates to poll auxiliary services 106 for data. Illustratively, the polling interface may periodically transmit a request to one or more user-specified auxiliary services 106 to retrieve any newly available data (e.g., social network “posts,” news articles, files, records, etc.), and to determine whether that data corresponds to user-established criteria triggering execution a task on the serverless code execution system 110. Illustratively, criteria for execution of a task may include, but is not limited to, whether new data is available at the auxiliary services 106, the type or content of the data, or timing information corresponding to the data. In some instances, the auxiliary services 106 may function to notify the frontend 120 of the availability of new data, and thus the polling service may be unnecessary with respect to such services.
In addition to tasks executed based on explicit user calls and data from auxiliary services 106, the serverless code execution system 110 may in some instances operate to trigger execution of tasks independently. For example, the serverless code execution system 110 may operate (based on instructions from a user) to trigger execution of a task at each of a number of specified time intervals (e.g., every 10 minutes).
The frontend 120 can further includes an output interface configured to output information regarding the execution of tasks on the serverless code execution system 110. Illustratively, the output interface may transmit data regarding task executions (e.g., results of a task, errors related to the task execution, or details of the task execution, such as total time required to complete the execution, total data processed via the execution, etc.) to the user computing devices 102 or to auxiliary services 106, which may include, for example, billing or logging services. The output interface may further enable transmission of data, such as service calls, to auxiliary services 106. For example, the output interface may be utilized during execution of a task to transmit an API request to an external service 106 (e.g., to store data generated during execution of the task).
Code executions triggered on the serverless code execution system 110 of
As shown in
To facilitate rapid execution of code, each worker 181 may be configured to maintain a set of instances 183 in a “pre-warmed” state, being at least partially configured to begin execution of code. For example, instances may be created on the worker and configured with access to computing resources (CPU, RAM, drive storage, etc.). In some cases, it may be impractical or impossible to maintain instances 183 in a fully warmed state for all possible code executions, as executions may be associated with a wide variety of at least partially distinct data sets (e.g., executable code files, disk images, and/or snapshots). Thus, instances 183 may be maintained in a “greatest commonality” for a given group of tasks, such as being provisioned with a set of computing resources common to those tasks, being configured to accept an operating system type used by those tasks, etc.
On receiving instructions to provision an instance 183 to support execution of the task, the worker 181 may adjust the configuration of the instance 183 to support that execution. Specifically, the worker 181 may provision the instance 183 with access to an executable code file, a disk image, or snapshot corresponding to the task. In some instances, the worker 181 may retrieve the disk image from the configuration data store 174 and store the full image locally. In other instances, the worker 181 may provide to an instance 183 what appears to be full local access to the disk image or snapshot, while “lazily” retrieving portions of that image or snapshot in response to a request to read such portions. Techniques for providing lazy retrieval of image portions are discussed in the '250 Applications, incorporated by reference above.
In addition, the system 110 includes a number of components for facilitating distribution of calls to execute a task from frontends 120 to particular VM instances 183. For example, the serverless code execution system 110 includes one or more worker managers 140 configured to manage execution environments (e.g., virtual machine instances) hosted by workers 181 among a worker fleet 180. The worker managers 140—each of which are illustratively implemented as physical or virtual-on-physical devices—illustratively “lease” particular VM instances 183 within the fleet 180, thus gaining operational control to, for example, instruct virtual machine instances 183 to execute code of the task. Thus, on receiving a call to execute a task, a frontend 120 may distribute the call to a worker manager 140, which may identify a currently-leased VM instance 183 in which to implement the task, and cause the instance 183 to implement the task. Example interactions for distributing a call from a frontend 120 to a worker manager 140 are described, for example, in U.S. Pat. No. 10,942,795 to Yanacek et al, entitled “SERVERLESS CALL DISTRIBUTION TO UTILIZE RESERVED CAPACITY WITHOUT INHIBITING SCALING” (the “'795 patent”), the entirety of which is hereby incorporated by reference.
