A million connections and beyond - Node.js at scale

Jul 26, 2011Download as KEY, PDF43 likes32,843 views

This document discusses benchmarks and performance testing of Node.js. It notes that while Node.js can handle over 1 million connections, benchmarks are not that important as other factors like productivity. It explores how to meaningfully measure Node.js performance, compares Node.js to other frameworks like Erlang and Tornado, and argues that benchmarks should reflect real-world use cases rather than simplistic "hello world" tests. The document questions overreliance on benchmarks and emphasizes picking the right tool based on the task.

A million connections...
AND BEYOND!!!
Node.js at Scale

What this talk is really
about
Picking meaningful benchmarks

Current state of Node.js benchmarks

Understanding why benchmarks aren't _that_
important

How to pick the right language/framework/lib

What can we measure?

Computation Disk I/O

Net work I/O Throughput

TCP Libraries

UDP URL Parsing

HTTP etc

How do we measure?

Load averages

Memory usage

Average time - Average perf. of each operation

Latency - Actual performance of each operation

Comparison

Erlang vs. Node.js vs. Tornado

3 Erlang libs

Stock Node.js

Stock Tornado

Single core

Questioning benchmarks

What do average times mean?

Responses on a curve

Who uses in memory servers?

Finding Node's strength
connections: 933990

errors: 0

Read from remote host gqzdj9ab.joyent.us:
Operation timed out

Connection to gqzdj9ab.joyent.us closed.

Enki:~ $

var net = require('net')

var conns = 0

function connectToServer(ip) {
conn = net.createConnection(8000, ip)
conn.on('connect', function() {
conns += 1
})
conn.on('end', function() {
conns -= 1
})
}

for(i=0;i<61000;i++) {
connectToServer('72.2.120.106')
}

var net = require('net')

var s = net.createServer()
var c = 0;
var e = 0;

s.on('connection', function(socket) {
c += 1

socket.on('end', function() {
c -= 1
})
socket.on('error', function(e) {
e += 1
})
})

s.listen(8000)

setInterval(function() {
console.log('connections: ' + c)
console.log('errors: ' + e)
}, 5000)

Finding Node's strength
PID USERNAME SIZE RSS STATE PRI NICE TIME CPU PROCESS/NLWP

22593 root 758M 642M cpu11 25 0 0:17:54 6.2% node/1

22542 croucher 4308K 3084K cpu2 59 0 0:00:08 0.2% prstat/1

...

...

ZONEID NPROC SWAP RSS MEMORY TIME CPU ZONE

27 31 1489M 782M 38% 1:59:54 6.3% gqzdj9ab

Where to use atomic
measurements

Measuring performance improvements over time

Figuring out the hot-path

Proﬁling against your speciﬁc use case

I am a super

stuff
effective
measurement
Because I put stuff on one axis and
things on another and now I'm like things
proper science and you should totally
use me to base all your judgements
about everything on…

no seriously...

Why benchmarks aren't
as important as we think

There is a tradeoff bet ween performance and
productivity

If this weren't true we'd all still be writing in ASM

Fit for purpose
Sandboxed language Event Driven
PHP, Python Node.js

Java, C# Event Machine (Ruby)
Ruby, etc Tornado (Python)

Message Passing
Erlang

Class of languages for the
Internet
New languages/platforms like Node.js designed for
Internet applications

New class of languages are efﬁcient enough, but are
they easy enough?

Node.js designed from scratch for net work server
programming

Reasons to use Node

It's really fast. Very much fast enough.

It's easy to use for Internet/Web applications.

It's JavaScript.

It has an extremely active community.

It has a lot of project velocity.

What we need from
benchmarks
Benchmarks to test real world use cases
Servers that do more than just 'hello world'
Benchmarks to compare real test cases from many
platforms
Benchmarks that reﬂect mobile clients
Node CI on many platforms

Questions?

I'm on Twitter http:/ witter.com/sh1mmer
/t

That's a "one" in my nick

Check out the book on http://ofps.oreilly.com

It's free to read and comment. New release this
week

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Using Node.js to Build Great Streaming Services - HTML5 Dev ConfTom Croucher

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This document provides an introduction and overview of a Node.js tutorial presented by Tom Hughes-Croucher. The tutorial covers topics such as building scalable server-side code with JavaScript using Node.js, debugging Node.js applications, using frameworks like Express.js, and best practices for deploying Node.js applications in production environments. The tutorial includes exercises for hands-on learning and demonstrates tools and techniques like Socket.io, clustering, error handling and using Redis with Node.js applications.

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The document discusses using Node.js to build scalable server-side code with JavaScript in a way that works for all users regardless of device or browser capabilities. It covers topics like balancing goals of speed, maintainability and cost when building applications that need to work across computers, mobile phones and other devices with varying processing power and bandwidth. It provides examples of using JSON instead of HTML for lightweight data transfer and techniques like client-side MVC patterns and templates. It also emphasizes the importance of server-side fallbacks for HTML5 features not supported on all browsers to ensure a good experience for all users.

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1. The document discusses multi-tiered Node.js architectures to improve scalability and efficiency. It suggests moving non-client facing work like logging and processing to separate "farms" or clusters to avoid blocking the main event loop. 2. Another approach presented is to use front-end clusters or "shards" to distribute client requests across multiple Node processes to take advantage of parallel processing. This improves response times. 3. The key goals are to minimize client response times by keeping the main event loop available, while maximizing server resource efficiency by moving heavy processing tasks out of the main process.

