I'm interested in deploying CPU intensive web app to an Azure App Service instance. I can't find any details around CPU usage and/or limits for Azure app service. My concern is that not having insight into the CPU specs/limitations for my app will not allow me to plan on how to accurately plan the physical cloud-based infrastructure (using Azure app service).
My app will be using the OpenCV computer vision library to do heavy image processing, face detection, and face recognition with hundreds/thousands of high quality images. This is naturally a CPU-intensive process. In a traditional setting (or on-premise Virtual Machine setup), I would at least know the specs on the machine (I.E. cpu specs, etc).
In summary, my question is two-fold:
1) Why doesn't azure app service say anything about the CPUs inside of their PaaS (App Service) context? If they do, where can i learn more about CPU limitations for this?
2) In the context of my application, is my CPU-based question irrelevant? I do read online that certain Azure App Service tiers do auto-scaling (meaning load balancing across more servers for better performance). Will this be sufficient for my need where multiple end-users are processing many photos to do face detection and recognition?
Microsoft represent the performance of the a VM in terms of ACU (https://learn.microsoft.com/en-us/azure/virtual-machines/windows/acu). There are limited number of VM's Available in Azure App Service plan.
App Service plan has both scale up and scale out option. Scale out can be done based on the different rules.
But always do remember that the application architecture will dictate how it will use the scale out option.
Note : I would suggest to use VM if it GPU or CPU intensive, as you will get more option.
As i know standard app service are running on A Series VM but based on the scenario that you explained i suggest you to go with Premium App Service Plan that runs on Dv2 VM's. Hope below article will help you out:
I Suggest you to check the app service overview link and it says what kind of VM is running on back end so you can cross check with the VM specs and you can find the CPU details there.
App Service Plan Overview
App Service Limitation
App Service Overview
Related
We had a legacy monolith website application that is hosted on Azure windows server and had 10 customers using it, now as the application data grows the bandwidth of the application is affecting each customer because they were hosted in single server as a single website. Now the client wants to split the database as per customer separately to reduce the database load, so we divided the databases as per customer.
Regarding the website, we still had a dilemma on how to proceed, so we already divide the databases so we are thinking as
it is better to host each customer website on separate servers?
create a different website on a single server for each and every customer?.
Because the clients want this to be scalable and 100%, that one client’s activities and usage will not affect another, as well as be able to easily distinguish cost.
The client also asked to differentiate how much cost occurring for each customer on the resource groups,
previously we had a shared resource group.
Could anyone suggest how to solve this problem?
If your requirement fits you could leverage Azure App Service WebApps (PAAS solution).
You can host apps in the same App Service Plan or isolate your app into new App Service plan (as per your requirement) by having tradeoff between level-of control and costs.
Or to have greater control on the underlying VMs you could leverage Azure VMs (IAAS solution).
To start with, kindly take a look at this approach - Common web application architectures – monolithic application design using Azure App Service.
You could create the web application as separate App Service apps. This design lets you run them in separate App Service plans so they can be scaled independently. If you don't need that level of scalability initially, you can deploy the apps into the same plan and move them into separate plans later if necessary.
The pricing tier of an App Service plan determines what App Service features you get and how much you pay for the plan.
Azure App Service plan overview
App Service plans pricing
Azure offers a number of ways to host your application code.
Kindly checkout this architecture guide on compute decision choice
Resource Group is a just a container that holds related resources for an Azure solution. The resource group can include all the resources for the solution, or only those resources that you want to manage as a group. It doesn't have direct cost implications, but the resources/services (in this case App Service) under it does.
You may wish to know:
Explore and analyze costs with cost analysis
Prevent unexpected charges with Azure billing and cost management
Does Azure charge only for the utilization of App service plan resources or for the number of app services we create under that App service plan? Does the number of app services created under a app service plan effects cost?
I am developing a microservices project and I am unsure of whether to deploy each microservice in a dedicated app service or deploying all in one app service as virtual directories. Cost is a concern for our project.
