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Building Cloud Native Applications
This document discusses building cloud native applications. It defines cloud native applications as having services that are published and consumed via web services, can handle failures, are designed for horizontal scalability, use asynchronous processing, and have a stateless model. It then provides an example of a social feed application, outlines its functional and non-functional requirements, and describes how to architect it using patterns like loose coupling, polyglot persistence, fault tolerance, and decoupling services. The key is to design for scalability, failures, and minimize human intervention through a DevOps approach.
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Building Cloud Native Applications
- 1. Building Cloud Native Applications By Munish K Gupta - @write2munish 1
- 2. Munish K Gupta • Current Avatar • Software Architect/Engineer –High Performance Architecture (HiPA) group @ Wipro Technologies • Author – Akka Essentials (Oct 2012) • Work with lot of open source stuff – Play Framework, Akka, Scala, mongodb, redis, LA MP stack • My Blogs • http://www.techspot.co.in • http://www.akkaessentails.in 2
- 3. What is CloudNative Application? 3
- 4. Cloud Native Application • All functionality is published and consumed via web Services services • Every Integration point will eventually fail one time Handling or another Failures • Be prepared to handle all kind of failures Horizontal • Design for Scale Out Scalability • Break down the task, process requests Asynchronous asynchronously Processing • Use queues to decouple functionality • Eventual consistency model • Build stateless services that can be scaled out and Stateless Model load balanced Minimize Human • Go DevOps/NoOps Intervention 4
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- 7. Functional & NonfunctionalRequirements • Functional Requirements • User registrations + Social Sites OAuth (FB, Twitter) • Allows users to insert/import RSS feeds • Feed data need to be categorized , auto tagged and searchable • Feed data can be bookmarked and shared across social channels • Feed recommendations based on social graph data • Feeds displayed to the user via series of templates (list, mosaic, magazine style) • Supports mobile view of data • Site Analytics • Nonfunctional Requirements • Supports 10,000 concurrent users • Supports initial user base of 500,000 users • Feed volumes of about 500 feeds/sec • Availability requirements (99.9% uptime) • Hosted on cloud and resilient to availability zone failures • CPU utilization should be minimum of 70% and application should be cost optimized for cloud resources 7
- 8. Functional Decomposition User Registration + •User registrations + Social Sites OAuth (FB, Twitter) Session Management •Allows users to insert/import RSS feeds User Data Feed Fetch, Search, •Feed data need to be categorized , auto tagged and searchable Content Tagging •Feed data can be bookmarked and shared across social channels User Preferences •Feed recommendations based on social graph data Recommendation •Site Analytics Engine •Feeds displayed to the user via series of templates (list, mosaic, magazine style) Responsive Web Design •Supports mobile view of data 8
- 9. Functional Model Responsive Web Design User Session User Search Registration Management Preferences Content Recommendati Feed Fetch Tagging on Engine 9
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- 11. 11 User Registration User Preferences Search Partition by Functionality Content Tagging Session Management Responsive Web Design Feed Fetch Recommendation Engine
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- 13. Polyglot Persistence Redis Neo4j MySQL MySQL Apache Mongodb Mongodb MapReduce Lucene 13
- 14. Fault Tolerance +Service Load Balancing Load Balancing between multiple Service provider instances Handling service provider instance failures 14
- 15. Fault Tolerance +Service Load Balancing Netflix Eureka Open Source Project Picture from https://github.com/Netflix/eureka https://github.com/Netflix/eureka/wiki/Eureka-at-a-glance 15
- 16. Decoupling Communication across Web Services functional columns using model can also messages - SQS be used here! Recommendation Content Data User Data Engine Search Mongo MySQL Lucene Neo4j db 16
- 17. Async Request processing LESS - Responsive Web Design Node.js for stateless and async request processing mode 17
- 18. Deployment Model Distributed Scalable Available Stateless ASync Event processing driven Fault Tolerant 18
- 19. Summary • Design to decouple and partition application functionality • Right tools to solve the right problem • Build for horizontal scalability – scale out • Design to handle all kinds of failures • Process asynchronously – event driven • Build stateless compute services • Minimize human intervention - DevOps/NoOps • Above all, do not forget continuous build and deployment Learned we may be with another man's learning: we can only be wise with wisdom of our own Michel de Montaigne 19
- 20. Munish K Gupta write2munish (at) gmail.com Twitter @write2munish Blog(s) www.techspot.co.in www.akkaessentials.in 20
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