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Our technical environment has been radically altered by the quick growth in technologies and the digitization boom. A large section of today’s population relies on their mobile phones for every move. If you work in quality assurance, you’re probably used to thinking of software monitoring tools to be not your forte or as someone else’s responsibility. Traditionally, IT teams were in charge of monitoring applications; QA’s involvement was limited to pre-deployment testing, and QA engineers seldom touched software monitoring tools.

However, monitoring tools—that is, technologies meant to assess application availability and performance and alert teams to problems—aren’t only for IT teams. They can also assist QA engineers in doing their duties more successfully.

Estimated number of QA and software developers employed in the US from 2020 to 2030

Here’s an overview of how monitoring technologies like Prometheus, Sumo Logic, and Splunk may assist QA and the problems QA teams should be aware of when dealing with software monitoring tools and their data.


Software Monitoring tools are constructed to track the system’s state in use and detect and fix faults, flaws, or issues as soon as they occur in a continuous interval.

Monitoring software is available for servers, networks, databases, security, performance, website and internet use, and applications.


Monitoring tools exhibit the following characteristics:

  • They detect the issues and notify the administrator (e.g., network administrator);
  • They record real-time and historical data; These are used to determine ideal settings;
  • They keep track of the number of network users;
  • They keep track of network traffic (either in real-time or covering a given length of time of operation with the analysis performed afterward)


Even while QA engineers are more accustomed to dealing with software testing tools than monitoring tools, the latter may assist QA.

1. Tracking the impact of QA on application quality

The role that software monitoring tools may play in tracking the impact of QA on application quality is perhaps the clearest.

When it comes to identifying the link between what the QA team is doing and the quality of production apps, software delivery teams are shooting in the dark without software monitoring tools and data. There is no systematic way to determine how a new testing routine or the transition of a test suite from human to automation affects the application’s dependability, usability, or performance. Some correlations between QA methods and application quality may be inferred, but these conclusions will be subjective and ad hoc.

When the QA team observes the application routinely in production rather than simply during testing, it becomes easier to establish links between QA methods and application quality. The monitoring data may be utilized to understand the impact of any modifications made by QA.

This results in a more effective method of arranging QA activities and deciding what works and what doesn’t.

2. Establishing universal KPIs

Establishing metrics that can track code quality at all stages of the pipeline is a typical difficulty in DevOps delivery pipelines. When developers use a set of tools to measure progress, QA uses another, and IT uses still another, it’s hard to create a unified body of data that represents application quality throughout the pipeline.

On the other hand, QA teams can assist in resolving this issue by utilizing monitoring technologies. They can collaborate with IT developers to develop a set of KPIs that everyone will use to assess application health and performance. QA may then build tests that focus on analyzing specific KPIs before releasing an application, while IT monitors the same KPIs after deployment. Developers may help by concentrating on the KPIs when writing new code.

3. Justify the investment in QA

Many businesses are under continual pressure to justify their investment in QA. Software monitoring tools can play a significant role in assisting with this. QA monitoring is also necessary for the successful running of the application. The use of monitoring technologies to track QA’s influence on application quality and define uniform KPIs helps to demonstrate the value of QA. So all the processes need investments, and the investment is justified and fruitful.


There is always a different story when you look at the flip side of the story. Every serendipitous discovery comes with its set of perils. Below, we will discuss some of the disadvantages of using software monitoring tools by QA teams.

  • You don’t need QA monitoring when you have sophisticated software monitoring tools.
  • Sometimes continuous testing and monitoring of the codes are not necessary, yet some APM vendors promise these facilities,

While software monitoring tools may appear to be a danger to QA, this is precisely why QA teams must embrace these monitoring tools and ensure that they support rather than replace the conventional QA approach. Even the most advanced monitoring systems cannot replace software testing. APM tools cannot resolve issues before they reach production. They are also ineffective for troubleshooting issues that QA excels in identifying and addressing before deployment, such as usability testing.


While monitoring technologies may appear to be a danger to QA at times, they are becoming an increasingly valuable supplementary resource for QA engineers. In the United States, in 2020, there will be around 1.49 million software developers and software quality assurance (QA) specialists. This figure is predicted to climb to 1.84 million by 2030.QA engineers may use monitoring technologies to clarify the overall relevance of QA, connect the QA process more directly to application quality in production, and communicate easily with developers and the IT team.