We have an ASP.NET MVC application hosted in an azure app-service. After running the profiler to help diagnose possible slow requests, we were surprised to see this:
An unusually high % of slow requests in the CLRThreadPoolQueue. We've now run multiple profile sessions each come back having between 40-80% in the CLRThreadPoolQueue (something we'd never seen before in previous profiles). CPU each time was below 40%, and after checking our metrics we aren't getting sudden spikes in requests.
The majority of the requests listed as slow are super simple api calls. We've added response caching and made them async. The only thing they do is hit a database looking for a single record result. We've checked the metrics on the database and the query avg run time is around 50ms or less. Looking at application insights for these requests confirms this, and shows that the database query doesn't take place until the very end of the request time line (I assume this is the request sitting in the queue).
Recently we started including SignalR into a portion of our application. Its not fully in use but it is in the code base. We since switched to using Azure SignalR Service and saw no changes. The addition of SignalR is the only "major" change/addition we've made since encountering this issue.
I understand we can scale up and/or increase the minWorkerThreads. However, this feels like I'm just treating the symptom not the cause.
Things we've tried:
Finding the most frequent requests and making them async (they weren't before)
Response caching to frequent requests
Using Azure SignalR service rather than hosting it on the same web
Running memory dumps and contacting azure support (they
found nothing).
Scaling up to an S3
Profiling with and without thread report
-- None of these steps have resolved our issue --
How can we determine what requests and/or code is causing requests to pile up in the CLRThreadPoolQueue?
We encountered a similar problem, I guess internally SignalR must be using up a lot of threads or some other contended resource.
We did three things that helped a lot:
Call ThreadPool.SetMinThreads(400, 1) on app startup to make sure that the threadpool has enough threads to handle all the incoming requests from the start
Create a second App Service with the same code deployed to it. In the javascript, set the SignalR URL to point to that second instance. That way, all the SignalR requests go to one app service, and all the app's HTTP requests go to the other. Obviously this requires a SignalR backplane to be set up, but assuming your app service has more than 1 instance you'll have had to do this anyway
Review the code for any synchronous code paths (eg. making a non-async call to the database or to an API) and convert them to async code paths
Related
We noticed an interesting issue regarding our serverside rendering of our NextJs application.
The issue occurred when we decided to add fetching of our translation key values (which are fetched via API) on our serverside calls.
We made this decision to reduce CLS and give the user a better overal experience on first load. We didn't think much of it, since it's just another api call being handled returning the json before rendering the page.
Below you see a graph of our cpu usage on AWS, between 10:00 (10AM) and 14:00 (2PM) the fetching of the translation keys was live on production. We had to manually restart every 2h in order for the servers to survive (That is the peak you are seeing). After 16:00 (4PM) We removed this api call from that specific serverside call and you see that the server is stable. From 20:00 (8PM) we enabled an automatic restart to be sure that the servers would survive the night, but as you can see this was not necessary.
The API call in question, just returns a JSON object. It can contain up to 700lines of values which should be fine as our Product listing page can have a larger responses (up to 10k lines). Everything has caching on enabled, so next/static and the api responses. We were also thinking that it might have something to do with outgoing connections not closing in time. But I am making this post because no one really knows why this is an issue.
We are running the following setup:
Dockerized Application
Running on AWS Beanstalk
Cloudfront + Akamai
NextJs v12.2
Node v14.16
If anyone has the smallest idea in which direction to look, please let me know. We appreciate it.
I am currently using an AWS micro instance as a web server for a website that allows users to upload photos. Two questions:
1) When looking at my CloudWatch metrics, I have recently noticed CPU spikes, the website receives very little traffic at the moment, but becomes utterly unusable during these spikes. These spikes can last several hours and resetting the server does not eliminate the spikes.
2) Although seemingly unrelated, whenever I post a link of my website on Twitter, the server crashes (i.e.,Error Establishing a Database Connection). Once restarting Apache and MySQL, the website returns to normal functionality.
My only guess would be that the issue is somehow the result of deficiencies with the micro instance. Unfortunately, when I upgraded to the small instance, the site was actually slower due to fact that the micro instances can have two EC2 compute units.