In the instance that a worker manager 140 does not currently lease a VM instance 183 corresponding to the called task, the worker manager 140 can contact a placement service 160 to request a lease on an additional instance 183, which is illustratively configured to grant to the worker managers 140 leases to individual VM instances 183. Illustratively, the placement service 160 may maintain state information for VM instances 183 across the fleet 180, as well as information indicating which manager 140 has leased a given instance 183. When a worker manager 140 requests a lease on an additional instance 183, the placement service 160 can identify an appropriate instance 183 (e.g., warmed with software and/or data required to support a call to implement a task) and grant to the manager 140 a lease to that instance 183. In the case that such an instance 183 does not exist, the placement service 160 can instruct a worker 181 to create such an instance 183 (e.g., by creating an instance 183 or identifying an existing unused instance 183, storing an appropriate data manifest for a required executable code file, disk image, snapshot, etc. in a user space of that instance 183, and configuring a file system process to provide access to the required data set) thereafter grant to the worker manager 140 a lease to that instance 183, thus facilitating execution.
In accordance with embodiments of the present disclosure, the serverless code execution system 110 further includes a tenant service 190 configured to manage a multi-tenant mode of the serverless code execution system 110. Specifically, the tenant service 190 includes an identity and access management (IAM) data store 192, a log data store 194, and a tenant manager 196. The serverless code execution system 110, in accordance with the multi-tenant mode, may also interact with tenant resources 150. The tenant resources 150 may include tenant data store(s) 152 and API service(s) 154. In some embodiments, the tenant service 190 may be a part of the frontends 120, or may be hosted near to the frontends 120 to minimize latency to support the functions of the frontends 120.
The tenant manager 196 illustratively represents a computing device configured to manage multi-tenant mode serverless functions on the system 110. As described in more detail below, the tenant manager 196 may (1) manage access to serverless functions, and (2) manage metrics associated with use of the system 110. For instance, the tenant manager 196 may manage access to serverless functions in accordance with the IAM data store 192 and/or the metrics associated with use of the system 110. Furthermore, the tenant manager 196 may manage the metrics associated with use of the system 110 by tracking sub-tenant-specific VM instances (see, e.g., journal below), and tracking log data indicating system performance and use of the system 110 (see, e.g., log data below). Moreover, as discussed in more detail below, the tenant manager 196 may provide session tags to instantiated sub-tenant-specific VM instances. The session tags may include sub-tenant-specific session tags that correspond to the particular sub-tenant that requested a serverless function. The sub-tenant-specific session tags may include a sub-tenant identifier. The sub-tenant-specific tags may be authentication tokens. The sub-tenant-specific session tags may be used to modify execution role permissions of the sub-tenant-specific VM instances, so that outbound requests from the serverless function may be handled as-if the sub-tenant transmitted the request. The metrics may be used determine whether one or more conditions to limit call rates are satisfied based on various criteria. Depending on if one of the conditions are satisfied, the system 110 may determine to limit call rates for serverless functions. Moreover, the system 110 may use the metrics for auditing and reporting. For instance, the system 110 may generate general or specific reports (e.g., per sub-tenant, per SaaS provider, etc.) for SaaS providers.
The IAM data store 192 illustratively includes information for a set of IAM policies. The set of IAM policies may be managed by SaaS provider owners and hosted by the serverless code execution system 110, so that access (or not) to specific compute resources (e.g., storage, functions, serverless functions, etc.) is conditioned based on identity of a requesting device associated with a user (e.g., developer of a SaaS provider) or a sub-tenant. One of skill in the art would recognize that the IAM data store 192 and associated functions performed in accordance with the set of IAM policies may be hosted in a separate system other than the serverless code execution system 110. The set of IAM policies may include, for each SaaS provider or other entity using the serverless code execution system 110, a sub-set of policies to condition access (or not) to serverless functions associated with the SaaS provider or other entity. Generally, the sub-set of policies may include at least one policy to define who may modify, delete, or add new serverless functions associated with the SaaS provider or other entity. Other policies of the sub-set of policies may condition access (or not) to use the various serverless functions in accordance with an identity of a requesting device. In addition, the IAM policies may condition access (or not) based on IAM roles of users or sub-tenants.
