Moogsoft Docs

Monitor Component CPU and Memory Usage

MySQL Tuner provides useful diagnostics and recommendations on MySQL settings. See MySQL Tuner for more information.

To monitor the CPU and memory usage of the running components of a Moogsoft AIOps system, you can run the following script that offers simple CPU and memory monitoring of the RabbitMQ, Socket LAM, Moogfarmd, Tomcat and MySQL processes:

#!/bin/bash

SLEEPTIME=$1

f_return_metrics() {

        PROCPID=$1
        TOPOUTPUT=`top -p $PROCPID -n1 | tail -2 | head -1 |sed 's/[^ ]\+\s\(.*\)/\1/g'`
        PROCICPU=`echo $TOPOUTPUT| awk '{print $8}'`
        if [ "$PROCICPU" == "S" ]; then PROCICPU=`echo $TOPOUTPUT| awk '{print $9}'`;fi
        PROCPCPU=`ps -p $PROCPID -o pcpu|tail -1|awk '{print $1}'`
        PROCMEM=`ps -p $PROCPID -o rss|tail -1|awk '{print $1}'`
        echo $PROCICPU,$PROCPCPU,$PROCMEM

}

#Capture PIDs
RABBITPID=`ps -ef|grep beam|grep -v grep|awk '{print $2}'`
LAMPID=`ps -ef|grep socket_lam|grep java|grep -v grep|awk '{print $2}'`
MYSQLPID=`ps -ef|grep mysqld|grep -v mysqld_safe|grep -v grep|awk '{print $2}'`
TOMCATPID=`ps -ef|grep tomcat|grep java|grep -v grep|awk '{print $2}'`
FARMDPID=`ps -ef|grep moog_farmd|grep java|grep -v grep|awk '{print $2}'`

echo "DATE,TIME,RABBITICPU(%),RABBITPCPU(%),RABBITRSS(Kb),LAMICPU(%),LAMPCPU(%),LAMRSS(Kb),FARMDICPU(%),FARMDPCPU(%),FARMDRSS(Kb),TOMCATICPU(%),TOMCATPCPU(%),TOMCATRSS(Kb),MYSQLICPU(%),MYSQLPCPU(%),MYSQLRSS(Kb)"

while [ true ]; do

  DATENOW=`date +"%m-%d-%y"`
  TIMENOW=`date +"%T"`

  RABBITMEAS=$(f_return_metrics $RABBITPID)
  LAMMEAS=$(f_return_metrics $LAMPID)
  FARMDMEAS=$(f_return_metrics $FARMDPID)
  TOMCATMEAS=$(f_return_metrics $TOMCATPID)
  MYSQLMEAS=$(f_return_metrics $MYSQLPID)
  TOMCATMEAS=$(f_return_metrics $TOMCATPID)

  echo "$DATENOW,$TIMENOW,$RABBITMEAS,$LAMMEAS,$FARMDMEAS,$TOMCATMEAS,$MYSQLMEAS"

  sleep $SLEEPTIME

done

Sample Usage and Output

 

[root@ldev04 640]# ./perfmon.sh 5
DATE,TIME,RABBITICPU(%),RABBITPCPU(%),RABBITRSS(Kb),LAMICPU(%),LAMPCPU(%),LAMRSS(Kb),FARMDICPU(%),FARMDPCPU(%),FARMDRSS(Kb),TOMCATICPU(%),TOMCATPCPU(%),TOMCATRSS(Kb),MYSQLICPU(%),MYSQLPCPU(%),MYSQLRSS(Kb)
05-10-18,22:44:26,28.0,8.5,203068,2.0,1.0,557092,20.0,13.5,2853408,4.0,2.1,5680584,28.0,17.4,9657152
05-10-18,22:44:34,14.0,8.5,183492,4.0,1.0,557092,16.0,13.5,2850484,0.0,2.1,5680584,33.9,17.4,9657152
05-10-18,22:44:43,0.0,8.5,181072,0.0,1.0,557092,0.0,13.5,2850484,0.0,2.1,5680584,4.0,17.4,9658312
05-10-18,22:44:51,12.0,8.5,181040,0.0,1.0,557092,0.0,13.5,2850484,0.0,2.1,5680584,4.0,17.4,9658312
05-10-18,22:44:59,0.0,8.5,181040,0.0,1.0,557092,0.0,13.4,2850484,0.0,2.1,5680584,0.0,17.4,9658312

Notes:

Notes

  • The script only outputs to the console, so you should redirect the output to a file for logging results.

  • Output is in csv format.

  • ICPU = "Instantaneous CPU Usage (%)"

  • PCPU = "Percentage of CPU usage since process startup (%)"

  • RSS = "Resident Set Size i.e. Memory Usage in Kb"

  • For CPU measurements a measure of 100% represents all of one processor so results > 100% are achievable for multi-threaded processes.

