yCrash Demo video

yCrash app is a non-intrusive, secure, instant root cause analysis tool. It captures thread dump, heap dump, GC log, netstat, vmstat, top, and several more artifacts, right when the problem is happening in the production. It instantly analyzes all the artifacts & generates a root cause analysis report in the dashboard. Watch this below video clip to get a detailed overview of yCrash!

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Detect proactively whether application’s memory is under-allocated

 When the application’s memory is under-allocated, it will result in the following side-effects: 

 a. Transactions response time will degrade

 b. CPU consumption will spike up

 c. OutOfMemoryError will be thrown

Only when OutOfMemoryError is thrown, most of us start to look at our application’s memory settings. This is like only when a patient goes to a critical condition; we begin to give treatment :-). 

In this post, let’s discuss how to detect whether your application’s memory is under-allocated or not in a proactive manner.

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AWS Cloud watch vs yCrash – Monitoring vs RCA

We had an outage in our online application GCeasy on Monday morning (PST) Oct’ 11, 2021. When customers uploaded their Garbage Collection logs for analysis, the application was returning HTTP 504 error. HTTP 504 status code indicates that transactions are timing out. In this post, we would like to document our journey to identify the root cause of the problem.

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Performance impact of java.lang.System.getProperty()

‘java.lang.System.getProperty()’ is a common API used by Java developers to read the System properties that are configured during application startup time. i.e. when you pass “-DappName=buggyApp” as your application’s startup JVM argument, the value of the ‘appName’ system property can be read by invoking the ‘java.lang.System.getProperty()’. Example:

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Is today’s microservice more bloated than yesterday’s monolith?

I am slightly hesitant to write this post, as it might attract some criticism. Nevertheless, I told myself there is nothing wrong with sharing my point of view (even though it might not be well accepted). I would like to share my personal experience regarding yesterday’s Monolithic and today’s Microservice architecture in this post.

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Overhead added by Garbage Collection Logging

Enabling Garbage collection logs on your application has certain advantages. In nutshell, Garbage collection logs will facilitate you to optimize Garbage Collection pause time, improve overall application’s response time, forecast production outages, reduce computing cost. Even though Garbage collection logs have these advantages, we weren’t sure what overhead does garbage collection logging add to the application. Thus we set out to conduct the below case study.

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Overhead added by collecting thread dumps

A thread dump is a snapshot of all the threads running in a java process. It’s a vital artifact to troubleshoot various production problems such as CPU spikes, unresponsiveness in the application, poor response time, hung threads, high memory consumption. Thus to facilitate troubleshooting, we have seen enterprises capture thread dumps on a periodic basis (every 5 minute or 2 minute).So we were curious to learn the overhead of capturing thread dump on a periodic basis. Thus we set out to conduct the below case study.

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