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The aim of this post is to explain how to help you monitoring Java applications deployed on SCP.

First of all, let’s go through the main monitoring built-in functionalities available and clearly visible and then we will go through the advanced functionalities which may be a bit hidden but are very important and valuable to use.

 

Step1 : UsingĀ the main monitoring built-in functionalities available and clearly visible

  • Monitoring physical resources such CPU, Memory, Disk I/O:

In order to monitor such metrics, that’s the probably easiest to get.

They are available within the cockpit whenever a Java application is deployed:

First of all, go to the Java applications:

Click on your Java application that you need to monitor. Then the following navigation menu displays as per below:

Then, this is where the interesting part starts šŸ™‚

Clicking on the Application Monitoring will display the following graphs:

  • Average Response Time (ms)
  • Busy Threads
  • CPU Load (%)
  • Disk I/O (B/s)
  • Free EBS Space (%)
  • Heap Memory Usage (%)
  • OS Memory Usage (%)
  • Requests per Minute (requests)
  • Used Disc Space (%)

Each graph can be zoomed-in in order to check for a specific timeframe or sometimes, it is useful whenver it is required to adjust the scale such for example once a very high response time appeared and it is not then possible to see the details later on.

Step 2 : Using advanced monitoring built-in functionalities available and not visible cleary

There is a huge of valuable monitoring information avaiable from the JMX console.

The JMX consoleĀ  is accessible in the navigation as below:

Then, a folder hierarchy like structure will appear.

Now, let’s go the most important metrics from the JMX console (… or at least the ones I could find the most useful for me once monitoring) .

  • Monitoring the JDBC connection pool:

Once monitoring a live system or also a system where we put some load for example for performance and stress tests, it is always a good idea to monitor it and make sure we do not run into a performance bottleneck in this area.

In order to monitor it, you need to browser into the following level:

com.sap.cloud.jmx -> Persistence -ConnectionPools:

Once monitoring a system, these information above are very precious.

Below, the most critical metrics in my view:

  • MaxConnections is the maximum number of connection the pool will open.
  • BorrowedConnectionsCount is the number of connections “borrowed” to the application.
  • PooledConnectionsCount is the number of connections available in the pool.

There are others metrics which can also show how much time threads have been waiting to get a connection and which could also be a good indicator to help you sizing properly the number of maxium connections to set in the pool.

  • Triggering thread dumps:

As for all Java applications, it is sometimes required to be able to trigger thread dumps to analyze locking situation issues/hanging situations. Therefore, it is also possible

2461379 – How to Trigger a Thread Dump for Java Applications on SCP( SAP Cloud Platform)

The previous KBA/Note will also explain you how to download the thread dumps then and analyze them.

In order to analyze them, I will then recommend you to use the SAP Thread Dump Viewer tha you can also find below:

1020246 – Thread Dump Viewer for SAP Java Engine

  • Analyzing Garbage Collections:

It is possible to analyze the Garbage Collections. To do so, you can review them from the SCP cockpit from the Logging and then in the section ‘Garbage Collection Logs’:

You can the either visualize it online from the cockpit or download the file itself and open it with your prefered GC viewer log.

  • Setting JVM arguments (neo command line)

Below, is the reference guide how to configure VM arguments:

Configuring VM arguments

You can for example fine tune the JVM parameters if you wish to increase the heap memory/resize the new area, etc…

Another useful guide is the one to deploy using the neo command line:

https://help.hana.ondemand.com/mavenSite/deploy-mojo.html

 

I will keep enriching this blog… therefore stay tuned…

 

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