The log data store 194 illustratively includes information for a journal and log data. As discussed in more detail below, the journal may track at least sub-tenant-specific VM instances, as the sub-tenant-specific VM instances are instantiated, in use, in a warm state (e.g., ready to be used), or decommissioned. In this way, the journal may indicate whether a sub-tenant-specific VM instance is available (or not) to handle an invocation of a serverless function for a particular sub-tenant requesting invocation of the serverless function. As discussed in more detail below, the log data may store concurrency data of VM instances for SaaS providers or other entities, and telemetry data for each request/response handled by the system 110. The concurrency data may indicate currently warm or in use sub-tenant-specific VM instances and currently warm or in use non-tenant-specific VM instances (e.g., non-multi-mode VM instances that may process non-multi-tenant serverless functions) for each of the SaaS providers or other entities. The telemetry data may indicate response time, load, pendency, sub-tenant/user requestor, etc. of each request/response of the system 110. In this way, and as discussed below, the system 110 may limit request rates on one or more conditions, such as concurrency conditions, load conditions, etc. In some embodiments, the journal may be stored and managed by the worker manager 140, as a part of managing leases. In some embodiments, the log data may be stored and managed by the frontends 120.
The tenant data store(s) 152 may be data repositories to store particular data for SaaS providers or other entities. The tenant data store(s) 152 may be any type of data store and may be hosted within the system 110 or somewhere else (e.g., within a private network associated with the system 110 or outside the private network). In some embodiments, at least some of the tenant data store(s) 152 may store data in multi-tenant architectures, such as Amazon™'s DynamoDB. In this case, those tenant data store(s) 152 may condition access to particular portions of data stored therein based on an identity of a requesting device. For instance, a tenant data store 152 may store data associated with a particular sub-tenant within a larger data structure that stores data associated with other sub-tenants, but may only allow access to the data associated with the particular sub-tenant if a device requesting the data provides a satisfactory identity indicator corresponding to the particular sub-tenant.
Similarly, the API service(s) 154 may be any service to be invoked by sub-tenants, other users, serverless functions, SaaS providers, or other entities. The API service(s) 154 may be hosted within the system 110 or somewhere else (e.g., within the private network associated with the system 110 or outside private network). In some embodiments, at least some of the API service(s) 154 may provide services in multi-tenant architectures. In this case, those API service(s) 154 may condition access to their respective services based on an identity of a requesting device. For instance, a API service 154 may only allow access to the its service if a device requesting the services provides a satisfactory identity indicator corresponding to the particular sub-tenant.
To simplify
As illustrated, the system includes a processing unit 290, a network interface 292, a computer readable medium drive 294, and an input/output device interface 296, all of which may communicate with one another by way of a communication bus. The network interface 292 may provide connectivity to one or more networks or computing systems. The processing unit 290 may thus receive information and instructions from other computing systems or services via the network 104. The processing unit 290 may also communicate to and from memory 280 and further provide output information for an optional display (not shown) via the input/output device interface 296. The input/output device interface 296 may also accept input from an optional input device (not shown).
The memory 280 may contain computer program instructions (grouped as units in some embodiments) that the processing unit 290 executes in order to implement one or more aspects of the present disclosure, along with data used to facilitate or support such execution. While shown in
The memory 280 may store an operating system 284 that provides computer program instructions for use by the processing unit 290 in the general administration and operation of the device 196. The memory 280 may further include computer program instructions and other information for implementing aspects of the present disclosure. For example, in one embodiment, the memory 280 includes an IAM manager 286 representing code executable to manage access to serverless functions, and provide session tags to instantiated sub-tenant-specific VM instances. In addition, the memory 280 includes a log manager 288 representing code executable to manage metrics associated with use of the system 110. In combination, the elements of the memory 280, when executed on the device 200, enable implementation of embodiments of the present disclosure.
