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今Serverlessが面白いわけ v19.09
Yoichi Kawasaki, Microsoft
@yokawasa
Presentation Slides for Serverless Meetup Tokyo #14
川崎 庸市 / Yoichi Kawasaki
@yokawasa
https://github.com/yokawasa
マイクロソフトコーポレーション
Azure Cloud Native Technical Specialist
インターネットサービス、エンタープライズ検索、クラウドサービス分野でのエンジニア生活を経て
現職。2017年~ Global Back Beltというグローバル組織のAPACチームに所属してクラウド開発分野で
お客様、パートナー様の技術支援、外部セミナーやイベント登壇を通じてクラウド技術の普及に従事。
NoOps Japanコミュニティ運営
What and why
Serverless?
Serverless=サーバが無い
Serverless=サーバを管理する必要がない
The UNIX Super Text 上下
技術評論社出版 (December 1, 1992)
Serverlesscomputing
Wikipedia-Serverless Computing
Serverless
AWS-https://aws.amazon.com/serverless/
Wikipedia
AWS
martinfowler.com
https://github.com/cncf/wg-serverless/tree/master/whitepapers/serverless-overview
Serverless computing refers to the concept of building and running 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
and resources 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)
1970 1980 1990 2000 2010 2020
2006 2008 2010
Amazon EC2
Google
App Engine Microsoft
Azure
Oracle Cloud
2012
Google
Compute
Engine
Alibaba Cloud
2006.8 2008.4 2010.2 2012.5
2014 2015 2016 2017 2018
AWS Lambda
2014.11
Google Cloud
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
Tech Adoption 2019 https://www.infoq.com/about-infoq
CHASM
Serverless computing refers to the concept of building and running 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
and resources 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)
内閣府 令和元年版高齢社会白書
https://www8.cao.go.jp/kourei/whitepaper/w-2019/gaiyou/pdf/1s1s.pdf
平成最後の時価総額ランキング。日本と世界その差を生んだ30年とは?
https://media.startup-db.com/research/marketcap-global
金融・製造業主導の経済から、ITを駆使した
ソフトウェア産業が世界を掌握
減り続ける労働人口
Monolith Microservices
Infrastructure
Host OS
Hypervisor
Guest
OS
Guest
OS
Bins/
Libs
Bins/
Libs
App App
Infrastructure
Host OS
Container Engine
Bins/
Libs
Bins/
Libs
App App
HTTP
HTTP
Proxy
/bin/sh
/bin/sh
/bin/sh
毎回Fork
でシェルからスクリプト実行
コストが大きい
ベンダーロックインをなくすための標準化を
進めるベンダー中立な団体
https://www.cncf.io/
マルチプラットフォーム間での標準化がもたらす
価値について疑問視する意見はあるものの
標準化は着実に進められています
• Events ( Cloud Event and it’s API & SDK 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
CNCF Serverless WGを中心に進められている
イベントスキーマ標準化のための共通仕様
• 異なるシステム間でのイベントの相互運用性(”
interoperability”)確保が目的
• イベントはさまざまなプロトコルで配送可能にする
• 業界標準(HTTP, AMQP, MQTT, SMTP, JSON)、OSS(Kafka, AVRO,
NATS)、ベンダー固有(Azure Event Grid), etc.
https://cloudevents.io/
https://github.com/cloudevents/spec/blob/master/json-format.md
サンプル: CloudEvent JSON (data部分が文字列の例)
Cloud Event Proposal https://github.com/cncf/wg-serverless/tree/master/proposals/cloudevents
CloudEvents Specs: https://github.com/cloudevents/spec
OSS Serverless Platform
OSS Serverless Framework
PublicCloud
https://www.pulumi.com/serverless/ https://github.com/pulumi/examples/blob/master/azure-ts-
functions/index.ts
• https://aws.amazon.com/jp/blogs/news/firecracker-
lightweight-virtualization-for-serverless-computing/
• https://github.com/firecracker-
microvm/firecracker/blob/master/docs/design.md
https://quarkus.io/
• https://developers.redhat.com/blog/2019/03/07/quarkus-next-
generation-kubernetes-native-java-framework/
• https://publickey1.jp/blog/19/javaquarkusjavajavared_hat.html
Kubernetes-based Serverless
• Knative
• KEDA
• Virtual Kubelet
https://github.com/knative
インフラストラクチャの抽象化
ネットワークの抽象化
アプリライフサイクルの抽象化
インフラストラクチャ
の抽象化
ネットワーク
の抽象化
アプリライフサイクル
の抽象化
• コードのビルド
• パッケージング
• リクエスト受信
• ルーティング
• スケール
• イベントソースの
抽象化
• コードの発火
https://knative.dev/docs/serving/ https://knative.dev/docs/eventing/
https://knative.dev/docs/build/
https://github.com/kedacore/keda
• KubernetesのHPA (Horizontal Pod
Autoscaler)は全PodのCPUやメモリ消費率
でスケールを調整するのが基本動作
• KEDAはRabbit MQ 、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
kubelet
kube proxy
Container
Container
runtime
Virtual Kubelet
• Alibaba Cloud ECI Provider
• Azure Container Instances Provider
• Azure Batch GPU Provider
• AWS Fargate Provider
• HashiCorp Nomad
• OpenStack Zun
https://github.com/virtual-kubelet/virtual-kubelet
https://aka.ms/AA630ny
本日の資料と過去の登壇資料
Microsoft Learn (無料学習サイト) はこちら
ご静聴いただき
ありがとうございました
Y
A
X B

