Setting up system monitoring with a Step agent

This article demonstrates how to set up distributed system monitoring using Keyword executions, and analyze the results as measurements.

This tutorial will demonstrate how to set up distributed system monitoring by leveraging Keyword executions on dedicated token pools, as well as how to analyze the results as numerical measurement in RTM views. This example is based on Windows performance counters using the standard typeperf command. The same approach can be used on Unix with vmstat and can easily be extended and customized to suit other platform needs.

Keyword setup

We will leverage the agent platform and execute a special Keywords at regular intervals in order to poll system metric values and feed them back to Step’s measurement database. Sample Keyword code is provided in our GitHub sample repository under “keywords/java/demo-system-monitoring”. The code contains a generic Keyword for executing managed processes from Java that is extended to cover the Windows typeperf process.

Setup your agent

We will create dedicated execution slots, called token pools, in order to isolate the execution of this technical Keyword from business keywords. You will need to modify the AgentConf.json configuration file in your existing agent setup.

Add an AGENT_TYPE “DEFAULT” to the main tokenGroups
Create a 2nd group with a unique AGENT_TYPE name and a capacity of 1

For the controller and database servers, you will install a dedicated agent with only one token group for the monitoring following the same rules, capacity of 1 and unique AGENT_TYPE value.

Example:

  {
"gridHost":"http://controller:8081",
"agentPort": 31001,
"registrationPeriod":1000,
"gridReadTimeout":20000,
"workingDir":"../work",
"tokenGroups":[
{"capacity":250,
"tokenConf":{
"attributes":{"AGENT_TYPE" : "DEFAULT"},
"properties":{"chromedriver":"../ext/bin/chromedriver/chromedriver.exe"}}
},
{"capacity":1,
"tokenConf":{
"attributes":{"AGENT_TYPE" : "MONITORING_agentName_001"},
"properties":{"chromedriver":"../ext/bin/chromedriver/chromedriver.exe"}}
}
],
"properties":{
"plugins.jmeter.home":"../ext/lib/jmeter",
"plugins.selenium.libs.2.x":"../ext/lib/selenium/selenium-2.53.1",
"plugins.selenium.libs.3.x":"../ext/lib/selenium/selenium-java-3.5.3",
"plugins.qftest.home":"C:/Users/jcomte/Programs/qftest-4.1.2",
"plugins.pdftest.gsexe":"/path/to/gswin64.exe"
}
}

Step controller parameters

Now that a distinct pool is available for monitoring purposes, we will tell Step to route all regular Keywords to the default pool. Later on, we will make sure to route the monitoring Keywords to the other pool in our plan.

Key: rout_to_AGENT_TYPE, value: DEFAULT

Metric configuration and postprocessing

We recommend updating the typeperf counters already defined in the included resource CSV file, “typePerf.csv”

  Metric_name,Typeperf_counter,groovy
CPU(%),\Processor(_Total)\% Idle Time,100-value
MemoryAvailableMB,\Memory\Available MBytes,

Metric name is the name of the metric which will be reported in RTM
Typeperf_counter is the typeperf counter to be retrieved. Refer to windows-commands/typeperf to learn more about typeperf.
groovy is a groovy expression which will be evaluated during the post processing; the resulting value will be stored as the measurement’s value.

The Step plan

The plan in the example below is designed to run for one hour, taking a sample for each defined agent each minute.

Note, the Keyword execution is configured to take place on the new token pool reserved for monitoring. Refer to the routing section of the Keyword call node in the provided plan.

Execution

You have the option to run the plan once and tweak it to match your desired duration and sampling interval or to schedule it to restart every hour as shown below:

Selecting the CRON expression to run every hour will result in the following entry in the scheduler

RTM

Unlike other test executions, all measurements from this Keyword are created using a common execution id, eld, unrelated to the actual Step execution. The common eld used is “OSmonitor” and is used in RTM to retrieve related measurements. If you keep the monitoring running in the background, it is recommended to use a time frame filter in your query. In addition to the metric name, the “hostname” of the monitoring agent is automatically added to your measurements and you may then use it as a group clause:

Which results in the following output:

Housekeeping

You may cleanup the measurement collection based on the OSmonitor eld and timestamp. Refer to our Housekeeping section.

Summary: This article demonstrates how to set up distributed system monitoring using Keyword executions, as well as how to analyze the results as numerical measurements in RTM views.

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