The system of
With reference to
The interactions of
At (2), the frontend 120 may retrieve a configuration from the configuration data store 174. For example, the frontend 120 may retrieve the executable code file, the disk image or the snapshot corresponding to the serverless function identifier (including, possibly, a version identifier), an identifier thereof, or metadata associated therewith from the configuration data store 174. For instance, the frontend 120 may retrieve the metadata to confirm that the serverless function supports a multi-tenant mode. If it does, the frontend 120 may proceed to handle the call request in accordance with the multi-tenant mode; otherwise, the frontend 120 may determine a malformed call request and handle it accordingly (e.g., transmit an error reply and exit the invoke process), or handle the call request as if it were not a multi-tenant mode (thereby ignoring the sub-tenant identifier). The frontend 120 may retrieve the disk image or snapshot to pass the disk image or snapshot to a worker 181 (via various components) to provision a VM instance to be instantiated. Alternatively, the frontend 120 may pass the identifier of the disk image or snapshot to the worker 181 (via various components) so that the worker 181 may retrieve the executable code file, the disk image or the snapshot and provision the VM instance to be instantiated.
At (3), (4), (5), and (6), the frontend 120, the tenant manager 196, and the IAM data store 192 may cooperate to determine whether the call request is authorized to proceed. At (3), the frontend 120 may request authorization from the tenant manager 196. For example, the frontend 120 may pass the serverless function identifier and the sub-tenant identifier to the tenant manager 196. Note, the frontend 120 may also include a request to authorize the caller separate from the call request.
At (4), the tenant manager 196 may retrieve an IAM policy from the IAM data store 192. For example, the tenant manager 196 may determine a particular IAM policy associated with the serverless function identifier from among the set of policies and retrieve the particular IAM policy. For instance, the particular IAM policy may be associated with all serverless functions associated with a SaaS provider, as indicated by the serverless function identifier or the tenant identifier of the sub-tenant identifier. One of skill in the art would recognize that the particular IAM policy may be for a subset of all serverless functions associated with the SaaS provider, or the particular IAM policy may be associated with the sub-tenant identifier. In the case that the particular IAM policy is associated with the serverless function, the particular IAM policy may indicate which sub-tenants may access (or not) the serverless function. In the case that the particular IAM policy is associated with the sub-tenant identifier, the particular IAM policy may indicate which serverless functions the sub-tenant account associated with the sub-tenant identifier may access (or not).
At (5), the tenant manager 196 may determine whether the call request is authorized to proceed. For instance, in a first case, the tenant manager 196 may determine whether the call request is authorized to proceed based on the retrieved IAM policy, the serverless function identifier, and the sub-tenant identifier. For example, the tenant manager 196 may determine whether a sub-tenant identifier is authorized (or not) to access (or not) the serverless function based on the retrieved IAM policy.
In some embodiments, the tenant manager 196 may determine a context of the call request and determine whether the call request is authorized to proceed based on the context, even if the particular IAM policy indicates it may proceed. For instance, the tenant manager 196 may retrieve the concurrency data and the telemetry data (collectively, “context”) from the log data store 194 and determine whether on one or more conditions are satisfied to limit request rates. Generally, the one or more conditions may include concurrency conditions, load conditions, pendency conditions, requester conditions, response time conditions, or combinations thereof. As an example, the tenant manager 196 may determine whether a concurrency condition is satisfied if a number of concurrent VM instances (both sub-tenant-specific and non-tenant specific VM instances) associated with a SaaS provider (as indicated by the serverless function identifier or the tenant identifier of the sub-tenant identifier) exceeds a threshold. If a condition of the one or more conditions is satisfied, the tenant manager 196 may determine the call request is not authorized to proceed; if none of the one or more conditions are satisfied, the tenant manager 196 may determine the call request is authorized to proceed. In some embodiments, if the tenant manager 196 determines the call request is not authorized to proceed, the tenant manager 196 may queue the call request and authorize the call request when no conditions are satisfied, or the tenant manager 196 may reject the call request and indicate a general declination to proceed or indicate a particular issue for the declination. In the case the call requested is queued, the call request may time out after a period of time. The tenant manager 196 may queue requests in various manners, such as in first-in-first-out process, on a per sub-tenant basis, on a per tenant basis, or for the entire system 110, depending on the types of the one or more conditions that are satisfied.
At (6), the tenant manager 196 may transmit authorization for the call request to proceed. For example, the tenant manager 196 may transmit the authorization for the call request to proceed when the tenant manager 196 determines the call request is authorized to proceed based on the particular IAM policy and, optionally, the context.
