When building a microservice application consisting of many distributed Azure services that communicate with each other, it is vital to have a mechanism that supports observing and tracing the request flow from end to end.

Understanding this, Azure offers native tools like Application Insights to achieve distributed tracing. They help to log and track how a request flow performs through Azure services.

This article dives deep into the significance of distributed tracing, how it can be attained using Application Insights, their pros/cons, and an out-of-the-box BAM solution to get started with.

Microsoft Azure VM is a flexible cloud computing service that runs on an isolated partition of its host computer, used popularly for development and testing. Its versatility and ability to allow users to deploy applications in minutes make it an indispensable asset for most business organizations.

However, without the proper Microsoft Azure monitoring tool, servers often don't perform at maximum efficiency, resulting in unnecessary downtimes and service disruption.

The massive shift from monolithic to microservices architecture has caused a considerable demand for distributed tracing. Traditional monitoring tools were designed for monolithic applications, so they primarily provide insights into application performance rather than how a request flows through the application.

However, if you are working with a microservices architecture, it is crucial to track every user request and the path of the request flow across multiple applications.

The Service Bus Queues and Topics are enterprise-level messaging technologies offered by Microsoft Azure to make messaging between services more reliable. Anyone using them for their business should be familiar with a concept known as message dead-lettering.

Now, let's begin by discussing Service Bus dead-letter Queues, how they work, and most importantly, the top choices you should consider for monitoring the same.