Running into a situation where requests are crashing on Heroku before as Node process exits, leaving that Node process orphaned — and delivering an ugly Heroku error message.
What I think needs happens is: Express needs a timeout set, and once reached, stops any process in flight (and handles the timeout in a graceful way — sending an error message to user).
https://www.npmjs.com/package/connect-timeout
I'm looking at connect-timeout and it seems a little awkward to sandwich in a haltOnTimedout after every middleware. Is there some other (better) way to manage timeouts in Express or this the best way?
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We have a NodeJS/Express server running in production, and occasionally, all requests are getting blocked. The web requests are being received, but not processed (and they eventually all time out). After a few minutes, it'll begin accepting requests again, but then almost immediately begin blocking like before.
We've been trying to reproduce the issue locally but can't reproduce and determine what the cause is. My guess is the event loop is getting blocked from either a synchronous operation that's taking too long to complete or doesn't complete at all.
Are there any ways to debug a live production system and figure out what's causing the block? I've searched, but could only find solutions for local development. Is my best solution to look back at the logs, see where the last request that didn't block complete (before it started blocking), and debug that?
Using Node 6.2.2, Express 4.13.4, and running on Heroku.
I have a question regarding the examples out there when using Nodejs, Express and Jade for templates.
All the examples show how to build some sort of a user administrative interface where you can add user profiles, delete them and manage them.
Those are considered beginner's guides to NodeJs. My question is around the fact that if I have have 10 users concurrently accessing the same interface and doing the same operations, surely NodeJs will block the requests for the other users as they are running on the same port.
So let's say I am pulling out a list of users which may be something like 10000. Yes I can do paging, but that is not the point. While I am getting the list from the server another 4 users want to access the application. They have to wait for my process to end. That is my question - how can one avoid that using NodeJS & Express?
I am on this issue for a couple of months! I currently have something in place that does the following:
Run the main processing of stuff on a port
Run a Socket.io process on a different port
Use a sticky session
The idea is that I do a request (like getting a list of items), and immediately respond with some request reference but without the requested items, thus releasing the port.
In the background "asynchronously" I then do the process of getting the items. Upon which when completed, I do an http request from one node to the socket node port node SENDING the items through.
When that is done I then perform a socket.io emit WITH the data and the initial request reference so that the correct user gets the message.
On the client side I have an event listening for the socket which then completes the ajax request by populating the list.
I have SOME success in doing this! It actually works to a degree! I have an issue online which complicates matters due to ip addresses, and socket.io playing funny.
I also have multiple workers using clustering. I use it in the following manner:
I create a master worker
I spawn workers
I take any connection request and pass it to the relevant worker.
I do that for the main node request as well as for the socket requests. Like I said I use 2 ports!
As you can see I have had a lot of work done on this and I am not getting a proper solution!
My question is this - have I gone all around the world 10 times only to have missed something simple? This sounds way to complicated to achieve a non-blocking nodejs only website.
I asked myself - surely all these tutorials would have not missed on something as important as this! But they did!
I have researched, read, and tested a lot of code - this is my very first time I ask anything on stackoverflow!
Thank you for any assistance.
P.S. One example of the same approach is this: I request a report using jasper, I pass parameters, and with the "delayed ajax response" approach as described above I simply release the port, and in the background a very intensive report is being generated (and this can be very intensive process as a lot of calculations are being performed)..! I really don't see a better approach - any help will be super appreciated!
Thank you for taking the time to read!
I'm sorry to say it, but yes, you have been going around the world 10 times only to have been missing something simple.
It's obvious that your previous knowledge/experience with webservers are from a blocking point of view, and if this was the case, your concerns had been valid.
Node.js is a framework focused around using a single thread to execute code, which means if it does any blocking operations, no one else would be able to get anything done.
There are some operations that can do this in node, like reading/writing to disk. However, most node operations will be asynchronous.
I believe you are familiar with the term, so I won't go into details. What asynchronous operations allows node to do, is to keep this single thread idle as much as possible. By idle I mean open for other work. If your code is fully asynchronous, then handling 4 concurrent users (or even 400) shouldn't be a problem, even for a single thread.
Now, in regards to your initial problem of ports: Once a request is received on a given port, node.js execute whatever code you have written for it, until it encounters an asynchronous operation as soon as that happens, it is available to to pick up more requests on the same port.
The second problem you inquire about, is the database operation. In this case, node-js would send the query to the database (which takes no time at all) and the database does that actual execution of the query. In the meantime, node is free to do whatever it wants, until the database is finished, and lets node know there is a result to fetch.
You can recognize async operations by their structure: my_function(..., ..., callback). Function that uses a callback function, is in most cases asynch.
