Reactive Microservices Architecture and Runtime Statistics & Metrics

posted May 2, 2015, 5:48 PM by Rick Hightower   [ updated May 2, 2015, 5:49 PM ]
Microservices Architecture Statistics and Metrics
With big data, data science, and microservices, runtime stats are required to understand how users use the app. You must know your users.


Runtime statistics and metrics are important for distributed systems. Since microservices architecture tend to promote and encourage remote process communication, they are inherently distributed systems. Runtime statistics and metrics can include request per second, available system memory, number of threads being used, connections that are open, failed authentication, expired tokens, and their ilk. If there is a parameter that is important to you, then you will want to track it. Given the complications of debugging a distributed system, you will find that runtime statistics of important parameters are a godsend.

Microservices Architecture Statistics

This is even more the case if you're dealing with a lot of message queues. It can be difficult to determine where a message stopped being processed, and runtime statistics can help you track down issues.

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