ADF Performance Monitor – Major New Version 9.0 (Part 1)

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I’m very excited to announce that we have a major new version of the ADF Performance Monitor – version 9.0 !

We have added many valuable new features; new metrics that can detect and help explain poor performance, disruptions, hiccups, and help troubleshooting ADF applications. Like operating system metrics: the CPU usage of the ADF application, the total CPU usage of the whole underlying operating system, the total used and free physical (RAM) memory of the whole system, and the Linux load averages. A high CPU usage rate and memory usage may indicate a poorly tuned or designed application. Optimizing the application can lower CPU utilization. Generic APM tools have these kinds of metrics too in some way, but the combination of system metrics with ADF specific metrics of the ADF Performance Monitor makes it even more possible to relate performance problems.

Another reason to pay attention to system metrics is that nowadays more and more applications are deployed on the cloud. Very likely there will be shared virtual machines and resources (CPU, memory, network). Applications and processes could influence each other if frequently other processes have a very high usage of the available CPU or memory capacity.

This blog (part 1) describes the first part of these new features. Part 2 describes the CPU execution time of individual HTTP requests and click actions. It answers the question: “What request/click action in the application is responsible for burning that CPU ?

CPU Usage and Performance

Read the whole article on our ADF Performance Monitor website

About Author

Frank Houweling is an Oracle ADF, Java and performance specialist. During the past years he has been requested several times as troubleshooter of ADF projects with bad performance. As such he has been performing performance analysis, bottleneck detection and developing mitigating solutions based on these analysis. He is also the creator of the ADF Performance Monitor, an advanced monitor that can identify, report and help solve performance bottlenecks in ADF applications.

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