In some embodiments, (2) may be contingent on the determination that the call request is authorized to proceed, that is (2) may not be performed if the call request is not authorized to proceed. In some embodiments, (3), (4), (5), and (6) may be contingent on (2) indicating the requested serverless function is indicated as a multi-tenant mode serverless function, that is (3), (4), (5), and (6) may not be performed if the requested serverless function is indicated as not to be a multi-tenant mode serverless function. In some embodiments, (3), (4), (5), and (6), and (2) may be performed in parallel, and the frontend 120 may only proceed if both the determination that the call request is authorized to proceed and requested serverless function is indicated as a multi-tenant mode serverless function.
At (7), the frontend 120 may transmit a reservation request to a worker manager 140. For example, the frontend 120 may distribute the reservation request from the frontend 120 to the worker manager 140, in a similar manner as discussed above with call requests. The reservation request may include the serverless function identifier and the sub-tenant identifier. The reservation request may include other data, such as instructions based on the context of the call request. The worker manager 140 may receive the reservation request.
At (8), the worker manager 140 may update the journal. For example, the worker manager 140 may write a new entry to the journal in the log data store 194 to indicate a new instantiation of a VM instance associated with the serverless function identifier and the sub-tenant identifier. The new entry may include other data, such as a time stamp or other contextual data.
At (9), the worker manager 140 may transmit a new sub-tenant VM request to the placement service 160. For example, the worker manager 140 may transmit the new sub-tenant VM request to the placement service 160 to contact the placement service 160 to request a lease on an additional instance 183, as discussed above. The new sub-tenant VM request may include the serverless function identifier and the sub-tenant identifier. The placement service 160 may receive the new sub-tenant VM request.
At (10), the placement service 160 may retrieve a tag from the tenant manager 196. For example, the placement service 160 may retrieve a session tag from the tenant manager 196 by providing the sub-tenant identifier to the tenant manager 196; the tenant manager 196 may determine the session tag and return the session tag to the placement service 160. In this manner, the tenant manager 196 ensures data nondisclosure by managing session tags, as the tenant manager 196 may ensure session tags are not repeated concurrently and/or correspond to an authorized entity (e.g., the sub-tenant account, based on a similar process as discussed above with respect to authorization). The tenant manager 196 may generate the session tag when the tenant manager 196 receives the authorization request (e.g., in anticipation of a subsequent contact from the placement service 160), or the tenant manager 196 may generate the session tag when the tenant manager 196 receives the sub-tenant identifier from the placement service 160. The tenant manager 196 or the placement service 160 may update the new entry in the journal with the session tag by updating the journal in the log data store 194. Alternatively, the placement service 160 may generate the session tag based on the sub-tenant identifier and notify the tenant manager 196, so that the tenant manager 196 may, e.g., track and manage session tags without slowing the instantiation process. Alternatively, the frontend 120 may pass the session tag (from the tenant manager 196) to the placement service 160, via transmitting the reservation request to the worker manager 140, who may pass the session tag via the transmitting the new sub-tenant VM request. For instance, the tenant manager 196 may provide the session tag when indicating authorization to proceed with the serverless function. In some embodiments, the IAM policy may be dynamically executed by the tenant manager 196 to provide the session tag. For instance, in response to a IAM request to retrieve the session tag (e.g., to assume the role of the sub-tenant), the tenant manager 196 may execute a dynamic policy based on a parameter (e.g., the sub-tenant identifier) of the IAM request. In this manner, the scale of the sub-tenants supported by the SaaS provider may not be limited by generation of the IAM policy or updates subsequent thereto.
