Preparation for deploying API services to the cloud (continued...)
This is a continuation of the previous post.
http://ravinote.blogspot.com/2021/03/preparation-for-deploying-api-services.html
Diagnostic queries: As each layer and component of the web API server create and maintain their own data structures during their execution, it helps to query these data structures at runtime to diagnose and troubleshoot erroneous behavior. While some of the queries may be straightforward if the data structures already support some form of aggregation, others may be quite involved and include several steps. In all these cases, the queries will be against a running system in as much permitted with read-only operations.
Performance counter: Frequently subsystems and components take a long time. It is not possible to exhaust diagnostic queries to discover the scope that takes the most time to execute. On the other hand, the code is perfectly clear about call sequences, so such code blocks are easy to identify in the source. Performance counters help measure the elapsed time for the execution of these code blocks.
Statistics counter: In addition to the above-mentioned diagnostic tools, we need to perform an aggregation over the execution of certain code blocks. While performance counters measure elapsed time, these counters help with aggregation such as count, max, sum, and so on.
Among the improvements to quality starting from design with the help of hooks, monitors, APIs, and other test processes, and ranging all the way through implementation to production support diagnostics, quality can be enforced with a variety of instruments. Static code analyzers, unit-tests, simulated tests, end to end automation, regression passes, continuous integration and deployment runs, fault injections, stress testing, appearances in regional languages, and many more nuances serve as instruments to enforcing quality
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