Real World Enterprise Reactive Programming using Vert.x
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The document provides an overview of using Vert.x for developing and deploying asynchronous applications within enterprise environments, with a focus on best practices and architecture. It includes practical guidance on starting with Vert.x, deployment strategies, module integration, and performance metrics, specifically in the context of using Kafka and Redis. Additionally, it outlines the benefits of a reactive programming model and efficient handling of messaging systems.
Real World Enterprise Reactive Programming using Vert.x
- 1. Mariam Hakobyan, Sascha Möllering, | zanox AG Björn Stahl Real World Enterprise Reactive Programming using Vert.x
- 2. TABLE OF CONTENTS 1.Introduction 2.The Beginning 3.How to start? 4.Best Practices 5.Architecture 6.Deployment 7.Vert.x module system 8.Integration with messaging system
- 3. INTRODUCTION ZANOX Europe‘s leading performance advertising network
- 4. THE BEGINNING Java Magazin 04.14: Vert.x im Unternehmenseinsatz Entwicklung und Betrieb von asynchronen Applikationen mit Vert.x in der Praxis
- 5. THE BEGINNING ● New core system for zanox ● Requirements are pretty high (not negotiable): ● Low latency ● High throughput ● Reactive ● Fast
- 7. WHAT IS VERT.X? Vert.x “Vert.x is a lightweight, high performance application platform for the JVM that's designed for modern mobile, web, and enterprise applications.”
- 8. WHAT IS VERT.X? Polyglot
- 9. WHAT IS A VERTICLE? ● Classes with an own Classloader ● operates Single Threaded ● executed by an Event Loop
- 10. V V V W W W Event Loop Pool Event Bus TAKE A LOOK INSIDE
- 11. HOW TO START? ● mvn archetype:generate - Dfilter=io.vertx: (do not forget the colon!) ● generates structure for all languages (JS, Ruby, Groovy, Python) ● maven pom is already set with relevant data
- 12. HOW TO START?
- 13. Lessons learned - Profiling ● Verticles and WorkerVerticles appear in different subtrees ● Be careful with blaming, a lot of stuff is just waiting ● If you think a verticle is a bottleneck: start more instances of this verticle ● Measure every change & compare results (yeah yeah - but really - do it!)
- 14. BEST PRACTICES Starter Verticle
- 16. BEST PRACTICES Logger Verticle ● Disadvantages: ● log entries are not in order ● loss of log levels ● Solutions: ●use IDs to follow log message flow ●use one LoggerVerticle per log level
- 17. BEST PRACTICES - On the fly deployment
- 18. BEST PRACTICES - On the fly deployment
- 19. BEST PRACTICES In General ● Do not block the loop ● put blocking code or extensive computation into worker verticles ● Keep the application responsive ● stress test as often as possible ● Encapsulate common code in modules (more on this later)
- 20. BEST PRACTICES Deployment fat-jar: one package to rule the deployment
- 21. BEST PRACTICES Deployment zip-File: ● have a separate folder for scripts ● bind packaging to verify phase to have it all with one command “mvn verify” ● complete example is on GitHub
- 22. Internet Availability Zone Auto Scaling group Auto Scaling group Availability Zone
- 23. Architecture
- 24. Architecture ● Main framework Vert.x ● mod-kinesis (Kinesis-Adapter for Vert.x) ● AWS Java SDK ● IAM roles for Amazon EC2 instances ● Coda Hale metrics and CloudWatch reporter ● Jedis (Redis client for Java) ● …
- 25. Deployment Workstation GitHub Jenkins Nexus Python/Fabric Datacenter Artefakt
- 26. Deployment
- 27. Deployment EC2 instance with Docker registry (port 5000) S3 bucket to store Docker images
- 28. Deployment Amazon Cloud Workstation GitHub Jenkins Python/Boto Docker Image Docker Registry S3 bucket with Docker Images
- 29. Deployment
- 30. Deployment
- 31. Deployment
- 32. Deployment python start_docker_instance.py -r <myregistry>:5000 -i kinesis-producer -t 95 -q 2 -s quality -d '-d -p 8080:8080' https://github.com/SaschaMoellering/aws-docker-scripts
- 33. Deployment python start_elb.py -r <myregistry>:5000 -i kinesis-producer -t 95 -s quality -d '-d -p 8080:8080' https://github.com/SaschaMoellering/aws-docker-scripts
- 34. Deployment
- 35. Deployment
- 37. Vert.x Module System Benefits: ● Re-usable components as a zip file ● Maven and Bintray integration ● Vert.x module registry ● Vert.x downloads and installs modules for you
- 39. Vert.x Event Bus ● Address is a simple string ● Types - Pub/Sub & P2P Pub/Sub P2P
- 40. Sender Receiver
- 41. Integration with Messaging System KAFKA MESSAGING SYSTEM ● Apache Kafka is a distributed publish-subscribe messaging system ● Fast ● Scalable ● Durable ● Distributed
- 42. Integration with Messaging System Main Terminology: ● Topic ● Producer ● Consumer ● Broker
- 43. Kafka Module in Module Registry Open source Kafka module in Vert.x’ module registry ● http://modulereg.vertx.io/
- 44. Using Vert.x Module // programmatically // command line
- 45. Using Kafka Module Configuration is a JSON object:
- 47. Metrics of Vert.x Project On 4 Cores virtual machine we had the following results: ●~28 K requests per second without Kafka, with lookup from Redis ●~18 K requests per second with Kafka and lookup from Redis
- 48. Metrics of Vert.x Project Test Traffic ~1000-3000 requests per minute: ● mean response time: 1-2ms ● 90% of responses 0.86 ms ●fully cached: 0.65 ms ● CPU Load: 1-3% ● Memory: 90MB (300MB reserved)
- 49. GET INVOLVED Kafka Module - https://github.com/zanox/mod-kafka Kinesis Module - https://github.com/zanox/mod-kinesis