Thanks.
Does Azure charge only for the utilization of App service plan resources or for the number of app services we create under that App service plan?
Ignoring the Free and Shared tiers, you'll pay only for the App Service Plan (cost per selected machine size x number of instances). You'll pay the same whether you have 0 or 50 Apps on the Service plan (although any other I/O, Storage etc consumed by those Apps will be additional).
(Whereas the free tier allows a max of 10 Apps, and the Shared tier allows 100 Apps)
In theory you can then add as many App Services (apps, e.g. Web Apps, Services, Function Apps etc) as you like on each App Service Plan, however in practice you'll be limited by the overall resources of the VM size and plan you've selected (e.g. 10GB Disk space on Basic, and a B1 only has 1.75GB RAM).
From the Microsoft docs, the recommendation is:
Isolate your app into a new App Service plan when:
The app is resource-intensive.
You want to scale the app independently from the other apps in the existing plan.
The app needs resource in a different geographical region.
I would also add the opinion:
If applicable, keep your environments (Dev, UAT, Prod) isolated, either at App Service Plan level, or consider isolation at Resource Group or Subscription level.
Unless your apps are maxing out CPU usage, while installing as many apps per Service Plan as makes logical sense, but monitor performance and the resource usage on the VM instances as you go.
In my situation, I've typically found that RAM to be the bottleneck, so I would typically try to scale up to a VM size with more RAM to host more Apps before separating out the Apps and adding more Service Plans.
If you are on .Net Core or another stack which doesn't need Windows, I would recommend looking into the Linux Service Plans - they are considerably cheaper than Windows instances. One caveat - as at present, there's a weird limitation which doesn't allow mixing of Windows and Linux Service Plans in the same resource group.
Each App is logically fairly well isolated on the Service Plan instances, so you can add, delete, and deploy apps without interfering with the others.
Although Docker containers can be deployed as an App Service, you might find AKS a better fit.
And More Detail
The terminology around the Azure Managed App Service Plans is somewhat confusing, but to clarify:
An App Service Plan (Service Plan) can have 1 or more managed VM instances
e.g. 1 Service Plan scaled to 3 Instances = 3 VMs to pay for.
Ignoring the Free / Shared tier (on the shared tier you pay for each App), and also ignoring the Isolated tier, you'll pay a fixed monthly cost for each Instance
You can add multiple Apps to each App Service Plan - e.g. Web Apps, Function Apps, Misc. Console Apps, and Docker images. These will be deployed to all instances in the plan.
On the Standard tier and above, you can also configure Deployment Slots on your Apps, which provides the ability to smoke-test and provide continued uptime during deployments, especially in your production environment.
App Service Plans (microsoft.web/serverfarms) account for approximately 40% of our overall Monthly Azure costs
This cost can quickly multiply, especially if you are running multiple isolated environments (Dev, UAT, Prod etc) and if you need to scale out to more than one instance per environment for redundancy or scale reasons.
As at time of writing, indicative VM instance costs on US East are approximately
Dev B1 1.75GB RAM are ~$15pm Linux / ~$50pm Windows
Prod P1V2 3.5GB RAM are ~$80 Linux / ~$150pm Windows
So it's only natural to try and minimize costs by deploying multiple apps to a single VM, especially in a fine-grained Microservice enterprise or system.
I would add to this that if you have an app that is memory intensive, I would definitely isolate it to its own App Service Plan. Since usage limits are at the plan level, you don't want to get errors for mission critical apps due to a runaway app or an app experiencing higher traffic. Another good tip is to set up auto scaling with rules you define by your needs, this will prevent downtime if higher traffic than what the plan allocates is experienced.
Though yes, money can definitely be saved by grouping apps together in the same plan.
Yes, you can save cost by hosting multiple apps in one app service plan. You do not need a separate web app plan for each web app.
Generally the price you pay is for the app service plan and not the web app (Exception here is the shared plan) so your costs do not increase as you add more applications to the same plan.
