HANA Host CPU Test

Without adequate processing power, a SAP HANA database server can stop functioning. This is why, it is imperative that administrators keep an eye on the CPU usage of the database server, so that if CPU usage exceeds permissible limits, it can be quickly detected and treated to ensure optimal performance of the server. This is where the HANA Host CPU test helps. This test monitors the overall CPU utilization of the SAP HANA database server and reveals where the maximum CPU time is spent – in serving user requests? in system-level processing? in waiting for I/O? or being idle? This way, the test not only points administrators to the excessive CPU usage by the SAP HANA server, but also indicates the reason for the same, so that administrators can initiate the correct remedial measures.

Target of the test : A SAP HANA Database Server

Agent deploying the test : A remote agent

Outputs of the test : One set of results for every SAP HANA database server being monitored.

Configurable parameters for the test
Parameter	Description
Test period	How often should the test be executed
Host	The host for which the test is to be configured.
Port	The port number at which the specified Host listens to. By default, this will be 30015.
User	In order to monitor a SAP HANA database server, a special database user account with Monitoring privileges has to be created in every SAP HANA database instance that requires monitoring. The syntax of the script that is used for user creation is discussed in How to Monitor SAP HANA Database Server Using eG Enterprise?. The name of such a user has to be specified here.
Password	Enter the password of the specified User.
Confirm Password	Confirm the password by retyping it here.
IsPassive	If the value chosen for this parameter is Yes, then the SAP HANA database server under consideration is a passive server in a SAP HANA cluster. No alerts will be generated if the server is not running. Measures will be reported as “Not applicable” by the agent if the server is not up.

Measurements made by the test
Measurement	Description	Measurement Unit	Interpretation
CPU Usage	Indicates the percentage of CPU that is currently utilized by the SAP HANA database server.	Percent	A value close to 100% hints a potential CPU contention at the host, which must be cleared pre-emptively, to ensure that the performance of the server is not compromised.
System CPU	Indicates the percentage of CPU time the SAP HANA server spent in system-level processing.	Percent	Compare the value of this measure with the value of the User CPU, Wait I/O CPU, and Idle CPU measures to understand where SAP HANA spent the maximum CPU time - in serving user requests? in system-level processing? in waiting for I/O? or being idle? In the event of a slowdown, you can use the results of this comparative analysis to determine what caused the CPU contention.
User CPU	Indicates the percentage of CPU time that the host spent in user-level processing.	Percent	Compare the value of this measure with the value of the System CPU, Wait I/O CPU, and Idle CPU measures to understand where SAP HANA spent the maximum CPU time - in serving user requests? in system-level processing? in waiting for I/O? or being idle? In the event of a slowdown, you can use the results of this comparative analysis to determine what caused the CPU contention.
Wait I/O CPU	Indicates the percentage of time the CPU had to wait for I/O operations on this SAP HANA database host.	Percent	Compare the value of this measure with the value of the System CPU, User CPU, and Idle CPU measures to understand where SAP HANA spent the maximum CPU time - in serving user requests? in system-level processing? in waiting for I/O? or being idle? In the event of a slowdown, you can use the results of this comparative analysis to determine what caused the CPU contention.
Idle CPU	Indicates the percentage of time the CPU was idle on this SAP HANA database host.	Percent	Compare the value of this measure with the value of the System CPU, User CPU, and Wait I/O CPU measures to understand where SAP HANA spent the maximum CPU time - in serving user requests? in system-level processing? in waiting for I/O? or being idle? In the event of a slowdown, you can use the results of this comparative analysis to determine what caused the CPU contention.