Node.js in Production
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The document discusses best practices for using Node.js in production, focusing on insights from a team at Curiosity Media responsible for the SpanishDict website. It outlines five key tips: understanding when to use Node.js, keeping software up to date, designing for failure, isolating services, and analyzing performance metrics. Additionally, it emphasizes the importance of monitoring and optimizing various system resources to ensure effective Node.js application management.
Node.js in Production
- 1. Node.js in Production - | Seattle Node.js May 8th, 2013 Ryan Roemer @ryan_roemer
- 2. Overview Production! Well, what our production looks like. Five Node.js-related things we've learned. Some additional resources.
- 5. Brought to you by... A team of three engineers Who are full-time developers Running everything in the cloud With minimal time available for ops
- 7. Demo
- 8. A Spanish-English Dictionary is the world’s largest Spanish-English dictionary, translation, and language learning website. We develop and provide reliable, accurate, easy-to-use resources for learning Spanish. SpanishDict.com
- 9. Our visitors A into our data and usage: 6,000,000 Unique visitors every month 1,000,000 Translations 100,000 Questions and answers 25,000 Flashcards 5,000 Video pronunciations 90 Lessons quick glance
- 10. Our Services Node Other API server Web site Auto-suggest server Data mining Translation server Operations Text-to-speech server
- 11. Our Traffic Very low latency for our db-backed services. Service Reqs/min API server 35K / min Auto-suggest server 15K / min Translation server 2.5K / min Text-to-speech server 400 / min
- 12. Five Node.js production tips 1. Know when to Node 2. Keep up with Node 3. Design for failure 4. Isolate services 5. Analyze everything
- 13. 1. Know when to Node Should you use Node.js?
- 14. Yes Small apps (think JSON APIs) "Glue" for services or data Proxies Concurrent data Use the module Lots of connections stream
- 15. Maybe not Computation Legacy applications "Solved" problems (fuzzy search, NLP, etc.)
- 16. 2. Keep up with Node Bleeding edge, lots of breakage. Stay up to date with Node.js and libraries.
- 17. Infrastructure
- 18. Node.js deployments PAAS: Often, the easier way. , , , etc. IAAS: Expect some DIY Build custom Node.js versions Install modules from scratch Get ready to roll back Joyent Heroku Nodejitsu
- 19. 3. Design for failure Fail and recover at multiple levels.
- 20. App-level Errors Handle: uncaughtException Listen: foo.on("error") Use the module Workers: die early on errors Master: monitor and kill workers cluster
- 21. Server-level Use or alternatives Restart the Node.js master monit
- 22. Service-level Have lots of small apps Stateless, fungible servers Hot failover wherever possible
- 23. 4. Isolate services Separate resource and failure classes.
- 24. Resources CPU/Load: Run out of this and it's over. Also, memory, I/O, etc. ... and combinations thereof
- 25. Our pains Node.js apps aren't necessarily good neighbors. Suggest (DB) and translate (http) Backend (DB) and web site (CPU/load, memory) Read and write servers
- 26. Takeaways Always preserve CPU Monitor system stats for cross-pressure
- 27. 5. Analyze everything How well are we addressing lessons 1-4? Data drives problem discovery and action.
- 29. Things to look for Some metrics that affect Node.js apps Type Metrics Uses System CPU, I/O, memory, network Alert Server Throughput, latency Alert, Report Traffic Peaks (weeks, months) Report Errors Quantitative, qualitative Alert, Report
- 30. Decisions, Goals Identify Resource pressure Bugs Decide Scale up, scale down? Separate?
- 31. Demo
- 32. Recap 1. Know when to Node 2. Keep up with Node 3. Design for failure 4. Isolate services 5. Analyze everything
- 33. Further Reading by by by Production Node.js Secrets @dshaw Node.js in Production @felixge Zero to Node @williamjohnbert