So bottom line: Don't worry about the problems around blocking IO, as you will hardly encounter any in node. Use a single port if you want (By creating multiple child processes, you can even have multiple node instances on the same port).
Hope this explains it good enough. If you have any further questions, let me know :)
We have a C# Web API server and a Node Express server. We make hundreds of requests from the C# server to a route on the Node server. The route on the Node server does intensive work and often doesn't return for 6-8 seconds.
Making hundreds of these requests simultaneously seems to cause the Node server to fail. Errors in the Node server output include either socket hang up or ECONNRESET. The error from the C# side says
No connection could be made because the target machine actively refused it.
This error occurs after processing an unpredictable number of the requests, which leads me to think it is simply overloading the server. Using a Thread.Sleep(500) on the C# side allows us to get through more requests, and fiddling with the wait there leads to more or less success, but thread sleeping is rarely if ever the right answer, and I think this case is no exception.
Are we simply putting too much stress on the Node server? Can this only be solved with Load Balancing or some form of clustering? If there is an another alternative, what might it look like?
One path I'm starting to explore is the node-toobusy module. If I return a 503 though, what should be the process in the following code? Should I Thread.Sleep and then re-submit the request?
It sounds like your node.js server is getting overloaded.
The route on the Node server does intensive work and often doesn't return for 6-8 seconds.
This is a bad smell - if your node process is doing intense computation, it will halt the event loop until that computation is completed, and won't be able to handle any other requests. You should probably have it doing that computation in a worker process, which will run on another cpu core if available. cluster is the node builtin module that lets you do that, so I'll point you there.
One path I'm starting to explore is the node-toobusy module. If I return a 503 though, what should be the process in the following code? Should I Thread.Sleep and then re-submit the request?
That depends on your application and your expected load. You may want to refresh once or twice if it's likely that things will cool down enough during that time, but for your API you probably just want to return a 503 in C# too - better to let the client know the server's too busy and let them make their own decision then to keep refreshing on its behalf.
I am using Sails js (node js framework) and running it on Heroku and locally.
The API function reads from an external file and performs long computations that might take hours on the queries it read.
My concern is that after a few minutes it returns with timeout.
I have 2 questions:
How to control the HTTP request / response timeout (what do I really need to control here?)
Is HTTP request considered best practice for this target? or should I use Socket IO? (well, I have no experience on Socket IO and not sure if I am not talking bullshit).
You should use the worker pattern to accomplish any work that would take more than a second or so:
"Web servers should focus on serving users as quickly as possible. Any non-trivial work that could slow down your user’s experience should be done asynchronously outside of the web process."
"The Flow
Web and worker processes connect to the same message queue.
A process adds a job to the queue and gets a url.
A worker process receives and starts the job from the queue.
The client can poll the provided url for updates.
On completion, the worker stores results in a database."
https://devcenter.heroku.com/articles/asynchronous-web-worker-model-using-rabbitmq-in-node
I'm using NodeJS to run a socket server (using socket.io). When a client connects, I want am opening and running a module which does a bunch of stuff. Even though I am careful to try and catch as much as possible, when this module throws an error, it obviously takes down the entire socket server with it.
Is there a way I can separate the two so if the connected clients module script fails, it doesn't necessarily take down the entire server?
I'm assuming this is what child process is for, but the documentation doesn't mention starting other node instances.
I'd obviously need to kill the process if the client disconnected too.
I'm assuming these modules you're talking about are JS code. If so, you might want to try the vm module. This lets you run code in a separate context, and also gives you the ability to do a try / catch around execution of the specific code.
You can run node as a separate process and watch the data go by using spawn, then watch the stderr/stdout/exit events to track any progress. Then kill can be used to kill the process if the client disconnects. You're going to have to map clients and spawned processes though so their disconnect event will trigger the process close properly.
Finally the uncaughtException event can be used as a "catch-all" for any missed exceptions, making it so that the server doesn't get completely killed (signals are a bit of an exception of course).
As the other poster noted, you could leverage the 'vm' module, but as you might be able to tell from the rest of the response, doing so adds significant complexity.
Also, from the 'vm' doc:
Note that running untrusted code is a tricky business requiring great care.
To prevent accidental global variable leakage, vm.runInNewContext is quite
useful, but safely running untrusted code requires a separate process.
While I'm sure you could run a new nodejs instance in a child process, the best practice here is to understand where your application can and will fail, and then program defensively to handle all possible error conditions.
If some part of your code "take(s) down the entire ... server", then you really to understand why this occurred and solve that problem rather than rely on another process to shield you from the work required to design and build a production-quality service.