At (11), the placement service 160 may instantiate a sub-tenant-specific VM instance. For example, the placement service 160 may identify an appropriate instance 183 (e.g., warmed with software and/or data required to support a call to implement a task) and grant to the manager 140 a lease to that instance 183. The placement service 160 may not select a warm instance 183 that is already assigned as a sub-tenant-specific VM instance 183, but may select a warm instance that is not assigned as a sub-tenant-specific instance 183 that has an appropriate software and/or data that can updated to execute the specific configuration for the serverless function. In the case that such an instance 183 does not exist, the placement service 160 can instruct a worker 181 to create such an instance 183, as discussed above, and grant to the worker manager 140 a lease to that instance 183. In either case, the placement service 160 may assign the identified instance 183 or the created instance 183 as a sub-tenant-specific VM instance 183 associated with the sub-tenant identifier, and pass the session tag to the sub-tenant-specific VM instance 183 to modify the temporary credentials of sub-tenant-specific VM instance with the session tag. In this manner, when the sub-tenant-specific VM instance 183 is invoked, the sub-tenant-specific VM instance 183 may assume the role of the sub-tenant when transmitting outbound requests to other services, such as the tenant resources 150.
At (12), the placement service 160 (or the worker 181) may update the journal to indicate the identity of the sub-tenant-specific VM instance 183. Therefore, the journal may be updated to identify which sub-tenant-specific VM instance 183 are currently assigned to specific sub-tenants, as the sub-tenant-specific VM instances 183 are instantiated, in use, or idle. Additionally or alternatively, the placement service 160 (or the worker 181) may notify the frontend 120 when the sub-tenant-specific VM instance 183 is ready.
With reference to
In other embodiments, the interactions of
The interactions of
At (14), the sub-tenant-specific VM instance 183 may execute code for the invoked serverless function, in accordance with the executable code file, the disk images and/or the snapshots associated with the serverless function and provided by SaaS provider. Illustratively, at (15), the sub-tenant-specific VM instance 183 may, as a part of executing the code for the invoked serverless function, retrieve sub-tenant data at sub-tenant level access from tenant data store(s) 152. For instance, the sub-tenant-specific VM instance 183 may transmit a request to a tenant data store 152, with a session tag that enables the sub-tenant-specific VM instance 183 to assume the role of the sub-tenant so that the tenant data store 152 provides access to the sub-tenant restricted data. For instance, the tenant data store 152 may check with tenant manager 196 whether an IAM policy associated with the tenant data store 152 authorizes the particular session tag to access the sub-tenant data; if so, the tenant data store 152 may provide access to the sub-tenant data; if not, the tenant data store 152 may deny access to the sub-tenant data. For instance, the code may not include the session tag (or authentication token) in the call to tenant data store(s) 152. Instead, the worker 181 that hosts the VM instance 183 may supplement calls with the session tag (or authentication token), so that the code need not worry about authentication. Alternatively, the code may refer to authentication information generically (e.g., as an environmental variable), and the worker 181 may populate the environment variable with the session tag (or authentication token) as linked to that generic identifier. In this manner, the code may work no matter the session tag (or authentication token).
At (16), the sub-tenant-specific VM instance 183 may transmit a response to the frontend 120. For instance, the sub-tenant-specific VM instance 183 may generate a response in accordance with code for the invoked serverless function and transmit the response to the frontend 120. The frontend 120 may receive the response.
At (17), the frontend 120 may relay the response to the user device 102. For instance, the frontend 120 may repackage the response, so that the response is transmitted to the return address of the user device 102. Alternatively, (16) and (17) may be omitted and the sub-tenant-specific VM instance may transmit the response directly to the user device 102. In this case, the sub-tenant-specific VM instance may notify the frontend 120 or the tenant manager 196 to notify that the response was sent to the user 102.
At (18), the frontend 120 may notify the tenant manager 196 that the response was sent. For instance, the frontend 120 may indicate the response was sent, along with optional data, such as response time, load, pendency, sub-tenant/user requestor. The tenant manager 196 may receive the notice that the response was sent.
At (19), the tenant manager 196 may generate logs and update the log data in log data store 194. For instance, the tenant manager 196 may update the telemetry data. The tenant manager 196 may also update an appropriate journal entry for the sub-tenant-specific VM instance 183, to reflect it is no longer in use.
In some embodiments, the tenant manager 196 may keep (via the workload manager 140 or other component of system 110) the sub-tenant-specific VM instance 183 in a warm state in case the sub-tenant has an additional calls to be processed. Generally, the sub-tenant-specific VM instance 183 may be kept in a warm state until a scale down policy decommissions the sub-tenant-specific VM instance 183. This may be based on various criteria, such as a period of time since a last call request for the serverless function identifier and the sub-tenant identifier, a load of the system 110, a concurrence amount of a tenant, or combinations thereof.
