applications that do not require server management. It describes a finer-grained deployment model where applications, bundled as one or more functions, are uploaded to a platform and then executed, scaled, and billed in response to the exact demand needed at the moment. Serverless computing does not mean that we no longer use servers to host and run code; nor does it mean that operations engineers are no longer required. Rather, it refers to the idea that consumers of serverless computing no longer need to spend time andresources on server provisioning, maintenance, updates, scaling, and capacity planning. Instead, all of these tasks and capabilities are handled by a serverless platform and are completely abstracted away from the developers and IT/operations teams. As a result, developers focus on writing their applications’ business logic. Operations engineers are able to elevate their focus to more business critical tasks. A serverless computing platform may provide one or both of the following: 1. Functions-as-a-Service (FaaS), which typically provides event-driven computing. Developers run and manage application code with functions that are triggered by events or HTTP requests. Developers deploy small units of code to the FaaS, which are executed as needed as discrete actions, scaling without the need to manage servers or any other underlying infrastructure. 2. Backend-as-a-Service (BaaS), which are third-party API-based services that replace core subsets of functionality in an application. Because those APIs are provided as a service that auto-scales and operates transparently, this appears to the developer to be serverless. https://github.com/cncf/wg-serverless/tree/master/whitepapers/serverless-overview スケーリングされ、使った分だけ課金 • Functions-as-a-Service (FaaS) • Backend-as-a-Service (BaaS)
Functions Azure Functions 2016.2 2016.3 IBM Cloud Functions Serverless Framework 2015.10 2016.12 OpenWhisk (OSS) by IBM Fn Project (OSS) by Oracle 2017.10 Serverless Whitepaper by CNCF 2018.2 2019 2018.12 Oracle Function 2018.7 Knative by Google
applications that do not require server management. It describes a finer-grained deployment model where applications, bundled as one or more functions, are uploaded to a platform and then executed, scaled, and billed in response to the exact demand needed at the moment. Serverless computing does not mean that we no longer use servers to host and run code; nor does it mean that operations engineers are no longer required. Rather, it refers to the idea that consumers of serverless computing no longer need to spend time andresources on server provisioning, maintenance, updates, scaling, and capacity planning. Instead, all of these tasks and capabilities are handled by a serverless platform and are completely abstracted away from the developers and IT/operations teams. As a result, developers focus on writing their applications’ business logic. Operations engineers are able to elevate their focus to more business critical tasks. A serverless computing platform may provide one or both of the following: 1. Functions-as-a-Service (FaaS), which typically provides event-driven computing. Developers run and manage application code with functions that are triggered by events or HTTP requests. Developers deploy small units of code to the FaaS, which are executed as needed as discrete actions, scaling without the need to manage servers or any other underlying infrastructure. 2. Backend-as-a-Service (BaaS), which are third-party API-based services that replace core subsets of functionality in an application. Because those APIs are provided as a service that auto-scales and operates transparently, this appears to the developer to be serverless. https://github.com/cncf/wg-serverless/tree/master/whitepapers/serverless-overview 開発者や運用者が本質的な ビジネスロジックの開発や、クリティカルタスクに集中できる サーバ管理が不要 需要に応じてスケーリングされ、使った分だけ課金 • Functions-as-a-Service (FaaS) • Backend-as-a-Service (BaaS)
for CE ) • Workflows / Function Composition • Event Orchestration / Chaining • Function Signatures • Common function logging, observing, and monitoring • Common function model • Common function Benchmark framework CNCF Serverless WG / Proposals https://github.com/cncf/wg-serverless/tree/master/proposals
、Kafka Streaming、 Azure Storage Queue、Azure Service Bus Queueなど非HTTPなイベントに連動した Podのスケール調整ができるのが特徴 • KEDAがZeroスケールイン・アウトして、 それ以外はHPAがスケールイン・アウト Storage Queue ServiceBus Queue Kafka RabbitMQ HPA KEDA 1->N or N->1 0->1 or 1->0 … K E D A
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