Monitoring the performance of big data repositories is an important part of monitoring the performance. It is not only important to monitor the big data repository, but to also monitor the applications that are querying the repository. Those applications are the direct clients that can be responsible for creating a performance issue and that certainly rely on the repository to perform well when queried. You can first discover a problem with the data repository in the application viewpoint that is actually impacting the performance and/or functionality of the application.
Big Data Monitoring
Now, how do we monitor Big Data in the real world?
End to end flow – Track all of the app transactions across application tiers and analyze their response times. It’s easy to identify exactly which components are experiencing problems with this information.
Code-level details – Once you’ve identified a performance problem in your big data application the next step is to understand what portion of the code is responsible for the problem. AppDynamics provides deep code diagnostics and is capable of showing you the call stack of your problematic transactions.
Back end processing – Tracing transactions from the end-user, through the application tier, and into the backend repository is required to properly identify and isolate performance problems.
Big data metrics – Every company has it’s own set of relevant KPIs but the important part is to understand what is normal behavior and good performance, once you have this information you can identify when KPIs are deviating from normal behaviors. This, combined with the end to end transaction tracking, will tell you if there is a problem, where the problem is and the root cause.
Big data deep dive – Sometimes KPIs aren’t enough to help solve your big data performance issues. That’s when you need to pull out the big guns and use a deep dive tool to assist with troubleshooting. Deep dive tools will be very detailed and very specific to the big data repository type that you are using/monitoring.
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Big Data Monitoring
"The term “Big Data” is quite possibly one of the most difficult IT-related terms to pin down ever. There are so many potential types of, and applications for Big Data that it can be a bit daunting to consider all of the possibilities..."