The build pipeline for my blog fails every once in a while. For example, there was an issue with the Azure CLI earlier this month. Each time that happens it takes me a few minutes to remember how the pipeline works. Therefore, I am documenting it quickly in this post. Build As I described in this post, my blog is hosted on AWS, Azure and GCP. There is a GitHub Action that runs for each cloud provider .

In the prior post, I looked at what happens the first time an ASP.NET application is invoked in Lambda. When we left off, we had a roughly 3 second initial response time. ReadyToRun As I mentioned earlier, one cause of long cold start times in .NET is Just In Time (JIT) compilation. As each .NET assembly is loaded, the runtime converts the Intermediate Language (IL) into machine code for the specific platform it is running on.

The ability to host an ASP.NET project in AWS Lambda is a great way to get started with serverless. However, cold starts can result in a slow first invocation of the ASP.NET function. In this post I’ll set up a typical, albeit simple, application to gather benchmarks. In part two, I will explore a few options to speed up initialization. Background A Lambda function is fundamentally different from a traditional application.

I just published a video to YouTube showing how to use Amazon Rekognition with .NET 5 applications. Link to the recording

Performance instrumentation and monitoring for .NET applications I’ll be presenting the following session at re:Invent 2021. Are you confident you can quickly identify service problems and resolve performance issues at scale? Isolating and remediating performance problems in the cloud, particularly with modern, distributed microservice architectures, can pose unique challenges. This session shows you how to capture logs, metrics, and telemetry for .NET applications across servers, containers, serverless architectures, and related components.