With reference to
The routine 400 begins at block 402, where the system 110 may determine whether a call request for a serverless function from a user device has been received. For example, the frontends 120 may wait for call requests for user devices, but generally, the call requests may be automated from other system components or other systems. Therefore, generally, the frontends 120 may wait for call requests. Generally, each call may be associated with a calling party (e.g., a sub-tenant, a service, a user device, a service, etc. that transmitted the call). In response to determining no call request for a serverless function has been received (block 402: No), the system 110 may return to wait for a call request at block 402.
At block 404, in response to determining a call request for a serverless function has been received (block 402: Yes), the system 110 may determine whether the serverless function is a multi-tenant serverless function. For example, the system 110 may retrieve metadata and determine the serverless function is a multi-tenant serverless function, as discussed above, but generally the system may determine whether the call request indicates a multi-tenant call request.
At block 406, in response to determining the serverless function is a multi-tenant serverless function (block 404: Yes), the system 110 may determine whether there is at least one warm sub-tenant-specific VM associated with a sub-tenant identifier. For example, the system 110 may determine a sub-tenant associated with the call by determining the sub-tenant based on the sub-tenant identifier, and determine whether there is at least one warm sub-tenant-specific VM associated with a sub-tenant identifier and a serverless function identifier, as discussed above. Alternatively, system 110 may automatically instantiate a sub-tenant-specific VM instance 183 for the sub-tenant identifier (e.g., proceed straight to block 414, discussed below) without considering whether there is at least one warm sub-tenant-specific VM associated with a sub-tenant identifier. For instance, in certain embodiments, the system 110 may be able to instantiate a VM for each call and quickly recycle the VM to handle a next call (without exposing sub-tenant data therebetween).
At block 408, in response to determining there is at least one warm sub-tenant-specific VM associated with a sub-tenant identifier (block 406: Yes), the system 110 may select a warm sub-tenant VM associated with the sub-tenant identifier. For example, the system 110 may select a warm sub-tenant-specific VM instance 183 from among the available warm sub-tenant-specific VM instances, in accordance with various criteria, such as age, load, etc.
At block 410, the system 110 may invoke the serverless function on the warm sub-tenant-specific VM. For example, the system 110 may pass a call, in accordance with the call request, to the selected sub-tenant-specific VM instance 183, as discussed above. Upon receiving the call, the sub-tenant-specific VM may execute the associated code (or image). Generally, the sub-tenant-specific VM may already have a session tag (e.g., a currently active session tag, as passed to it during instantiation) or the sub-tenant-specific VM may get passed a session tag (e.g., a new session tag). Therefore, the sub-tenant-specific VM may assume the role of the sub-tenant when executing the associated code, such as when interacting with tenant services 150.
At block 412, the system 110 may respond to the user device based on output of the serverless function. For example, the system 110 may execute the code of the serverless function on the selected sub-tenant-specific VM instance, generate a response, and transmit the response to the user device 102, as discussed above. Note, the response may be to any entity that transmitted the call request and not just user devices. The routine 400 may return to block 402, where the system 110 may determine whether a call request for a serverless function from a user device has been received.
At block 414, in response to determining there is no warm sub-tenant-specific VM associated with a sub-tenant identifier (block 406: No), the system 110 may instantiate a sub-tenant-specific VM instance 183 for the sub-tenant identifier. For example, the system 110 may instantiate a sub-tenant-specific VM instance that has a session tag to assume the role of the sub-tenant when executing the code associated with the serverless function, as discussed above.
At block 416, the system 110 may invoke the serverless function on instantiated sub-tenant-specific VM instance 183. For example, the system 110 may pass a call, in accordance with the call request, to the instantiated sub-tenant-specific VM instance 183, as discussed above. Upon receiving the call, the instantiated sub-tenant-specific VM may execute the associated code (or image). Generally, the instantiated sub-tenant-specific VM may assume the role of the sub-tenant when executing the associated code, such as when interacting with tenant services 150.
