This question is meant for single core only therefore multiple cores are out.
I am running Node.js application as HTTP server on single core computer using Express.js. Assuming that my server is able to handle 1000 concurrent requests, would clustering brings about any better in response speed ?
Does process context switch has much impact on performance in this case ?
I wouldn't expect improvements in speed, but you might get some other benefits.
for example if the process crashes, the other nodejs instance could still work.
would clustering brings about any better in response speed ?
You are aware of the fact that in clustered mode, your application will be running behind a load balancer, that will in turn take some CPU and memory to manage and forward the network traffic. Then, what's left of the resources, will be used to distribute the network load.
Apart from a few, rare and easily avoidable cases such as #Cristyan mentions—in which case your load balancer can be an orchestrator managing most of the stuff, like Kubernetes—running a Node.js app in cluster does not make sense to me, on a single CPU core. If the process has to wait for an item, it has to wait for it! Asynchronously you can make it work on other requests, but even in this case, other processes would want to take a share of CPU too.
Related
I am running a node app on a Digital Ocean cloud server, and the app merely services API requests. All client-side assets are served by a CDN, and the DB is accessed remotely, rather than stored on the server instance itself.
I have the choice of a greater number of vCPUs or RAM. I have no idea what that means in any way, so any feedback is a great help.
A single node.js server will run your Javascript on only one CPU so it doesn't help your Javascript run any faster to have more CPUs unless you cluster your app and run multiple node.js processes sharing the load of your app or unless there are other processes on the same server that are being used by your server.
Having more RAM (memory) will only improve things if you actually need more RAM. That depends entirely upon what the memory usage profile is of your app and how much RAM you already have available. Probably, you would already know if you were running out of RAM because you either get drastic slow-down when the OS starts page swapping or your process crashes when out of memory.
So, in order to know which would benefit you more, you really need more data on how your existing app is performing (whether it is ever bog down with CPU intensive operations and how much RAM it uses compared to how much you have available). It is quite possible that neither will actually matter to you - it totally depends upon the usage profile or your server process.
If you have no more data than this and have to make a choice, choose the vCPUs because there are some circumstances where it might help you (and gives you the option to go to clustering in the future if needed) whereas adding more RAM when you aren't even using what you already have won't help you at all.
I have a very simple nodejs application that accepts json data (1KB approx.) via POST request body. The response is sent back immediately to the client and the json is posted asynchronously to an Apache Kafka queue. The number of simultaneous requests can go as high as 10000 per second which we are simulating using Apache Jmeter running on three different machines. The target is to achieve an average throughput of less than one second with no failed requests.
On a 4 core machine, the app handles upto 4015 requests per second without any failures. However since the target is 10000 requests per second, we deployed the node app in a clustered environment.
Both clustering in the same machine and clustering between two different machines (as described here) were implemented. Nginx was used as a load balancer to round robin the incoming requests between the two node instances. We expected a significant improvement in the throughput (like documented here) but the results were on the contrary.
The number of successful requests dropped to around 3100 requests per second.
My questions are:
What could have gone wrong in the clustered approach?
Is this even the right way to increase the throughput of Node application?
We also did a similar exercise with a java web application in Tomcat container and it performed as expected 4000 requests with a
single instance and around 5000 successful requests in a cluster
with two instances. This is in contradiction to our belief that
nodejs performs better than a Tomcat. Is tomcat generally better
because of its thread per request model?
Thanks a lot in advance.
Per your request, I'll put my comments into an answer:
Clustering is generally the right approach, but whether or not it helps depends upon where your bottleneck is. You will need to do some measuring and some experiments to determine that. If you are CPU-bound and running on a multi-core computer, then clustering should help significantly. I wonder if your bottleneck is something besides CPU such as networking or other shared I/O or even Nginx? If that's the case, then you need to fix that before you would see the benefits of clustering.
Is tomcat generally better because of its thread per request model?
No. That's not a good generalization. If you are CPU-bound, then threading can help (and so can clustering with nodejs). But, if you are I/O bound, then threads are often more expensive than async I/O like nodejs because of the resource overhead of the threads themselves and the overhead of context switching between threads. Many apps are I/O bound which is one of the reasons node.js can be a very good choice for server design.
I forgot to mention that for http, we are using express instead of the native http provided by node. Hope it does not introduce an overhead to the request handling?
Express is very efficient and should not be the source of any of your issues.
As jfriend said , you need to find the bottlenecks ,
one thing you can try is to reduce the bandwith/throughput by using sockets to pass the json and especially this library https://github.com/uNetworking/uWebSockets.
The main reason for that is that an http request is significantly heavier than a socket connection.
Good Example : https://webcheerz.com/one-million-requests-per-second-node-js/
lastly you can also compress the json via (http gzip) or a third party module.
work on the weight ^^
Hope it helps!
Ok guys, is it useful to generate more than one websocket instance on a Node.js server? I mean possibly you also create subworkers..
I know, it depends on your hardware and the network cards maximum. But can you reach this maximium with only one task or can you get more performance with several parallel processes?
It depends on the CPU count in your server. Parallel processes (the cluster module) aren't a silver bullet for performance - on a 1 CPU system they might even decrease it just due to overhead. But if you have more than one CPU, a NodeJS process CANNOT use that extra horsepower. The cluster module solves this. Used properly you can use all the available CPU power on the system.
Note that this has nothing to do with WebSockets themselves. This is a core NodeJS architectural constraint. But WebSockets are a great use-case where clustering is advantageous...
I have a simple nodejs webserver running, it:
Accepts requests
Spawns separate thread to perform background processing
Background thread returns results
App responds to client
Using Apache benchmark "ab -r -n 100 -c 10", performing 100 requests with 10 at a time.
