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The Story So Far with Ratpack: High Performance Java Web Framework
- 1. Ratpack The story so far Phill Barber - Team Thor - Team Cirrus - Energized Work
- 2. Agenda ● What is Ratpack? ● Why did we decide to use it? ● A look at the code. ● Mistakes you can make. ● Issues we currently face. ● Retrospective.
- 4. What is ratpack? ● A high performance Java web framework. ● Asynchronous and non-blocking model. ● Aims to make asynchronous programming on the JVM easier. ● Built on Java 8 and Netty. ● Currently at version 1.1.1
- 5. What is ratpack? (continued) Assuming your application is I/O bound, it offers the following benefits: ● High throughput ● Low CPU usage ● Lower Memory usage (due to less threads) All of these benefits are due to its threading model and using non blocking I/O
- 6. Synchronous - Blocking I/O
- 7. Asynchronous - Non Blocking I/O
- 8. What is ratpack? (continued) This efficiency comes with the cost of increased complexity. ● Steep learning curve. ● Easy to get wrong. ● Hard to debug.
- 9. Ratpack misconceptions ● Asynchronicity is internal only! ○ It’s just a web server. ○ It takes time to respond to http requests. ● Doesn’t improve latency. ○ If a downstream call takes 500ms, ratpack will take > 500ms to respond. ● If you are using Ratpack - it doesn’t mean your system will necessarily perform any better. ○ You can make it perform worse!
- 10. Why did we decide to use it?
- 13. Ratpack vs Dropwizard - Load profiles Three load profiles were given to each application as detailed below: 1. 5 minute duration, 100 JMeter Threads 2. 5 minute duration, 200 JMeter Threads 3. 5 minute duration, 300 JMeter Threads
- 18. Why did we decide to use it? ● We will be I/O bound. ● We will be at high load. ● Ratpack vs Dropwizard Performance Test revealed encouraging stats. ● We had a sense of optimism that we’d pick up the async challenges.
- 19. A look at the code
- 20. A look at the code - Overview ● Runnable Jar. ● main() method starts the server. ○ Simple and easy to start for testing. ● URIs mapped to Handlers. ● Execution model deals with Promises. ● We decided to use Rx Java in “service” layer and use Observables.
- 21. A look at the code ● Happy path example.
- 22. A look at the code ● Happy path example. ● High throughput example.
- 23. A look at the code ● Happy path example. ● High throughput example. ● Deterministic demonstration.
- 24. Mistakes you can make ...BIG BIG mistakes!
- 25. Mistakes - Two Types 1. Dangerous mistakes. 2. Annoying mistakes.
- 26. Dangerous mistakes ● Calling a blocking method. ○ So many ways to do this. IMPACT: ?
- 27. Dangerous mistakes ● Making new Threads IMPACT: Memory & CPU increase -> Ultimately low throughput
- 28. Annoying mistakes ● Not understanding execution model. ○ Not using Promises when you should.
- 29. Annoying mistakes ● Messing up Threads ○ Using Cassandra thread to call Cassandra. ○ Happened to us whilst implementing ListenableFuture
- 30. Issues we currently face
- 31. Issues (continued) ● Ratpack http client does not use a connection pool. ● AppDynamics integration still ongoing.
- 32. Issues Performance related issue: At load, 1 in 1000 requests would not get a response. ● Hard to debug ● Thread dumps revealed that (big surprise) nothing was blocking. Where do you go from here? Now Resolved ● Was actually an issue related to secretly running in Development mode. InteliJ IDEA ○ Issue #909
- 33. Retrospective
- 34. Retro / Assorted notes... ● It was harder than we expected. ● It took longer than expected to get up to speed. ● Rx bought us flexibility but introduced an extra learning curve. ● Cost vs Reward analysis is difficult but would have been a benefit. ● Monitoring our CPU and Memory usage is key to realising the benefit. ● Confidence is improving day by day… BUT… ● Still not proven - We’re not live yet!
- 35. Thanks! Questions? More info: http://phillbarber.blogspot.co.uk/ Code: https://github.com/phillbarber/ratpack-demo