Curiosity Media

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

SpanishDict.com

Demo

A Spanish-English Dictionary

SpanishDict.com 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.

Our visitors

A quick glance 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

Our Services

Our Traffic

Very low latency for our db-backed services.

1. Know when to Node

Should you use Node.js?

Yes

• Small apps (think JSON APIs)
• "Glue" for services or data
  • Proxies
  • Concurrent data
  • Use the stream module
• Lots of connections

Maybe not

• Computation
• Legacy applications
• "Solved" problems (fuzzy search, NLP, etc.)

2. Keep up with Node

Bleeding edge, lots of breakage.

Stay up to date with Node.js and libraries.

Infrastructure

Node.js deployments

• PAAS: Often, the easier way.

  • Joyent, Heroku, Nodejitsu, etc.

• IAAS: Expect some DIY

  • Build custom Node.js versions
  • Install modules from scratch
  • Get ready to roll back

3. Design for failure

Fail and recover at multiple levels.

App-level

• Errors
  • Handle: uncaughtException
  • Listen: foo.on("error")
• Use the cluster module
  • Workers: die early on errors
  • Master: monitor and kill workers

Server-level

• Use monit or alternatives
• Restart the Node.js master

Service-level

• Have lots of small apps
• Stateless, fungible servers
• Hot failover wherever possible

4. Isolate services

Separate resource and failure classes.

Resources

• CPU/Load: Run out of this and it's over.
• Also, memory, I/O, etc.
• ... and combinations thereof

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

Takeaways

• Always preserve CPU
• Monitor system stats for cross-pressure

5. Analyze everything

How well are we addressing lessons 1-4?

Data drives problem discovery and action.

Log, Monitor, Mine

Things to look for

Some metrics that affect Node.js apps

Decisions, Goals

• Identify
  • Resource pressure
  • Bugs
• Decide
  • Scale up, scale down?
  • Separate?

Demo