About Michael Kopp

Michael Kopp has 10 years of experience as an architect and developer in the Java/JEE and C++. He currently works as a technology strategist and evangelist in the Compuware dynaTrace Center of Excellence. In this role he specializes in the architecture and performance of large scale production deployments. As part of the R&D team he influences the dynaTrace product strategy and works closely with key customers in implementing performance management solution for the entire lifecylce. Before joining Compuware he was the Chief Architect at GoldenSource, a major player in the EDM space. In this role one special focus has always been performance and scalability of their enterprise offerings.

Speeding up a Pig+HBase MapReduce job by a factor of 15

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The other day I ran a Pig script. Nothing fancy; I loaded some data into HBase and then ran a second Pig job to do some aggregations. I knew the data loading would take some time as it was multiple GB of data, but I expected the second aggregation job to run much faster. It ran for over 15 hours and was not done at that time. This was too long in my mind and I terminated it. I was using Amazon Elastic Map Reduce as my Hadoop environment, so … [Read more...]

Why Averages Suck and Percentiles are Great

percentiles

Anyone that 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 … [Read more...]

NoSQL or Traditional Database: From an APM Perspective There Isn’t Really Much Difference

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Traditional Enterprise Database vendors often bring up the lack of professional monitoring and management tool support for NoSQL solutions. Their argument is that enterprise applications require sophisticated tuning and monitoring of the database in order to ensure a performant and smooth operation. NoSQL Vendors, while arguing that this lack is not enough to favor RDBMS over their respective solutions, do agree. Several vendors try to … [Read more...]

Lessons learned from real world BigData implementations

In the last weeks I visited several Cloud and Big Data conferences. Especially the Big Data Innovation in Boston gained me a lot of insight. Some people only consider the technology side of BigData technologies like Hadoop or Cassandra. The real driver however is a different one. Business analysts discover Big Data technologies as the means to leverage tons of existing data and ask questions about customer behavior and all sorts … [Read more...]

How Garbage Collection differs in the three big JVMs

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Most articles about garbage collection ignore the fact that the Sun Hotspot JVM is not the only game in town. In fact whenever you have to work with either IBM WebSphere or Oracle WebLogic you will run on a different runtime. While the concept of Garbage Collection is the same, the implementation is not and neither are the default settings or how to tune it. This often leads to unexpected problems when running the first load tests or in the … [Read more...]