The routine 400 may then advance to block 412, in which the system 110 may respond to the user device based on output of the serverless function, and return to block 402, where the system 110 may determine whether a call request for a serverless function from a user device has been received.
At block 418, in response to determining the serverless function is not a multi-tenant serverless function (block 404: No), the system 110 may determine whether there is at least one warm VM. For example, the system 110 may determine whether there is at least one warm non-tenant-specific VM instance 183, as discussed above.
At block 420, in response to determining there is at least one warm VM (block 418: Yes), the system 110 may select a warm VM. For example, the system 110 may select a warm VM instance 183 from among the available warm VM instances that are not warm tenant-specific VM instances, as described above.
At block 422, the system 110 may invoke the serverless function on the warm VM. For example, the system 110 may pass a call, in accordance with the call request, to the selected warm VM instance 183, as discussed above. The routine 400 may then advance to block 412, in which the system 110 may respond to the user device based on output of the serverless function, and return to block 402, where the system 110 may determine whether a call request for a serverless function from a user device has been received.
At block 424, in response to determining there is no warm VM (block 418: No), the system 110 may instantiate a VM instance 183. For example, the system 110 may instantiate a VM instance 183 without a session tag.
At block 426, the system 110 may invoke the serverless function on instantiated VM instance 183. For example, the system 110 may pass a call, in accordance with the call request, to the instantiated VM instance 183, as discussed above. The routine 400 may then advance to block 412, in which the system 110 may respond to the user device based on output of the serverless function, and return to block 402, where the system 110 may determine whether a call request for a serverless function from a user device has been received.
Generally, the system 110 may confirm authorization to proceed with the call request before doing any of blocks 404 to 426. In this manner, the IAM policies may ensure appropriate access to sub-tenant data.
Therefore, the systems and methods of the present disclosure may utilize a shared model to build multi-tenanted applications (therefore avoiding dedicated infrastructure per sub-tenant), while minimizing the security concerns by provisioning a fresh execution environment to process requests from each sub-tenant using sub-tenant specific VM instances or containers (therefore avoiding exposing persistent data to unauthorized entities). Furthermore, multi-tenant mode of the serverless code execution system may manage credentials corresponding to a requesting sub-tenant, so that the invoked serverless function may access other tenant-level services that support multi-tenant architectures.
All of the methods and processes described above may be embodied in, and fully automated via, software code modules executed by one or more computers or processors. The code modules may be stored in any type of non-transitory computer-readable medium or other computer storage device. Some or all of the methods may alternatively be embodied in specialized computer hardware.
Conditional language such as, among others, “can,” “could,” “might” or “may,” unless specifically stated otherwise, are otherwise understood within the context as used in general to present that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment.
Disjunctive language such as the phrase “at least one of X, Y or Z,” unless specifically stated otherwise, is otherwise understood with 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.
Unless otherwise explicitly stated, articles such as ‘a’ or ‘an’ should generally be interpreted to include one or more described items. Accordingly, phrases such as “a device configured to” are intended to include one or more recited devices. Such one or more recited devices can also be collectively configured to carry out the stated recitations. For example, “a processor configured to carry out recitations A, B and C” can include a first processor configured to carry out recitation A working in conjunction with a second processor configured to carry out recitations B and C.
Any routine descriptions, elements or blocks in the flow diagrams described herein and/or depicted in the attached figures should be understood as potentially representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or elements in the routine. Alternate implementations are included within the scope of the embodiments described herein in which elements or functions may be deleted, or executed out of order from that shown or discussed, including substantially synchronously or in reverse order, depending on the functionality involved as would be understood by those skilled in the art.
It should be emphasized that many variations and modifications may be made to the above-described embodiments, the elements of which are to be understood as being among other acceptable examples. All such modifications and variations are intended to be included herein within the scope of this disclosure and protected by the following claims.
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| WO 2020005764 | Jan 2020 | WO |
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| WO 2023107649 | Jun 2023 | WO |
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| Number | Date | Country | |
|---|---|---|---|
| 20230188516 A1 | Jun 2023 | US |
