Skip to main content

How to get the instance index of a web role or worker role - Windows Azure

When we have one or more instances of a specific web role or worker role in the cloud, there are moments when we want to know from the code how many instances we have of the specific type or the index of current instance.
The total number of instances can be obtained using
RoleEnvironment.Roles[i].Value.Instance.Count
To be able to detect the index of the current instance we need to parse the id of the role instance. Usually the id of the current instance ends with the index number. Before this number we have ‘.’ character if the instance is on the cloud or ‘_’ when we are using emulator.
Because of this we will end with the following code when we need to get the index of the current instance:
int currentIndex = 0;
string instanceId = RoleEnvironment.CurrentRoleInstace.Id;
bool withSuccess = int.TryParse(instanceId.Substring(instanceId.LastIndexOf(".") + 1, out currentIndex));
if( !withSuccess )
{
  withSuccess = int.TryParse(instanceId.Substring(instanceId.LastIndexOf("_") + 1, out currentIndex));
}
Take into account that when you increase and decrease the number of instances, there are situation when you can end up with the following name of the instances:
  • […].0
  • […].1
  • […].3
  • […].4
Two is missing because when we decreased the number of instances from 5 to 4, that instance was stopped.

Comments

Post a Comment

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