Average response time of 5.6 seconds.
My logic for using nodejs is that is typically quite resource efficient, especially when the bulk of the work is being done by another process. Seems like the most lightweight webserver option for this scenario.
The Problem
With 10 concurrent requests my CPU was maxed out, which is no surprise since there is CPU intensive work going on the background.
Scaling horizontally is an easy thing to, although I want to make the most out of each server for obvious reasons.
So how with nodejs, either raw or some framework, how can one keep that under control as to not go overkill on the CPU.
Potential Approach?
Could accepting the request storing it in a db or some persistent storage and having a separate process that uses an async library to process x at a time?
In your potential approach, you're basically describing a queue. You can store incoming messages (jobs) there and have each process get one job at the time, only getting the next one when processing the previous job has finished. You could spawn a number of processes working in parallel, like an amount equal to the number of cores in your system. Spawning more won't help performance, because multiple processes sharing a core will just run slower. Keeping one core free might be preferred to keep the system responsive for administrative tasks.
Many different queues exist. A node-based one using redis for persistence that seems to be well supported is Kue (I have no personal experience using it). I found a tutorial for building an implementation with Kue here. Depending on the software your environment is running in though, another choice might make more sense.
Good luck and have fun!
We host about 150 websites (possibly scaling to 300+) that we are considering migrating to node.js. Most of the sites are fairly low traffic <1mil pageviews per month.
Should each website be it's own node.js process, or should we serve all websites using the same node.js process (or small set of load balanced processes). Is there a technical limit or a reasonable limit to the number of node processes per server?
Process per site: Feels inefficient, but I don't know if it actually is inefficient. Would ensure one buggy site doesn't affect other sites.
Process per core/small set of processes: Likely higher performance, but what happens when I need to update a sites codebase, won't it take down other sites? Also, code failures in one site would affect other sites.
Ideally, I would prefer one process per site so that we could host all sites from each worker server. That way when load increases we can just spin up another identical worker server and load balance between the two without having to arbitrarily say SiteA goes to ServerA and SiteB goes to ServerB. Any node.js gurus available to offer some wisdom?
All static file requests will be handled likely by Nginx or something like Varnish.
There are a lot of issues at play here. The big picture answer is, it depends... as it always does when you bring in the whole "performance" discussion. That being said, the simplest way to get a solid Node set up is to note the following basic facts about NodeJS, and I will also comment on their implications as they pertain to your questions.
The concurrency you get with Node works really good in certain situations, namely IO heavy operations. What we're really talking about here is minimizing the amount of downtime to wait for the next request. Because of this, Node works really well in an environment where there is one process per core on a machine. Node does really well at maximizing the amount of CPU available to serve requests under heavy load. This being said, if you have literally ZERO other work going on in your even loop, you can see minor performance increases (in terms of max requests/second/processor core) by having multiple node processes per core. But, I've never seen any benefit from increasing this number past 3. Even under circumstances where the entire event loop was literally just a file server.
On the process per site comment. This is a bad idea for many reasons. For one, a well put together node server can process thousands of requests per second. Our (company name omitted) servers, hosted through Amazon EC2 on medium clusters (lots of ram, mid CPU clock, 4 cores), typically fail around 3000 requests per second per cluster. Our servers do a fair bit of CPU work, for simple file servers I'm sure you can do much better. Strictly speaking, sure, per site, you will be able to serve more requests by launching each site in its own process/core/escalating quickly here! But it's not necessary from a cost and over complication of your architecture point of view. What I WOULD recommend, is investing in a setup with a lot of RAM. The ability for your server to cache often requested files will effect your performance infinitely more than launching an abundance of processes for a given machine.
On the whole RAM thing. The number of processes you want to launch for a given core is dependant on two things. One is how much synchronous work done in your event loop. The more synchronous work, the more time between a given request coming in and the event loop being ready to adress the next one. If you have a busy event loop, you will be in a situation where you require more processes/CPU Core. The other thing that can effect this, particularly relevant for file servers, is the amount of RAM. Node runs much better in a high ram environment, but you can say this about ANY file server really... What this has to do with, is the number of active asynchronous operations. One downside of the way node works, is under heavy loads, you can get a large number of event handlers active at once. This is great for concurrency/simplicity, however, if your server is busy waiting around for a lot of async disk/IO to happen it will slow down and crash much sooner than if you had plenty of RAM. If you don't have enough RAM to handle all of these event handlers, you will want to keep to the 1 process/core arrangement. Otherwise, it is easier for Node to spin up many event handlers simultaneously, and again cause you to crash sooner than you would otherwise.
I don't really have enough information to tell you what you SHOULD do. This depends entirely too much on the architecture of your specific server, sites, size of your sites, amount of data... etc. But these three pieces of knowledge are the basic things that help you get the most out of your Node server. To be honest, your idea about load balancing mixed with the considerations above, should do nicely for you. Surely, microoptimizations are possible, but if you do these things, you should easily see requests/second in the thousands before you start experiencing crashes because of DDOS type of conditions.
No, don't do it. Keep it simple! And check out http://12factor.net/.
A few hundred processes is nothing compared to the simplicity you otherwise lose. It would be a terrible decision, on so many levels, to have more than one site (or, "logical application unit") served by a single Node process.
If you're asking this question, you may want to explore Node more before you "migrate" to Node. Error handling and separation of concerns are more complicated in Node than in other situations. Specifically, neither the domain nor cluster APIs are mature. But really it's the philosophy of clean and simple application deployment that you'd be violating. I could go on and on.