I recently started with node and I have been reading a lot about its limitation of it being single threaded and how it does not utilise your cores and then I read this
http://bit.ly/1n2YW68 (which talk about the new cluster module of nodejs for loadbalancing)
Now I'm not sure I completely agree to it :) because the first thing that I thought of before starting with node on how to make it utilise cores with proper load balancing is via web-server some like upstream module like nginx
like doing something like this
upstream domain1 {
server http://nodeapp1;
server http://nodeapp2;
server http://nodeapp3;
}
So my question is there an advantage to use such cluster module for load balancing to utilise the cores does it has any significant advantage over web server load balancing
or is blog post too far from real use.
Note: I'm ain't concerned about load balancing handle by various app server like passenger(passenger has nodejs support as well but something that I'm not looking for answer :)) which I already know since I'm mostly a ruby programmer
One other option you can use to cluster NodeJs applications is to deploy the app using PM2.
Clustering is just easy as this, You don't need to implement clustering by hand
pm2 start app.js -i max
PM2 is an expert to auto detect the number of available CPUs and run as many processes as possible
Read about PM2 cluster mode here
http://pm2.keymetrics.io/docs/usage/cluster-mode/
For controlling the load of IO operations, I wrote a library called QueueP using the memoization concept. You can even customize the memoization logic and gain speedup values of more than 10, sometimes
https://www.npmjs.com/package/queuep
As far as I know, the built in node cluster is not a good solution yet (load is not evenly distributed across cores). Until v0.12: http://strongloop.com/strongblog/whats-new-in-node-js-v0-12-cluster-round-robin-load-balancing/
So you should use nginx until then. After that we will see some benchmarks comparing both options and see if the built in cluster module is a good choice.
Related
After reading a handful of articles on scaling node apps I have not yet made up my mind about when should I use node builtin cluster or simply adding more dynos.
Let me tell you I have already read the following threads on StackOverflow:
How to properly scale nodejs app on heroku using clusters
Running Node.js App with cluster module is meaningless in Heroku?
As far as I understood it, if I make use of node cluster functionality I will end up with the total memory available divided by the number of forked processes.
On the other hand, if I add one more dyno I will double the memory available.
So, what is the point of using node clusters?
It's not really an either-or situation. You can make use of multiple node cluster instances on multiple dynos. Memory isn't really what you want to look at, though, since that would be a shared resource. CPU / core usage is more relevant to clustering in node, since each node process can only make use of one CPU core at a time.
It's really going to depend on which dynos you are using, too.
Have you seen these suggestions on the official heroku docs yet?
I am very new to Node.js and express. I am currently learning it by building my own services.
I recently read about clusters. I understood what clusters do. What I am not able to understand is how to make use of clusters in a production application.
One way I can think of is to use the Master process to just sit in front and route the incoming request to the next available child process in a round robin fashion. I am not sure if this is how it is designed to be used. I would like to know how should clusters be used in a typical web application.
Thanks.
The node.js cluster modules is used with node.js any time you want to spread out the request processing across multiple node.js processes. This is most often used when you wish to increase your ability to handle more requests/second and you have multiple CPU cores in your server. By default, a single instance of node.js will not fully utilize multiple cores because the core Javascript you run in your server is single threaded (uses one core). Node.js itself does use threads for some things internally, but that's still unlikely to fully utilize a mult-core system. Setting up a clustered node.js process for each CPU core will allow you to better maximize the available compute resources.
Clustering also provides you with some additional fault tolerance. If one cluster process goes down, you can still have other live clusters serving requests while the disabled cluster restarts.
The cluster module for node.js has a couple different scheduling algorithms - the round robin you mention is one. You can read more about that here: Cluster Round-Robin Load Balancing.
Because each cluster is a separate process, there is no automatic shared data among the different cluster processes. As such, clustering is simplest to implement either where there is no shared data or where the shared data is already in a place that it can be accessed by multiple processes (such as in a database).
Keep in mind that a single node.js process (if written to properly use async I/O and not heavily compute bound) can server many requests itself at once. Clustering is when you want to expand scalability beyond what one instance can deliver.
I have created a poc on cluster in nodejs and added some details in the below blogs. Once go through it. It may provide some clearance.
https://jksnu.blogspot.com/2022/02/cluster-in-node-js-application.html
https://jksnu.blogspot.com/2022/02/cluster-management-in-node-js.html
Are there any special tuning tips for strengthening an API built on top of the hapijs framework?
Especially if you have lots of concurrent request (+10000/sec) that are accessing the DB?
I'm using PM2 to start my process in "cluster mode" to be able to load-balance to different cores on the server
I don't need to serve static content, so there's no apache/nginx proxy
update 17:11
Running tests with 1000 requests/sec (with loader.io) results in this curve - ok, so far. but I'm wondering if there is still room for improvements.
(hardware: 64gb / 20 core digital ocean droplet)
In the end I just used a combination of node's http and the body-parser module to achieve what I needed.
But I think that this was only viable, because my application had just two endpoint (one GET, one POST).
