I have one big task to do every day, with no need to scale, that takes about 30 minutes and is DB, processor and memory intensive.
This means actual 16h/month of computation time.
WebJobs require constantly running WebSite 744h/month
WebRole is also constantly running 744h/month
Azure Batch - suited for scaled storage input - storage output
processing (or that is how I understand it)
Stopped cloud service still cost you. Setting instance count to 0 is not available. And paying for 728h/month unused computation time looks like madness. Only thing I can imagine is automatic deployment of cloud service every day and automatic deletion of deployment once task is finished, but this also looks like madness.
Are there any options for this scenario in Azure?
Cloud service will be charged continuously until the deployment is deleted. Yes you can delete it every day and redeploy...
Azure VMs in Stopped (Deallocated) status, does not incur any charge. You can shut them down in portal or by script when you don't need them.
I think there is a large difference in billing if you only use it 62h/month. Would you consider switch this deployment to VM? WorkerRole and VMs can be placed on the same subnet, they can still connect to each other.
Related
Question regarding pricing tiers for Azure Sql database and if the cheapest plan ($4.90/month) offloads resources after a specific time period for non use.
If my Azure Sql Server database doesn't get queried for a specific period of time, ex. 30 minutes. Will Azure offload the resources for the database, until it gets a new request?
This would be similar to an app service running the basic (free) plan. After ~30 minutes the site resources get offloaded from memory (I think). So, when I go to the site, instead of loading up immediately, it takes about 5-10 seconds, then if I hit the site again, because it's loaded back into memory, it will load immediately.
Does this same thing happen with Sql Server running in Azure with the cheap $4.90/month plan? It seems like it does! If I don't hit my app service (website), now upgraded to the S1 plan so no offloading, and come back a day later and hit a page that has to fetch database results to display on the page, it will take approx. 5-10 seconds, but then if I refresh the page again or hit another page that needs to query the DB, the queried data comes back instantly!
No it should not do that. You reserve capacity in vCores or DTUs, and that is what you should get. But different management operations (like maintenance, capacity restructuring, moving workloads from faulty hardware) will evict your workload from the underlying host it is running on and spin it up on another hardware. It would be transparent to you if not for the flushed cache. Of course this should not happen every time your application goes idle, but can be the case from time to time.
If you are using DTU purchasing model, I would recommend switching to vCore based model as it's the recommended one. Then take a look at the CPU Used metric. As long as the line of the metric is continuous you have allocated CPU, when the line becomes dotted it indicates that the db is paused, but the dotted behavior should only apply for serverless.
You can set your Azure SQL Database as serverless. It is the only Azure SQL Database (PaaS) option that can be auto-paused after a specific time of inactivity has passed, the minimum time of inactivity is 1 hour. You also get billed by the minute instead of by the hour. Here you will find step-by-step tutorial how you create a serverless database.
Make sure you set the auto-pause delay setting.
I am using Azure Functions on the App Service Plan. My understanding is for every new execution the Azure Function will create a new App Service, execute the function and then shut down the App Service. There would be nothing shared between the multiple App Services that are spawned due to multiple requests.
However when I do test my Function(which is a video processing one), for one request the time it takes is around 2-3 mins however for multiple simultaneous requests the time increases to 10-15 mins. My questions are whether my understanding above is correct? If not then what resource is shared amongst these App Services? How should I decide my scaling options(manual vs auto)?
"My understanding is for every new execution the Azure Function will create a new App Service" Nope it will not run new instance each time. Generally if there is no load on AF it will stop all instances.
Then if first request/event comes in it will start first instance. This is why we have ColdStart in Serverless. After that scale controller will measure your instance performance memory and CPU consumption and decide if it needs to scale but it wont be instant. So if lets say you sent N amount of requests to do smth with video they could go to same first instance and increase load. Then AF will scale, because of CPU spike but it wont help with old requests since they are handled at first instance. Keep in mind For non-HTTP triggers, new instances are allocated, at most, once every 30 seconds which means that your AF should have CPU spike for at least 30 second to add new instance https://learn.microsoft.com/en-us/azure/azure-functions/event-driven-scaling
I am not sure if Azure Functions are good option for video processing. Azure function should be used for quick stuff usually I would say not more than 30 sec. But there are some limitation of execution time depends how you run it https://learn.microsoft.com/en-us/azure/azure-functions/functions-premium-plan?tabs=portal
Not sure what type of video processing you doing but i would have a look into Azure Media Services
The other options as you mentioned is Batch jobs with low priority https://azure.microsoft.com/en-au/blog/announcing-public-preview-of-azure-batch-low-priority-vms/ it actually a good use case you have: Media processing and transcoding, rendering and so on
A small addition to Vova's answer: if you're running your Function in an App Service (also known as a Dedicated Plan), it will by default only scale instances within the possibilities of the App Service Plan you defined. This means that all of the instances of your Function App run on the same virtual machine. That is most probably the reason you're seeing increasing request times with more requests.
If you want your Functions to scale beyond the capabilities of that plan, you will need to manually scale or enable autoscaling for the App Service plan.
An App Service plan defines a set of compute resources for an app to run. These compute resources are analogous to the server farm in conventional hosting.
and
Using an App Service plan, you can manually scale out by adding more VM instances. You can also enable autoscale, though autoscale will be slower than the elastic scale of the Premium plan. [...] You can also scale up by choosing a different App Service plan.
If you run your Function App on Consumption Plan (the true serverless hosting plan option since it enables scaling to zero),
The Consumption plan scales automatically, even during periods of high load.
