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)
(Note: If you’re interested in WebSphere in a production environment, check
out Michael's upcoming webinar with The Bon-Ton Stores)
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 worst case... (more)
In my last article I explained what a major Garbage Collection is. While a
major Collection certainly has a negative impact on performance it is not the
only thing that we need to watch out for. And in case of the CMS we might not
always be able to distinguish between major and minor GC. So before we start
tuning the garbage collector we first need to know what we want to tune
for. From a high level there are two main tuning goals.
Execution Time vs. Throughput
The first thing we need to clarify if we want to minimize the time the
application needs to respond to a request or if we... (more)
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)
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)