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今Serverlessが面白いわけ v19.09

Editor's Notes

  1. ku
  2. https://en.wikipedia.org/wiki/Cloud_computing https://en.wikipedia.org/wiki/Alibaba_Cloud
  3. Azure Functions 実行ランタイムはGitHubにてオープンソース化 https://www.cncf.io/blog/2018/02/14/cncf-takes-first-step-towards-serverless-computing/
  4. ハイテク分野の新しい製品やサービスがローンチ後、成長期に差し掛かる直前に立ちはだかる深い溝を「キャズム」と呼んでいる
  5. もはや実数の勝負ではなく、どれだけソフトウェアでレバレッジを効かせた勝負ができるか
  6. 仮想化、自動化、抽象化、業界のうねりが向かう先はNoOpsとも言える では他に何がくるのかといえば
  7. AWS API Gateway + Lambda and Auth0 webtask を状況によって切り替えるできたらいいよね?
  8. Pulumni - SDK Terraform – HashiCorp Configuration Language (HCL) CloudFormationのIaCソリューションでserverless アプリを定義して、DevOpsをシンプルにしてくれる. https://www.publickey1.jp/blog/19/pulumi10javascriptpythongo.html Plumni version1.0到達。 そのTerraformもクラウドサービスとして本格的な展開が始まった。今後はInfrastructure as Codeツールもクラウドサービスとして利用することが一般的になっていくでしょう
  9. 2018, 11 AWS event
  10. GraalVMを使用してNativeビルドをすることでJVMが不要になり起動が高速化 Helidon Micronaut(まいくろのーと) 他にも参考にしたい http://koduki.hatenablog.com/entry/2019/04/15/063038
  11. Multi-Cloud / Cross Cloud ベンダロックイン、特定クラウドプロバイダのアーキテクチャなどの恐れがある 今後はロックインを避け、マルチクラウドでいけるようになthe unification of FaaS APIs or frameworks such as IronFunctionsの動きがでるでしょう マルチクラウドの話に戻すと、恐らくデータの集積の基本となるクラウドと、それを元に部分的に複数のクラウドを使っていくという形が増えていくのではないでしょうか。今だとデータをS3に集めて、AI部分のみ別のクラウド使って、またADだけAzure使ってという所は結構あるかもしれません。基本となるクラウドが1つあれば、後は良いとこ取りできるよというのがマルチクラウドだと思います。 ベンダーロックインの恐れと、Cloud Agnostic solutionの現れ + ハイブリッドモデルServerless container orchestration one design, any cloudの話: WalmartLabs' OneOps, for example, bills itself as "one design, any cloud." OneOps is a comprehensive solution, but it requires some commitment to its architecture to take full advantage.
  12. Cloud Runは Knative から作成されている Cloud Run を使用してフルマネージド型でコンテナを実行するか、Cloud Run with GKE を使用して Google Kubernetes Engine クラスタ内でコンテナを実行するかを選択できる https://thenewstack.io/how-google-cloud-run-combines-serverless-with-containers/