Why is Azure MySQL database unresponsive at first - azure

I have recently setup an 'Azure Database for MySQL flexible server' using the burstable tier. The database is queried by a React frontend via a node.js api; which each run on their own seperate Azure app services.
I've noticed that when I come to the app first thing in the morning, there is a delay before database queries complete. The React app is clearly running when I first come to it, which is serving the html front-end with no delays, but queries to the database do not return any data for maybe 15-30 seconds, like it is warming up. After this initial slow performance though, it then runs with no delays.
The database contains about 10 records at the moment, and 5 tables, so it's tiny.
This delay could conceivably be due to some delay with the node.js server, but as the React server is running on the same type of infrastructure (an app service), configured in the same way, and is immediately available when I go to its URL, I don't think this is the issue. I also have no such delays in my dev environment which runs on my local PC.
I therefore suspect there is some delay with the database server, but I'm not sure how to troubleshoot. Before I dive down that rabbit hole though, I was wondering whether a delay when you first start querying a database (after, say, 12 hours of inactivity) is simply a characteristic of the burtsable tier on Azure?

There may be more factors affecting this (see comments from people on my original question), but my solution has been to set two global variables which cache data, improving initial load times. The following should be set to ON in the Azure config:
'innodb_buffer_pool_dump_at_shutdown'
'innodb_buffer_pool_load_at_startup'
This is explained further in the following best practices documentation: https://learn.microsoft.com/en-us/azure/mysql/single-server/concept-performance-best-practices in the section marked 'Use InnoDB buffer pool Warmup'

Related

Why is my Azure node.js app becoming unresponsive?

I recently deployed a Node.js Backend Service to Azure and have the following problem. The service becomes unresponsive after a certain amount of time, and only comes back to life if a external request is sent. The problem is, that it takes about 3 minutes for the Container to start back up and actually return the request. I'm running Node 14 LTS. I also added a health check yesterday, but azure simply doesn't bother actually keeping the app alive, here is the metric off azure
I verified azure is actually trying to reach the correct endpoint, and it does. I also have "Always On" enabled. I also verified that the app itself, is not crashing. I log every request and all of a sudden requests are no longer received, which means the health endpoint doesn't respond either, but it does not result in a container restart. It just waits for an external request to appear and then decides to start everything back up, which takes too long.
I feel like it's some kind of configuration issue, because the app itself is not very complex and I never experienced crashes when doing local development.
The official document tells us that the Free pricing tier you are currently using, Always on does not take effect.
How do I decrease the response time for the first request after idle time?

Best way to approach long running tasks (but not cpu, memory intensive) in GCP

We built a web application where we utilized firebase functions for lightweight works such as login, update profile etc. and we deployed 2 functions to App Engine with Nodejs.
Function 1: Downloading an audio/video file from firebase storage and converting it with ffmpeg and uploading converted version back to storage.
But App Engine is terminating with a signal in the middle of download process (after ~40 seconds) if the file is larger (>500MB)
Function 2: Calling Google API (ASR) and waiting response (progress %) and writing this response to firestore until it's completed (100%).
This process may take between 1 min - 20 min depending on the file length. But here we get two different problems.
Either App Engine creates a new instance in the middle of API call process and kills current instance (since we set instances# to 1) even there is no concurrent requests.
I don't understand this behavior since this should not require intensive CPU or memory usage. App Engine gives following Info in logs:
This request caused a new process to be started for your application,
and thus caused your application code to be loaded for the first time.
This request may thus take longer and use more CPU than a typical
request for your application
Or App Engine terminates due to idle_timeout even it is waiting async API response and writing it to db.
It looks like when there is no incoming requests, App Engine is considering itself as idle and terminating after a while (~10 minutes)
We are new to GCP and App Engine, so maybe we are using wrong product (e.g. Compute Engine?) or doing the wrong implementation. Also we saw PubSub, Cloud Tasks etc. which looks like a solution for our case.
Thus I wonder what could be most elegant way to approach the problem and implement solution?
Any comment, feedback is appreciated.
Regards
A. Faruk Acar
App Engine app.yaml Configuration
runtime: nodejs10
manual_scaling:
instances: 1
App Engine has a maximum timeout per request
10 minutes for App Engine Standard
60 minutes for App Engine Flex
in both cases the default values are less.
So for what you describe as your process it is not the optimal solution.
Cloud Tasks has similar limitations as App Engine so you might get to similar problems.
Compute Engine can work for you as it is virtual machines where you control the configuration. To keep it cost effective see what is the smallest computer type which can run your app.

How to find/cure source of function app throughput issues

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.

Stress testing Azure App Service periodically stops processing requests

I am currently stress testing a .Net Core application, targeting netcoreapp2.2, that is hosted on Azure as a App Service connected to a P1V2 (210 ACU, 3.5GB memory) service plan with 2 instances.
The endpoint that I'm stress testing is very simple, it validates a Oauth2.0 token, gets the user and some info about the user from a P2 (250 DTU) Azure hosted database, total 4 db queries per request, and returns the string "Pong".
When running 15 concurrent users (or more) in 200 loops I see the stop(s) in processing seen in the image (between the high peaks). The service plan never hits more than around 20-35% CPU and the database never uses more than 2% load. Increasing the users decreases the average throughput.
When looking at the slow requests it is like it just randomly stops, never at the same place. When I look at the DB requests I never see a request that takes longer than a couple of 100 milliseconds while some requests can take upwards to 5-6s to process.
It feels like I reach some limit which results in something stopping for a period of time, but I can't figure out where the problem lies.
When running the same stress locally I don't see these stops.
I'm using jmeter cli to run the stress tests against both environments.
Any help is greatly appreciated, thanks!
This could be because of Azure DDOS protection behaviour.
If your application is being attacked by a DDOS attack, Microsoft will
stop all connections to your end point and in effect taking down your
service.
To avoid this you need to setup Web application firewall (WAF) to exclude healthy requests.

what is an appropriate value for maxLag in node toobusy on Heroku?

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.

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