Any suggestions?
If you want to stay in the free tier of AWS (micro instance), you should off load as much as possible away from your EC2 instance.
I would suggest you to upload the images directly to S3 instead of going through your web server (see some example for it here: http://aws.amazon.com/articles/1434).
S3 can also be used to serve most of your web pages (images, js, css...), instead of your weak web server. You can also add these files in S3 as origin to Amazon CloudFront (CDN) distribution to improve your application performance.
Another service that can help you in off loading the work is SQS (Simple Queue Service). Instead of working with online requests from users, you can send some requests (upload done, for example) as a message to SQS and have your reader process these messages on its own pace. This is good way to handel momentary load cause by several users working simultaneously with your service.
Another service is DynamoDB (managed NoSQL DB service). You can put on dynamoDB most of your current MySQL data and queries. Amazon DynamoDB also has a free tier that you can enjoy.
With the combination of the above, you can have your micro instance handling the few remaining dynamic pages until you need to scale your service with your growing success.
Wait… I'm sorry. Did you say you were running both Apache and MySQL Server on a micro instance?
First of all, that's never a good idea. Secondly, as documented, micros have low I/O and can only burst to 2 ECUs.
If you want to continue using a resource-constrained micro instance, you need to (a) put MySQL somewhere else, and (b) use something like Nginx instead of Apache as it requires far fewer resources to run. Otherwise, you should seriously consider sizing up to something larger.
I had the same issue: As far as I understand the problem is that AWS will slow you down when you reach a predefined usage. This means that they allow for a small burst but after that things will become horribly slow.
You can test that by logging in and doing something. If you use the CPU for a couple of seconds then the whole box will become extremely slow. After that you'll have to wait without doing anything at all to get things back to "normal".
That was the main reason I went for VPS instead of AWS.
I found a question that explains how Play Framework's await() mechanism works in 1.2. Essentially if you need to do something that will block for a measurable amount of time (e.g. make a slow external http request), you can suspend your request and free up that worker to work on a different request while it blocks. I am guessing once your blocking operation is finished, your request gets rescheduled for continued processing. This is different than scheduling the work on a background processor and then having the browser poll for completion, I want to block the browser but not the worker process.
Regardless of whether or not my assumptions about Play are true to the letter, is there a technique for doing this in a Rails application? I guess one could consider this a form of long polling, but I didn't find much advice on that subject other than "use node".
I had a similar question about long requests that blocks workers to take other requests. It's a problem with all the web applications. Even Node.js may not be able to solve the problem of consuming too much time on a worker, or could simply run out of memory.
A web application I worked on has a web interface that sends request to Rails REST API, then the Rails controller has to request a Node REST API that runs heavy time consuming task to get some data back. A request from Rails to Node.js could take 2-3 minutes.
We are still trying to find different approaches, but maybe the following could work for you or you can adapt some of the ideas, I would love to get some feedbacks too:
Frontend make a request to Rails API with a generated identifier [A] within the same session. (this identifier helps to identify previous request from the same user session).
Rails API proxies the frontend request and the identifier [A] to the Node.js service
Node.js service add this job to a queue system(e.g. RabbitMQ, or Redis), the message contains the identifier [A]. (Here you should think about based on your own scenario, also assuming a system will consume the queue job and save the results)
If the same request send again, depending on the requirement, you can either kill the current job with the same identifier[A] and schedule/queue the lastest request, or ignore the latest request waiting for the first one to complete, or other decision fits your business requirement.
The Front-end can send interval REST request to check if the data processing with identifier [A] has completed or not, then these requests are lightweight and fast.
Once Node.js completes the job, you can either use the message subscription system or waiting for the next coming check status Request and return the result to the frontend.
You can also use a load balancer, e.g. Amazon load balancer, Haproxy. 37signals has a blog post and video about using Haproxy to off loading some long running requests that does not block shorter ones.
Github uses similar strategy to handle long requests for generating commits/contribution visualisation. They also set a limit of pulling time. If the time is too long, Github display a message saying it's too long and it has been cancelled.
