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Serverless Architecture Patterns - Manoj Ganapathi - Serverless Summit

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-- Presented in Serverless Summit 2017 - www.inserverless.com --
The earlier sessions at this conference covered development scenarios & operations, frameworks/platforms, and technology applications. In this session, I'll tie them together to provide a perspective on architectures and patterns for serverless. I'll cover how serverless compute can be used as glue or backend, legacy API proxy, or do real-time processing. Further, I'll discuss how serverless can be employed for web applications, batch processing, stream processing and event-driven automation, at a high level.

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Serverless Architecture Patterns - Manoj Ganapathi - Serverless Summit

  1. 1. CodeOps Technologies Serverless Architecture Patterns Manoj Ganapathi Chief Architect, CodeOps manoj@codeops.tech @manojgr
  2. 2. Serverless: Core Principles ❖ Functions are the unit of deployment and scale ❖ Use Serverless to solve specific problems, not every application can be written as Serverless. ❖ Keep your functions Stateless – use cloud storage for WIP state ❖ Functions should: ❖ “Do One Thing”– Single Responsibility Principle ❖ Be Idempotent ❖ Finish as fast as possible “Rethink your application as an orchestra of autonomous functions”
  3. 3. Architectures •Compute as a Backend •Real-time Processing •Compute as a glue •Hybrid •Proxy Use Cases •App Backend •Data Pipelines •Bots and Skills •Legacy API Proxy •Scheduled/Event Driven services •Stream Processing Patterns •Messaging •Command •Pipes and Filter •Fan Out •Priority Queue Reference: Serverless Architectures on AWS
  4. 4. Key Patterns
  5. 5. Messaging and Command • Decouple services by introducing a queue • Typically in asynchronous messaging in web apps and services to take the load off the application • Also shows the Command pattern (encapsulated implementation for a standard interface) Reference: Serverless Architectures on AWS
  6. 6. Fan Out • Topic-Subscription scenario. • For e.g: Once a video is uploaded, you may want to encode them in multiple formats in parallel and also transcribe Reference: Serverless Architectures on AWS
  7. 7. Pipes and Filter • To manage a sequential series of tasks – like a data pipeline • Functions can work as a pipe (connector) or a filter (transformation) Reference: Serverless Architectures on AWS
  8. 8. Appendix AWS Lambda and Azure Functions examples
  9. 9. AWS: Web Applications https://www.slideshare.net/AmazonWebServices/aws-reinvent-2016-serverless- architectural-patterns-and-best-practices-arc402
  10. 10. AWS: Batch Processing https://www.slideshare.net/AmazonWebServices/aws-reinvent-2016-serverless- architectural-patterns-and-best-practices-arc402
  11. 11. AWS: Stream Processing https://www.slideshare.net/AmazonWebServices/aws-reinvent-2016-serverless- architectural-patterns-and-best-practices-arc402
  12. 12. Azure Functions: Stream Processing https://www.slideshare.net/satonaoki/serverless-patterns-with-azure-functions
  13. 13. Azure Functions: Managing Dialog responses in Chatbots https://www.slideshare.net/satonaoki/serverless-patterns-with-azure-functions
  14. 14. Azure Functions: Integration and Web API https://www.slideshare.net/ServerlessConf/chris-anderson-and-yochay- kiriaty-serverless-patterns-with-azure-functions
  15. 15. AWS: Event Driven Automation https://www.slideshare.net/AmazonWebServices/aws-reinvent-2016-serverless- architectural-patterns-and-best-practices-arc402
  16. 16. Azure Functions: Service Event Processing https://www.slideshare.net/satonaoki/serverless-patterns-with-azure-functions

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