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Introduction to Akka Serverless

We have been talking about Serverless a lot lately and there are a couple of reasons for that. Serverless computing will provide greater scalability, more flexibility, and quicker time to release at reduced cost and this is the reason everybody is after it. Is serverless architecture enough to drive all this we talked about just now? The answer is no, of course. Also, State management has been absolutely challenging in serverless computing but Cloudstate will make it possible for us, wondering how? Keep reading the article until and you will learn it. The Lightbend’s Cloudstate which was released in August last year(2019) has proved to be a game-changer here as it provides stateful serverless computing, Cloudstate brings powerful new distributed and durable state management primitives based on Akka to the Serverless paradigm. Serving of stateful functions powered by Akka Cluster. That was all for the introduction, let’s talk about Cloudstate in detail below.

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Introduction to Akka Serverless

  1. 1. Presented By: Himanshu Gupta Anjali Sharma Knoldus Inc Cloudstate Distributed State Management for Serverless
  2. 2. Lack of etiquette and manners is a huge turn off. KnolX Etiquettes Punctuality Respect Knolx session timings, you are requested not to join sessions after a 5 minutes threshold post the session start time. Feedback Make sure to submit a constructive feedback for all sessions as it is very helpful for the presenter. Silent Mode Keep your screens on mute unless you have query. Avoid Disturbance Avoid unwanted chit chat during the session.
  3. 3. Agenda 01 What is Serverless Computing 02 Limitations of Serverless Platforms 03 Rethinking CRUD 04 About Cloudstate and its architecture 05 Working with Cloudstate
  4. 4. What is Serverless Computing ?
  5. 5. ● Serverless computing is a method of providing backend services on an as-used basis ● Serverless means that the developers can do their work without having to worry about servers at all. What is Serverless Computing ?
  6. 6. Simplified Scalability Low Latency Easily Deployable Cost Effective No Server Management Required Benefits of Serverless Computing
  7. 7. Stateless Latency No addressability Limitations of Serverless Platforms
  8. 8. Stateless ● Aside from the components that are explicitly designed to be data stores, most Serverless components are effectively stateless ● Forces to load and store the state from the backend storage over and over again. ● Stateless components must, by definition, interact with other, stateful components to persist any information beyond their immediate lifespan. Limitations of Serverless Platforms
  9. 9. Latency ● Serverless faces two kinds of latency challenges: cold-starts and high tail latencies ● When the first user request arrives, the serverless platform needs to load the function. ● Cold-starts are avoided by keeping one copy running, by forecasting when the first call happens, or by improving the startup time of the code. Limitations of Serverless Platforms
  10. 10. No Addressability ● Quite often, functions simply have no direct addressability ● They can’t communicate directly with each other using point-to-point communication. ● This forces developers to resort to publish-subscribe, passing all data over some slow and expensive storage medium. Limitations of Serverless Platforms
  11. 11. ● We need to rethink the use of CRUD in Serverless. ● CRUD, in the general sense, means unconstrained database access, and is too broad and open-ended to be used effectively in Serverless environments ● You are thereby moving all the operational concerns from the Serverless framework into the user function Rethinking CRUD
  12. 12. ● Is the operation a read, or a write? ● Can it be cached? ● Can consistency be relaxed, or is strong consistency needed? ● Can operations proceed during partial failure? Rethinking CRUD
  13. 13. Abstracting over State ● When we try to use the existing CRUD strategy then maintaining the state becomes difficult. ● Unconstrained CRUD does not work in this model since we can’t pass the entire data set in and out of the function. Solution? Restricted I/O Patterns Rethinking CRUD
  14. 14. Event Sourcing In Event Sourcing, state in is the event log while state out is any newly persisted events as a result of handling a command. Restricted I/O Patterns
  15. 15. CRDTs In CRDTs, state in is a stream of deltas and/or state updates, and state out is a stream of deltas and/or state updates. Restricted I/O Patterns
  16. 16. Key-Value This is the least complex and most used pattern. As in it, the Key is the State Out and the Value is the State In. VALUE KEY Restricted I/O Patterns
  17. 17. Cloudstate is a specification, protocol, and reference implementation for providing distributed state management patterns suitable for Serverless computing. – cloudstate.io About Cloudstate and its Architecture
  18. 18. ● In simple terms, Cloudstate is a framework that helps in building Distributed Stateful Serverless Applications. ● It supports a variety of serverless patterns, like: ○ Event Sourcing ○ Conflict-Free Replicated Data Types (CRDTs) ○ Key-Value storage ○ P2P messaging, and ○ CQRS read side projections ● It is polyglot, which means that services can be written in any language that supports gRPC, like (Dart, Go, Java, Javascript, Kotlin, Python, Sprint Boot, .Net). What is Cloudstate?
  19. 19. ● Cloudstate is built on top of K8, Knative, Graal VM, gRPC, and Akka. ● A gRPC channel is used for both – Inbound & Outbound communication which goes through sidecars. ● Also, a single gRPC channel is used per service/entity which allows the infrastructure to safely cache the entity state in memory. Bird’s Eye View of its Architecture
  20. 20. ● The Knative Stateful Serving is an Akka Cluster under the hood. ● It provides durable Akka Actors which in turn supports several data models, storage techniques, and DBs. ● This shields the User from the complexities of the Akka Cluster via a set of sidecars which bridges the user code to the backend state & cluster management. What is present Under the Hood?
  21. 21. The first step we need to take is, decide the programming language of our choice. Cloudstate have connectors for a wide range of programming languages. Like: 1. Dart 2. Go 3. Java 4. Kotlin 5. Javascript Choose Your Language Wisely
  22. 22. ● The next step of working with Cloudstate is to focus on the business logic. ● Yes, you read it correctly. You don’t have to take care of the nitty-gritty details anymore. ● You just need to provide a Kubernetes environment and run your Cloudstate services on it. Focus on Business Logic
  23. 23. ● Ingress: Cloudstate expects traffic to be distributed evenly across its pods. Hence any service approach, like Istio, Knative, or just regular ClusterIP service communication in K8 can be used. ● Akka Sidecar: It is injected by the Cloudstate operator. All requests go through it. ● f(x): This represents the function implemented by the user. ● Distributed DB: This is the place where state is persisted in form events. Cloudstate Service Structure
  24. 24. References 01 Lightbend Series from Knoldus Inc. 02 Cloudstate official documentation
  25. 25. Thank You ! For further queries reach out to us at: himanshu@knoldus.com anjali.sharma@knoldus.com

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