Skip to main content

SQL Azure - Improve restoring time of BACPAC during load tests

SQL Azure is a great service when you need a location to store a relational database and you don't want to manage the infrastructure that is behind it. In only a few minutes, you can get a powerful database ready for your needs.

In almost all projects life cycles, there is a moment in time when need to run one or more Load Tests. For each scenario, you may need a different database setup.
In the above example, we have 3 different scenarios that we want to test. This means that, we need to load 3 different bacpac files. If the database is relatively small (10MB) than we will not have any kind of problems.
But with a large database, the restoring process can take some time. Behind the scene, a database restoring process is complex and CPU intensive, because of this it will require time and CPU.
This will not be a problem for a database of type P1 or P2, where the restoring process is fast. But, for a S0 or S1, we may need to wait for even a few hours, until our backup is restored and our database is ready to run another load test scenario.

What we could do in this case? What we can do to reduce the waiting time between Load Tests?
Better databases
One possible solution would be to upgrade our database to a better one. Unfortunately this is not a solution. When you run a load test you want to run with the same configuration like in production. Running with a better database may affect your load tests results.

Different databases
Another solution is to prepare multiple databases, with different configuration. In this way you can have for each scenario a different database instance. From your application you could specify what database you want to use.
This could work for small/medium solutions. But this could increase the load test setup if your system use 15 different databases for example. Also, the costs of running the load tests may be impacted.

Better databases only when we restore a bacpac
Using this approach, we would run the load test with the database type that we want. Only during the load test setup, we would upgrade our database instance to a better type. In this way we can minimize the time that is needed to restore a specific bacpac and we would also reduce the costs of the load tests.

 
It is important to know that changing the type of a database takes only a few minutes. In this way we can easily play with different types.

In conclusion we could say that the best approach in this situation is to use the same database, but to change the type of the database when a database restore is done. This would allow us to keep the time and the costs to minimal and well-balanced.

Comments

Popular posts from this blog

Windows Docker Containers can make WIN32 API calls, use COM and ASP.NET WebForms

After the last post , I received two interesting questions related to Docker and Windows. People were interested if we do Win32 API calls from a Docker container and if there is support for COM. WIN32 Support To test calls to WIN32 API, let’s try to populate SYSTEM_INFO class. [StructLayout(LayoutKind.Sequential)] public struct SYSTEM_INFO { public uint dwOemId; public uint dwPageSize; public uint lpMinimumApplicationAddress; public uint lpMaximumApplicationAddress; public uint dwActiveProcessorMask; public uint dwNumberOfProcessors; public uint dwProcessorType; public uint dwAllocationGranularity; public uint dwProcessorLevel; public uint dwProcessorRevision; } ... [DllImport("kernel32")] static extern void GetSystemInfo(ref SYSTEM_INFO pSI); ... SYSTEM_INFO pSI = new SYSTEM_INFO(

Azure AD and AWS Cognito side-by-side

In the last few weeks, I was involved in multiple opportunities on Microsoft Azure and Amazon, where we had to analyse AWS Cognito, Azure AD and other solutions that are available on the market. I decided to consolidate in one post all features and differences that I identified for both of them that we should need to take into account. Take into account that Azure AD is an identity and access management services well integrated with Microsoft stack. In comparison, AWS Cognito is just a user sign-up, sign-in and access control and nothing more. The focus is not on the main features, is more on small things that can make a difference when you want to decide where we want to store and manage our users.  This information might be useful in the future when we need to decide where we want to keep and manage our users.  Feature Azure AD (B2C, B2C) AWS Cognito Access token lifetime Default 1h – the value is configurable 1h – cannot be modified

What to do when you hit the throughput limits of Azure Storage (Blobs)

In this post we will talk about how we can detect when we hit a throughput limit of Azure Storage and what we can do in that moment. Context If we take a look on Scalability Targets of Azure Storage ( https://azure.microsoft.com/en-us/documentation/articles/storage-scalability-targets/ ) we will observe that the limits are prety high. But, based on our business logic we can end up at this limits. If you create a system that is hitted by a high number of device, you can hit easily the total number of requests rate that can be done on a Storage Account. This limits on Azure is 20.000 IOPS (entities or messages per second) where (and this is very important) the size of the request is 1KB. Normally, if you make a load tests where 20.000 clients will hit different blobs storages from the same Azure Storage Account, this limits can be reached. How we can detect this problem? From client, we can detect that this limits was reached based on the HTTP error code that is returned by HTTP