I have an Azure function app triggered by an HttpRequest. The function app reads the request, tosses one copy of it into a storage table for safekeeping and sends another copy to a queue for further processing by another element of the system. I have a client running an ApacheBench test that reports approximately 148 requests per second processed. That rate of processing will not be enough for our expected load.
My understanding of function apps is that it should spawn as many instances as is needed to handle the load sent to it. But this function app might not be scaling out quickly enough as it’s only handling that 148 requests per second. I need it to handle at least 200 requests per second.
I’m not 100% sure the problem is on my end, though. In analyzing the performance of my function app I found a LOT of 429 errors. What I found online, particularly https://learn.microsoft.com/en-us/azure/azure-resource-manager/resource-manager-request-limits, suggests that these errors could be due to too many requests being sent from a single IP. Would several ApacheBench 10K and 20K request load tests within a given day cause the 429 error?
However, if that’s not it, if the problem is with my function app, how can I force my function app to spawn more instances more quickly? I assume this is the way to get more throughput per second. But I’m still very new at working with function apps so if there is a different way, I would more than welcome your input.
Maybe the Premium app service plan that’s in public preview would handle more throughput? I’ve thought about switching over to that and running a quick test but am unsure if I’d be able to switch back?
Maybe EventHub is something I need to investigate? Is that something that might increase my apparent throughput by catching more requests and holding on to them until the function app could accept and process them?
Thanks in advance for any assistance you can give.
You dont provide much context of you app but this is few steps how you can improve
If you want more control you need to use App Service plan with always on to avoid cold start, also you will need to configure auto scaling since you are responsible in this plan and auto scale is not enabled by default in app service plan.
Your azure function must be fully async as you have external dependencies so you dont want to block thread while you are calling them.
Look on the limits. Using host.json you can tweek it.
429 error means that function is busy to process your request, so probably when you writing to table you are not using async and blocking thread
Function apps work very well and scale as it says. It could be because request coming from Single IP and Azure could be considering it DDOS. You can do the following
AzureDevOps Load Test
You can load test using one of the azure service . I am very sure they have better criteria of handling IPs. Azure DeveOps Load Test
Provision VM in Azure
The way i normally do is provision the VM (windows 10 pro) in azure and use JMeter to Load test. I have use this method to test and it works fine. You can provision couple of them and subdivide the load.
Use professional Load testing services
If possible you may use services like Loader.io . They use sophisticated algos to run the load test and provision bunch of VMs to run the same test.
Use Application Insights
If not already you must be using application insights to have a better look from server perspective. Go to live stream and see how many instance it would provision to handle the load test . You can easily look into events and error logs that may be arising and investigate. You can deep dive into each associated dependency and investigate the problem.
Related
In some 1-5% of our requests, we are seeing slow communication between APIs (REST API requests). Both APIs are developed by us and hosted on Azure, each app service on its own app service plan in the same region, P1v2 tier.
What we are seeing on application insights is that POST or GET requests on origin API can take a few seconds to execute, while real execution time on destination API is only a few milliseconds.
Examples (first line POST request on origin, second execution time on destination API): slow req 1, slow req 2
Our best guess is that the time difference is lost in communication between components. We don't have an explanation for it since the payload is really small and in most cases, communication takes less than 5 milliseconds.
We dismiss the possible explanation it could be due to component cold start since it happens during constant load and no horizontal scaling was performed.
Do you have any idea what might cause it or how to do additional analysis in order to discover it?
If you're running multiple sites on the App Service Plan, then enable the "Always On" setting for your web app > All Settings > Application Settings > Click on Always On
See here for details: https://azure.microsoft.com/en-us/documentation/articles/web-sites-configure/
When Always On is off, the site is shut down after 20 minutes of inactivity to free up resources for any additional websites that might be using the same App Service Plan.
The amount of information it needs to collect, process and then present itself requires some time, and involve internal calls as well, that is why considering the server load and usage, it takes around 6 to 7 seconds sometimes even more.
To Troubleshoot that latency, try this steps, provided by Microsoft.
Our existing system uses App Services with API controllers.
This is not a good setup because our scaling support is poor, its basically all or nothing
I am looking at changing over to use Azure Functions
So effectively each method in a controller would become a new function
Lets say that we have a taxi booking system
So we have the following
Taxis
GetTaxis
GetTaxiDrivers
Drivers
GetDrivers
GetDriversAvailableNow
In the app service approach we would simply have a TaxiController and DriverController with the the methods as routes
How can I achieve the same thing with Azure Functions?
Ideally, I would have 2 function apps - Taxis and Drivers with functions inside for each
The problem with that approach is that 2 function apps means 2 config settings, and if that is expanded throughout the system its far too big a change to make right now
Some of our routes are already quite long so I cant really add the "controller" name to my function name because I will exceed the 32 character limit
Has anyone had similar issues migrating from App Services to Azure Functions>
Paul
The problem with that approach is that 2 function apps means 2 config
settings, and if that is expanded throughout the system its far too
big a change to make right now
This is why application setting is part of the release process. You should compile once, deploy as many times you want and to different environments using the same binaries from the compiling process. If you're not there yet, I strongly recommend you start by automating the CI/CD pipeline.