I am concerned about the load performance of my Chat bot deployed in Chat bot service.
If for my Bots in production, there is sudden load of huge number of users chatting simultaneously, will my Bot handle that load.
Do I need to consider special criteria for auto scaling different than app service
As we know that Bot Service provides two hosting plans for your bots: App Service plan and Consumption plan.
And Consumption plan scales automatically, even during periods of high load.
Besides, if you host your bot application with an specified App Service plan on Azure web app and you configured autoscaling for the plan, then your bot application and other apps in that plan are scaled out together based on the autoscale settings.
As Fei Han mentioned above, Azure functions provides two option based on scaling and hosting capabilities: App Service plan and Consumption plan.
This article provides guidance to improve the performance and reliability of your serverless function apps.
The Consumption plan automatically allocates compute power when your code is running, scales out as necessary to handle load, and then scales down when code is not running. You don't have to pay for idle VMs and don't have to reserve capacity in advance.
With an App Service plan, you can manually scale out by adding more VM instances, or you can enable autoscale. And the other reason to consider this is, they support Linux.
You can decide by comparing both based on your business requirements. Hope this helps!!
I have B3 service plan with 7GB RAM and 3 app services into a resource group. One service requires over 4GB but it throws out of memory exception after 2.4GB usage. It looks like available memory is divided between 3 services evenly. How can I manage RAM usage?
One way I can think of would be to put the apps on separate app service plans. One of your apps requires quite a lot, so why not give it its own plan?
Then you would have one Basic 3 service plan for that app, and maybe a Basic 1 plan for the other 2 if that is enough for them?
Yes, you are correct. The RAM listed for each instance size based on the pricing tier that you choose is for the underlying VM. So, this includes the OS and various infrastructure processes, in addition to IIS and your Web Apps. It is also shared with the App Services deployed under the same App Service plan.
This issue could be related to your web application, you may try the following:
View the memory utilization in Azure new portal
(http://portal.azure.com).
Use kudu Diagnostic Dump to see the information of memory
consumption.
Move the Web App to another App Service plan that has only one Web
App.
I would suggest you refer the blog post How to view the memory utilization of your Azure Web Site for more details.
This is my azure payasyougo usage cost for this month.
I'm struggling to understand why I would be charged for a Standard Medium App Service, I would of thought that it would be included in the compute hours? I have only one Cloud Service running and this seems a bit steep for a cloud service that is not doing much...
Any suggestions?
While pricing is off-topic, I think I can answer this from a general operational angle (even though this will likely be closed since it's not programming-related).
As your graphic shows, you are consuming resources for different services. Compute-hours equates to your virtual machines that you've deployed, and you're consuming those resources whether you're using 0% or 100% CPU / memory / network, whether you've deployed code or not. They are allocated and, as far as Azure is concerned, deployed for your use, no matter what you're doing (or not doing) with them.
When you created your App Service, that was yet-another set of resources deployed. And another set of resource-hours you're consuming (again, whether you use 0% or 100% is irrelevant).
Same thing would happen if you created a database instance or any other Azure service: You'd pay in whatever way is described for that particular service. And each service has its own specific cost which is described in detail in Azure's pricing page.
There's no nesting of separate services. In your specific case: there's no concept of creating an App Service inside a Virtual Machine (nor is there any hint of that anywhere). They are two separate services.
Computer covers only Virtual Machines and Cloud Services. Pricing can be found here:
https://azure.microsoft.com/en-us/pricing/details/virtual-machines/
App Services are "special", while they internally use compute resources behind the scenes, they are charged based on the tier of performance and SLA you want to achieve. Pricing for them can be found here:
https://azure.microsoft.com/en-us/pricing/details/app-service/
You will notice that there is a PREMIUM price for the same level of service on App Services. The theory is that the App Service stack is providing more managed value and thus worth more. For my use cases I have not found this to be the case and instead choose to run our environments under the PaaS VM / Cloud Service stacks.