A language for the Internet: Why JavaScript and Node.js is right for Internet...Tom Croucher

Node.js and JavaScript are well-suited for Internet applications because Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, capable of supporting many more concurrent connections than traditional server-side models like Apache. This event loop system allows Node.js to handle multiple requests simultaneously without blocking any specific request. It also minimizes memory usage so more requests can be served from fewer servers.

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Increasingly we want to do more with the web and Internet applications we build. We have more features, more data, more users, more devices and all of it needs to be in real-time. With all of these demands how can we keep up? The answer is choosing a language and a platform that are optimized for the kind of architecture Internet and web applications really have. The traditional approach prioritises computation, assigning server resources before they are actually needed. JavaScript and Node.js both take an event driven approach only assigning resources to events as they happen. This allows us to make dramatic gains in performance and resource utilization while still having an environment which is fun and easy to program.

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Node.js allows JavaScript to be used for server-side programming. It is a popular choice because JavaScript programmers can reuse code and libraries on both the client-side and server-side. Node.js is also fast and non-blocking which allows for high concurrency levels. The Node.js ecosystem includes many libraries like Express for building web servers and Mustache.js for templating that make building server-side JavaScript applications easy.

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This document discusses using JavaScript on the server side with Node.js and the YUI framework. It begins by explaining why server-side JavaScript is useful and discusses JavaScript runtimes like V8, SpiderMonkey, and Rhino. It then covers Node.js, CommonJS frameworks, and how to use YUI modules on the server by enabling YUI's module loader. Examples are provided for accessing remote data, rendering HTML on the server, and implementing progressive enhancement.

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A million connections and beyond - Node.js at scale

1. A million connections... AND BEYOND!!! Node.js at Scale

2. One million connections!!!

3. A million isn't very much these days...

4. One hundred billion connections!!!

5. What this talk is really about Picking meaningful benchmarks Current state of Node.js benchmarks Understanding why benchmarks aren't _that_ important How to pick the right language/framework/lib

6. What can we measure? Computation Disk I/O Net work I/O Throughput TCP Libraries UDP URL Parsing HTTP etc

7. How do we measure? Load averages Memory usage Average time - Average perf. of each operation Latency - Actual performance of each operation

8. Comparison Erlang vs. Node.js vs. Tornado 3 Erlang libs Stock Node.js Stock Tornado Single core

9. Desired vs. Real Responses

10. Response times

11. I pity the fool who uses Node

12. Questioning benchmarks What do average times mean? Responses on a curve Who uses in memory servers?

13. Finding Node's strength connections: 933990 errors: 0 Read from remote host gqzdj9ab.joyent.us: Operation timed out Connection to gqzdj9ab.joyent.us closed. Enki:~ $

14. var net = require('net') var conns = 0 function connectToServer(ip) { conn = net.createConnection(8000, ip) conn.on('connect', function() { conns += 1 }) conn.on('end', function() { conns -= 1 }) } for(i=0;i<61000;i++) { connectToServer('72.2.120.106') }

15. var net = require('net') var s = net.createServer() var c = 0; var e = 0; s.on('connection', function(socket) { c += 1 socket.on('end', function() { c -= 1 }) socket.on('error', function(e) { e += 1 }) }) s.listen(8000) setInterval(function() { console.log('connections: ' + c) console.log('errors: ' + e) }, 5000)

16. Finding Node's strength PID USERNAME SIZE RSS STATE PRI NICE TIME CPU PROCESS/NLWP 22593 root 758M 642M cpu11 25 0 0:17:54 6.2% node/1 22542 croucher 4308K 3084K cpu2 59 0 0:00:08 0.2% prstat/1 ... ... ZONEID NPROC SWAP RSS MEMORY TIME CPU ZONE 27 31 1489M 782M 38% 1:59:54 6.3% gqzdj9ab

17. Where to use atomic measurements Measuring performance improvements over time Figuring out the hot-path Proﬁling against your speciﬁc use case

18. 8x Perf improvement

19. I am a super stuff effective measurement Because I put stuff on one axis and things on another and now I'm like things proper science and you should totally use me to base all your judgements about everything on… no seriously...

20. Why benchmarks aren't as important as we think There is a tradeoff bet ween performance and productivity If this weren't true we'd all still be writing in ASM

21. Fit for purpose Sandboxed language Event Driven PHP, Python Node.js Java, C# Event Machine (Ruby) Ruby, etc Tornado (Python) Message Passing Erlang

22. Class of languages for the Internet New languages/platforms like Node.js designed for Internet applications New class of languages are efﬁcient enough, but are they easy enough? Node.js designed from scratch for net work server programming

23. Reasons to use Node It's really fast. Very much fast enough. It's easy to use for Internet/Web applications. It's JavaScript. It has an extremely active community. It has a lot of project velocity.

24. What we need from benchmarks Benchmarks to test real world use cases Servers that do more than just 'hello world' Benchmarks to compare real test cases from many platforms Benchmarks that reﬂect mobile clients Node CI on many platforms

25. Questions? I'm on Twitter http:/ witter.com/sh1mmer /t That's a "one" in my nick Check out the book on http://ofps.oreilly.com It's free to read and comment. New release this week

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