Now answering your question, the proper way (IMHO) is to decouple taxis and drivers. When requested a taxi, your controller should add a message to a Queue, which will have an Azure Function listening to it, and it get triggered automatically to dequeue / process what needs to be processed.
Advantages:
Your controller response time will get faster as it will pass the processing to another process
The more messages in the queue / more instances of the function to consume, so it will scale only when needed.
Http Requests (from one controller to another) is not reliable (unless you implement properly a circuit breaker and a retry policy. With the proposed architecture, if something goes wrong, the message will remain in the queue or it won't get completed by the Azure function and will return to the queue.
I have an Azure function with ServiceBusTrigger which will post the message content to a webservice behind an Azure API Manager. In some cases the load of the (3rd party) webserver backend is too high and it collapses returning error 500.
I'm looking for a proper way to implement circuit breaker here.
I've considered the following:
Disable the azure function, but it might result in data loss due to multiple messages in memory (serviceBus.prefetchCount)
Implement API Manager with rate-limit policy, but this seems counter productive as it runs fine in most cases
Re-architecting the 3rd party webservice is out of scope :)
Set the queue to ReceiveDisabled, this is the preferred solution, but it results in my InputBinding throwing a huge amount of MessagingEntityDisabledExceptions which I'm (so far) unable to catch and handle myself. I've checked the docs for host.json, ServiceBusTrigger and the Run parameters but was unable to find a useful setting there.
Keep some sort of responsecode resultset and increase retry time, not ideal in a serverless scenario with multiple parallel functions.
Let API manager map 500 errors to 429 and reschedule those later, will probably work but since we send a lot of messages it will hammer the service for some time. In addition it's hard to distinguish between a temporary 500 error or a consecutive one.
Note that this question is not about deciding whether or not to trigger the circuitbreaker, merely to handle the appropriate action afterwards.
Additional info
Azure functionsV2, dotnet core 3.1 run in consumption plan
API Manager runs Basic SKU
Service Bus runs in premium tier
Messagecount: 300.000
The scaling documentation for Azure Functions is a bit light on details for how Azure Functions decide when to add more instances of an app.
Say for example I have a function that is triggered by a Github webhook. 10,000 people simultaneously commit to the Github repo (with no merge conflicts ;) ), and Github calls my function 10,000 times in a very short period of time.
What can I expect to happen? Specifically,
Will Azure Functions throttle the webhook calls? i.e., will Azure Functions reject certain function calls if my function app is under high load?
Does Azure Functions queue the requests somehow? If so, where/how?
How many instances of my function app will Azure Functions create in this scenario? One for each request (i.e., 10,000), and each will run in parallel?
If my app function was scaled down to zero instances, because there was no load on it, could I expect to see some "warm-up time" before the first function is executed? Roughly how long?
Azure Functions won't reject a webhook call, but in the case of sudden, extreme load, some requests may timeout. For web apis, please include retry on the client, as a best practice.
They aren't queued in any persistent place. They are (implementation detail) managed by IIS.
(Implementation detail) Number of instances isn't a hard set thing. We have certain, unpublished protections in place, but we're designed to scale quite far. Your requests will be handled by multiple instances.
Yes. Right now, it's pretty hefty (seconds), but we'll be working to improve it. For perf sensitive situations, a canary or a timer trigger to keep it awake is recommended.
I'm from the Azure Functions team. The things I marked as implementation details aren't promises and will likely also change as we evolve our service; just an attempt at transparency.
tested today. it took more than seconds :(
ACTUAL PERFORMANCE
--------------
ClientConnected: 13:58:41.589
ClientBeginRequest: 13:58:41.592
GotRequestHeaders: 13:58:41.592
ClientDoneRequest: 13:58:41.592
Determine Gateway: 0ms
DNS Lookup: 65ms
TCP/IP Connect: 40ms
HTTPS Handshake: 114ms
ServerConnected: 13:58:41.703
FiddlerBeginRequest: 13:58:41.816
ServerGotRequest: 13:58:41.817
ServerBeginResponse: 14:00:36.790
GotResponseHeaders: 14:00:36.790
ServerDoneResponse: 14:00:36.790
ClientBeginResponse: 14:00:36.790
ClientDoneResponse: 14:00:36.790
Overall Elapsed: **0:01:55.198**
We're evaluating using the toobusy module https://github.com/lloyd/node-toobusy on an app hosted on Heroku. I am not sure what an appropriate value for maxLag would be for Heroku environment. It seems like it would need a fair amount of playing around and tweaking to tune it? Anyone use this module in production and with what kind of setup (ie. dynos) and with what params?
Thanks!
I recently started running a small auto-complete RESTful service on heroku.
It serves lots of requests for each user (request is sent on each character the user types).
This service is running on two x1 dynos.
I need it to keep responding fast under load, so I'm also using toobusy. At first I've set it to max lag of 10ms but that was an ambitious goal - it denied many requests when I ran a load test.
After some tweaking - I've ended up with max lag of 40ms. It gave me a good balance between the load (amount of requests service needs to handle) and the desired response time (before denying requests).
I'm monitoring my app for denied requests due to load, so I'm able to add more dynos when needed.
I believe you'll have to play with this value and run load tests to get to the right number as it's very specific to the hardware (in your case Heroku) and what your app is doing for each request.