YouTube has a nice message for longer queued tasks: "This is taking longer than expected. Your video has been queued and will be processed as soon as possible."
I think this is just one solution. You can also take a look EventMachine gem, that helps to improve the performance, handler parallel or async request.
Since this kind of problem may involve one or more services. Think about possibility of improving performance between those services(e.g. database, network, message protocol etc..), if caching may help, try out caching frequent requests, or pre-calculate results.
Hi
I've been working on a medium sized MVC project. It works fine on the localhost at a good speed rate. In each page, there's a lot of server-side data retrieved, I use a lot of jquery to minimize the traffic to the server, but even then, the webpage loads very slowly. There are many events on which I retrieve json results, to get a specific number from the database and make calculations, this data takes a long time to be retrieved on the webpage, although on the localhost it is immediately shown. Also, when I submit pages, it takes awfully a lot of time to submit. I've published my project to GoDaddy's server and also my database is there. What could be the problem that is making the project that slow? How can I minimize it? And why is it only when the website is online and not on the localhost too?
As such, issue can be anywhere and only certain way to know is instrumenting the code. I will suggest that you add simple logging traces with date-time stamp in your server code (note that logging should be configurable, any logging framework (including System.Diagnostic.Trace) should support it) and check where the time is spent. For example, database trips can be expensive etc. If you don't find the culprit on server side code i.e. sever is serving the request in reasonable time then you have to look at the performance over network. Tools such as Fiddler (or Firefox) should help you here - sometimes issuing too many requests from browser is also problematic because browser may make only n concurrent requests or even server may have been configured to accept only n requests from particular client - this could result in serialization of request increasing total response time. These scenarios are difficult to catch on localhost because network latency is almost zero there. You may also use tool such as YSlow for related performance improvement suggestions. But please do your investigation first, find the bottlenecks and then ask for solutions to specific problems.
Run it in chrome. Turn on the developer tools. Expand the Console. watch for errors. Also from there you can monitor those network calls to see which is slow.
if MVC uses entity framework (based on LINQ), it will sure be slow
because LINQ is slow compared to the old ADO.NET
I'm writing a Rails web service that interacts with various pieces of hardware scattered throughout the country.
When a call is made to the web service, the Rails app then attempts to contact the appropriate piece of hardware, get the needed information, and reply to the web client. The time between the client's call and the reply may be up to 10 seconds, depending upon lots of factors.
I do not want to split the web service call in two (ask for information, answer immediately with a pending reply, then force another api call to get the actual results).
I basically see two options. Either run JRuby and use multithreading or else run several regular Ruby instances and hope that not many people try to use the service at a time. JRuby seems like the much better solution, but it still doesn't seem to be mainstream and have out of the box support at Heroku and EngineYard. The multiple instance solution seems like a total kludge.
1) Am I right about my two options? Is there a better one I'm missing?
2) Is there an easy deployment option for JRuby?
I do not want to split the web service call in two (ask for information, answer immediately with a pending reply, then force another api call to get the actual results).
From an engineering perspective, this seems like it would be the best alternative.
Why don't you want to do it?
There's a third option: If you host your Rails app with Passenger and enable global queueing, you can do this transparently. I have some actions that take several minutes, with no issues (caveat: some browsers may time out, but that may not be a concern for you).
If you're worried about browser timeout, or you cannot control the deployment environment, you may want to process it in the background:
User requests data
You enter request into a queue
Your web service returns a "ticket" identifier to check the progress
A background process processes the jobs in the queue
The user polls back, referencing the "ticket" id
As far as hosting in JRuby, I've deployed a couple of small internal applications using the glassfish gem, but I'm not sure how much I would trust it for customer-facing apps. Just make sure you run config.threadsafe! in production.rb. I've heard good things about Trinidad, too.
You can also run the web service call in a delayed background job so that it's not hogging up a web-server and can even be run on a separate physical box. This is also a much more scaleable approach. If you make the web call using AJAX then you can ping the server every second or two to see if your results are ready, that way your client is not held in limbo while the results are being calculated and the request does not time out.