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In the Cloud, you have to trust your instruments...

Michael Kopp

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Top Stories by Michael Kopp

Anyone who ever monitored or analyzed an application uses or has used averages. They are simple to understand and calculate. We tend to ignore just how wrong the picture is that averages paint of the world. To emphasis the point let me give you a real-world example outside of the performance space that I read recently in a newspaper. The article was explaining that the average salary in a certain region in Europe was 1900 Euro's (to be clear this would be quite good in that region!). However when looking closer they found out that the majority, namely 9 out of 10 people, only earned around 1000 Euros and one would earn 10.000 (I over simplified this of course, but you get the idea). If you do the math you will see that the average of this is indeed 1900, but we can all agree that this does not represent the "average" salary as we would use the word in day to day li... (more)

A Discussion on Top Performance Problems for Hadoop and Cassandra

In the last couple of weeks my colleagues and I attended the Hadoop and Cassandra Summits in the San Francisco Bay Area. It was rewarding to talk to so many experienced Big Data technologists in such a short time frame - thanks to our partners DataStax and Hortonworks for hosting these great events. It was also great to see that performance is becoming an important topic in the community at large. We got a lot of feedback on typical Big Data performance issues and were surprised by the performance related challenges that were discussed. The practitioners here were definitely no n... (more)

Application Performance Monitoring in Production

Last time I explained logical and organizational prerequisites to a successful production level application performance monitoring. I originally wanted to look at the concrete metrics we need on every tier, but was asked how you can correlate data in a distributed environment, so this will be the first thing that we look into. So let’s take a look at the technical prerequisites of successful production monitoring. Collecting data from distributed environment The first problem that we have is the distributed nature of most applications. In order to isolate response time problems or... (more)

Eating Our Own Dog Food – 2x Faster Hadoop MapReduce Jobs

For a while now I have been writing about how to analyze and optimize Hadoop jobs beyond just tweaking MapReduce options. The other day I took a look at some of our Outage Analyzer Hadoop jobs and put words into action. A simple analysis of the Outage Analyzer jobs with Compuware APM 5.5 identified three hotspots and two potential Hadoop problems in one of our biggest jobs. It took the responsible developer a couple of hours to fix it and the result is a 2x improvement overall and a 6x improvement on the Reduce part of the job. Let's see how we achieved that. About Outage Analyze... (more)

Why Perfomance Management Is Easier in Public than On-Premise Clouds

Performance is one of the major concerns in the cloud. But the question should not really be whether or not the cloud performs, but whether the Application in question can and does perform in the cloud. The main problem here is that application performance is either not managed at all or managed incorrectly and therefore this question often remains unanswered. Now granted, performance management in cloud environments is harder than in physical ones, but it can be argued that it is easier in public clouds than in on-premise clouds or even a large virtualized environment. How do I ... (more)