Other Utilities

MySQLTuner provides useful diagnostics and recommendations on MySQL settings. See MySQL Tuner for more information.

To monitor the CPU and memory usage of the running components of a Moogsoft AIOps system, you can run the following script that offers simple CPU and memory monitoring of the RabbitMQ, Socket LAM, Moogfarmd, Tomcat and MySQL processes:

#!/bin/bash

SLEEPTIME=$1

f_return_metrics() {

        PROCPID=$1
        TOPOUTPUT=`top -p $PROCPID -n1 | tail -2 | head -1 |sed 's/[^ ]\+\s\(.*\)/\1/g'`
        PROCICPU=`echo $TOPOUTPUT| awk '{print $8}'`
        if [ "$PROCICPU" == "S" ]; then PROCICPU=`echo $TOPOUTPUT| awk '{print $9}'`;fi
        PROCPCPU=`ps -p $PROCPID -o pcpu|tail -1|awk '{print $1}'`
        PROCMEM=`ps -p $PROCPID -o rss|tail -1|awk '{print $1}'`
        echo $PROCICPU,$PROCPCPU,$PROCMEM

}

#Capture PIDs
RABBITPID=`ps -ef|grep beam|grep -v grep|awk '{print $2}'`
LAMPID=`ps -ef|grep socket_lam|grep java|grep -v grep|awk '{print $2}'`
MYSQLPID=`ps -ef|grep mysqld|grep -v mysqld_safe|grep -v grep|awk '{print $2}'`
TOMCATPID=`ps -ef|grep tomcat|grep java|grep -v grep|awk '{print $2}'`
FARMDPID=`ps -ef|grep moog_farmd|grep java|grep -v grep|awk '{print $2}'`

echo "DATE,TIME,RABBITICPU(%),RABBITPCPU(%),RABBITRSS(Kb),LAMICPU(%),LAMPCPU(%),LAMRSS(Kb),FARMDICPU(%),FARMDPCPU(%),FARMDRSS(Kb),TOMCATICPU(%),TOMCATPCPU(%),TOMCATRSS(Kb),MYSQLICPU(%),MYSQLPCPU(%),MYSQLRSS(Kb)"

while [ true ]; do

  DATENOW=`date +"%m-%d-%y"`
  TIMENOW=`date +"%T"`

  RABBITMEAS=$(f_return_metrics $RABBITPID)
  LAMMEAS=$(f_return_metrics $LAMPID)
  FARMDMEAS=$(f_return_metrics $FARMDPID)
  TOMCATMEAS=$(f_return_metrics $TOMCATPID)
  MYSQLMEAS=$(f_return_metrics $MYSQLPID)
  TOMCATMEAS=$(f_return_metrics $TOMCATPID)

  echo "$DATENOW,$TIMENOW,$RABBITMEAS,$LAMMEAS,$FARMDMEAS,$TOMCATMEAS,$MYSQLMEAS"

  sleep $SLEEPTIME

done

Example usage and output:

[root@ldev04 640]# ./perfmon.sh 5
DATE,TIME,RABBITICPU(%),RABBITPCPU(%),RABBITRSS(Kb),LAMICPU(%),LAMPCPU(%),LAMRSS(Kb),FARMDICPU(%),FARMDPCPU(%),FARMDRSS(Kb),TOMCATICPU(%),TOMCATPCPU(%),TOMCATRSS(Kb),MYSQLICPU(%),MYSQLPCPU(%),MYSQLRSS(Kb)
05-10-18,22:44:26,28.0,8.5,203068,2.0,1.0,557092,20.0,13.5,2853408,4.0,2.1,5680584,28.0,17.4,9657152
05-10-18,22:44:34,14.0,8.5,183492,4.0,1.0,557092,16.0,13.5,2850484,0.0,2.1,5680584,33.9,17.4,9657152
05-10-18,22:44:43,0.0,8.5,181072,0.0,1.0,557092,0.0,13.5,2850484,0.0,2.1,5680584,4.0,17.4,9658312
05-10-18,22:44:51,12.0,8.5,181040,0.0,1.0,557092,0.0,13.5,2850484,0.0,2.1,5680584,4.0,17.4,9658312
05-10-18,22:44:59,0.0,8.5,181040,0.0,1.0,557092,0.0,13.4,2850484,0.0,2.1,5680584,0.0,17.4,9658312

Notes:

  • Script only outputs to the console so should be redirected to a file for logging results

  • Output is in csv format.

  • ICPU = "Instantaneous CPU Usage (%)"

  • PCPU = "Percentage of CPU usage since process startup (%)"

  • RSS = "Resident Set Size i.e. Memory Usage in Kb"

  • For CPU measurements a measure of 100% represents all of one processor so results > 100% are achievable for multi-threaded processes.