So, what exactly does OverOps do? OverOps pinpoints the exact cause of critical exceptions in your application with the variable state for context. Armed with that information, you don’t have to waste countless hours on detective work sorting through logs or your APM to figure out what happened with your application and what precisely needs to be fixed. For example, a programmer typically sees an exception with the related stack trace like the following.
Ever create the perfect Spark application with automated tests just to have it fail when it is distributed and run on a big data set? If so then this article is for you. My name is Chris Caspanello and before I joined OverOps, I worked on Pentaho, a leading visual data transformation tool. One of its powerful features is to develop a transformation locally and then run that transformation on your big data cluster with Spark. Sounds cool, right?
Automated garbage collection (along with the JIT HotSpot Compiler) is one of the most advanced and most valued components of the JVM, but many developers and engineers are far less familiar with Garbage Collection (GC), how it works and how it impacts application performance. First, what is GC even for? Garbage collection is the memory management process for objects in the heap.
What is the ultimate alerting strategy to make sure your alerts are meaningful and not just noise? Production monitoring is critical for your application’s success, we know that. But how can you be sure that the right information is getting to the right people? Automating the monitoring process can only be effective when actionable information gets to the right person. The answer is automated alerting.