If your application logic is rather complicated and you want to stick with hapi, think about using a load-balancer and dividing the load to multiple VMs.
Loadtest results (new setup on an even smaller DO droplet):
Creating a node.js application is simple enough.
var app = require('express')();
app.get('/',function(req,res){
res.send("Hello world!");
});
But suppose people became obsessed with your Hello World! application and exhausted your resources. How could this example be scaled up on practice? I don't understand it, because yes, you could open several node.js instance in different computers - but when someone access http://your_site.com/ it aims directly that specific machine, that specific port, that specific node process. So how?
There are many many ways to deal with this, but it boils down to 2 things:
being able to use more cores per server
being able to scale beyond more than one server.
node-cluster
For the first option, you can user node-cluster or the same solution as for the seconde option. node-cluster (http://nodejs.org/api/cluster.html) essentially is a built in way to fork the node process into one master and multiple workers. Typically, you'd want 1 master and n-1 to n workers (n being your number of available cores).
load balancers
The second option is to use a load balancer that distributes the requests amongst multiple workers (on the same server, or across servers).
Here you have multiple options as well. Here are a few:
a node based option: Load balancing with node.js using http-proxy
nginx: Node.js + Nginx - What now? (using more than one upstream server)
apache: (no clearly helpful link I could use, but a valid option)
One more thing, once you start having multiple processes serving requests, you can no longer use memory to store state, you need an additional service to store shared states, Redis (http://redis.io) is a popular choice, but by no means the only one.
If you use services such as cloudfoundry, heroku, and others, they set it up for you so you only have to worry about your app's logic (and using a service to deal with shared state)
I've been working with node for quite some time but recently got the opportunity to try scaling my node apps and have been researching on the same topic for some time now and have come across following pre-requisites for scaling:
My app needs to be available on a distributed system each running multiple instances of node
Each system should have a load balancer that helps distribute traffic across the node instances.
There should be a master load balancer that should distribute traffic across the node instances on distributed systems.
The master balancer should always be running OR should have a dependable restart mechanism to keep the app stable.
For the above requisites I've come across the following:
Use modules like cluster to start multiple instances of node in a system.
Use nginx always. It's one of the most simplest mechanism for creating a load balancer i've came across so far
Use HAProxy to act as a master load balancer. A few pointers on how to use it and keep it forever running.
Useful resources:
Horizontal scaling node.js and websockets.
Using cluster to take advantages of multiple cores.
I'll keep updating this answer as I progress.
The basic way to use multiple machines is to put them behind a load balancer, and point all your traffic to the load balancer. That way, someone going to http://my_domain.com, and it will point at the load balancer machine. The sole purpose (for this example anyways; in theory more could be done) of the load balancer is to delegate the traffic to a given machine running your application. This means that you can have x number of machines running your application, however an external machine (in this case a browser) can go to the load balancer address and get to one of them. The client doesn't (and doesn't have to) know what machine is actually handling its request. If you are using AWS, it's pretty easy to set up and manage this. Note that Pascal's answer has more detail about your options here.
With Node specifically, you may want to look at the Node Cluster module. I don't really have alot of experience with this module, however it should allow you to spawn multiple process of your application on one machine all sharing the same port. Also node that it's still experimental and I'm not sure how reliably it will be.
I'd recommend to take a look to http://senecajs.org, a microservices toolkit for Node.js. That is a good start point for beginners and to start thinking in "services" instead of monolitic applications.
Having said that, building distributed applcations is hard, take time to learn, take LOT of time to master it, and usually you will face a lot trade-off between performance, reliability, manteinance, etc.
I have just learned about Heroku and was pretty much excited to test it out. Ive quickly assembled their demo's with Node.js Language and stumbled across a problem. When running the application locally, apache benchmark prints roughly about 3500 request/s but when its on the cloud that drops to 10 request/s and does not increase or lower based on network latency. I cannot believe that this is the performance they are asking 5 cents/hour for and highly suspect my application to be not multi-threaded.
This is my code.js: http://pastebin.com/hyM47Ue7
What configuration do I need to apply in order to get it 'running' (faster) on Heroku ? Or what other web servers for node.js could I use ?
I am thankful for every answer on this topic.
Your little example is not multi-threaded. (Not even on your own machine.) But you don't need to pay for more dyno's immediately, as you can make use of multiple cores on a dyno, see this answer Running Node.js App with cluster module is meaningless in Heroku?
To repeat that answer: a node solution to using multiple processes that should increase your throughput is to use the (built-in) cluster module.
I would guess that you can easily get more than 10 req/s from a heroku dyno without a problem, see this benchmark, for example:
http://openhood.com/ruby/node/heroku/sinatra/mongo_mapper/unicorn/express/mongoose/cluster/2011/06/14/benchmark-ruby-versus-node-js/
What do you use to benchmark?
You're right, the web server is not multi-threaded, until you pay for more web dynos. I've found Heroku is handy for prototyping; depending on the monetary value of your time, you may or may not want to use it to set up a scalable server instead of using EC2 directly.