In case you need longer execution times than those available in Consumption Plan, but the App Service Plan doesn't seem to be the best hosting environment for your Functions there's also the Premium Plan.
The Azure Functions Elastic Premium plan is a dynamic scale hosting option for function apps.
Premium plan hosting provides the following benefits to your functions:
Avoid cold starts with perpetually warm instances
Virtual network connectivity.
Unlimited execution duration, with 60 minutes guaranteed.
Premium instance sizes: one core, two core, and four core instances.
More predictable pricing, compared with the Consumption plan.
High-density app allocation for plans with multiple function apps.
More info on all the different Azure Functions hosting options.
I have a .NET Core application currently running as an Azure App Service, and I need it to do a lot of 'work' only about a few times a day. In order to save on the hourly billing, this is the solution I developed:
Using a runbook (Azure Automation): scale the App Service Plan to the 'Free' tier at 7:00 PM
Using a runbook (Azure Automation): scale the App Service Plan back up to the premium tier at 8:00 AM
Hard-code my .NET Core application to ensure it only does the heavy 'work' between 8:00 AM and 7:00 PM
This is fine as it saves me a significant portion of cost, as I'm only paying for the hours in which the App Service Plan is scaled up to the premium tier. However it is definitely not ideal.
My question is - what design pattern should I implement in order to accomplish what I'm trying to do? I need a lot of compute resources but only for a few hours out of the day. I know AWS has 'spot' instances that you can configure - is there a similar mechanism in Azure?
Ideally I could implement a solution that involves me only paying for those heavy compute resources when I actually need it (e.g.: a few times a day, while the sun is up)
Thank you for any insight and help!
EDIT in regards to the type of computation, my summary is essentially a few ML.NET trainers running in parallel with some moderate Elasticsearch document writing
It is pretty tough to answer this with the whole description of your workload being a "lot" of "heavy compute".
If you can put your "compute" into Azure Functions, going serverless with a consumption plan will probably be the nicest solution. However, individual function executions have a given timeout, so you need to see if your app fits the bill.
As an alternative, you can put your application into an Azure Container Instance, and spin that up on demand.
If you have REALLY high workload, you can use Azure Batch. If your current workload can be done on an AppService plan, this may be "overkill".
The equivalent to AWS spot instances is called Azure Spot Virtual Machines. You can also use them with Azure Batch.
Yes, you can switch to Serverless. Host front end on Storage Accounts and back end move to Azure Functions (Consumption Plan).
PS: If it's a long running processing, it may not be the best solution unless you use Durable Functions.
Ok Azure Experts,
I have a task that only needs to run once every week - this is a long
running task that can take 2-3 days to run.
I have set up a worker role to scale based on a queue. On the day
that we want the task to start - we populate the queue (using a Web
Job).
During the rest of the time, when the queue is empty, I want the
worker roles to shut down - but I cannot scale down to 0 instances.
Originally, we wanted to do this with a Web Job, but the website shuts down from time to time - abruptly turning off my webjob - is this supposed to happen? Even with Keep-Alive turned on? Also, you cannot stop a triggered Web Job from running - so if we want the process to stop - we need to turn off the Web site - not ideal.
How do I scale my instances down to zero?
* Alternatives solutions are also welcome.
Trying to minimize cost here - why pay for a worker role that isn't doing anything?
It is not possible to scale-down a Worker Role to 0 instances at this time. Even if you STOP the worker role, you're still incurring charges for STOPPED instances.
However, behavior that you're looking for, is possible with Virtual Machines. If you shutdown (STOP & DEALLOCATE) a virtual machine, you're not paying fees for that machine.
Now, the only challenge is to stop/start the VM based on a queue count. I don't recall if Azure portal's native scaling supports scaling down to 0 instances for VMs. However, if you use AzureWatch, you should be able to get this done without any issues. Disclaimer: I am affiliated with AzureWatch.
HTH
Can anybody explain the difference between Azure Web Jobs and Azure Scheduler
Azure Web Jobs
Only available on Azure Websites
It is used to run code at particular intervals. E.g. a console application every day
Used to trigger and run workloads.
Mainly recommended for workloads that either scale with the website or are relatively small.
Can be persistently running if "Always On" selected, otherwise you will get the 20 min timeout.
The code that needs to be run and schedule are defined together.
Azure Scheduler
Is not tied to Websites or Cloud Services
It allows you to call a website or add a message to a storage queue
Used for triggering events or triggering small workloads (e.g. add to queue), usually to trigger larger workloads
Mainly recommended for triggering more complex workloads.
This is only a trigger, and a separate function listening to trigger events (e.g. queue's) needs to be coded separately.
For many instances I prefer to use the scheduler to push to a storage queue and a worker role on each instance takes off the queue. This keeps tasks controlled granularly and can also move up or down in scale outside of your website.
With WebJobs they scale up and down with your site and hence your background tasks can become over taxed if your website is experiencing low traffic and scaled down.
Azure Scheduler - Provides a way to easily schedule http calls in a well-defined schedule, like every hour, every Friday at 9:00 am, Once a day, ...
Azure WebJobs - Provides a way to run small to medium work load (in the form of a script: .exe, .cmd, .sh, .js, ...) at the same context of an Azure Website (but can be hosted even with an empty website).
While a WebJob can run continuously (with a process that has a while loop) and Azure will make sure this WebJob is always running (with "Always On" set).
There is also an integration between Azure scheduler and Azure WebJobs where you have a WebJob that is running some finite work and the schduler is responsible for scheduling this work (invoking the WebJob).
So in summary, the scheduler is about scheduling work and WebJobs is about running work load.