To achieve higher product quality, QAOps makes sure the QA team collaborates with the operations and development teams and is a part of the CI/CD pipeline.
What is QAOPS?
A new methodology called QAOps incorporates QA (Quality Assurance) into the pipelines used to deploy software. The QA team must collaborate closely with the operations team and the development team as a result.
Achieving this requires combining the SDLC with QA processes, automation, and a QA reporting dashboard.
By using QAOps, the tester and developer teams will work together more closely by giving the QA team a new responsibility within the software development life cycle.
QAOPs primarily follow these two guiding principles:
The Continuous Integration (CI)/Continuous Deployment (CD) pipelines must include QA actions.
When constructing the CI/CD pipeline, software engineers should collaborate closely with the operations and development teams.
It can be challenging to comprehend QAOps based just on an explanation. If you are familiar with CI/CD and how it fits into the software development lifecycle, you will understand it clearly.
While the SDLC heavily relies on the QAOps technique, its foundation is DevOps’ Continuous Integration and Continuous Delivery (CI/CD) infrastructure.
There are various benefits to implementing QAOps in DevOps, some of which are as follows:
Workflow produces quicker, higher-quality solutions.
The testing team collaborates extensively with other teams, raising their level of expertise.
A higher standard of dependability, quality, and stability assures improved client satisfaction.
Life Cycle of QAOPS:-
The core of QAOps is creating a precise platform with well-liked tools on the CI/CD pipeline to guarantee that newly created code is thoroughly verified and tested. We are accustomed to setting up test platforms because they involve three distinct steps: triggering, executing, and reporting.
Trigger:-
The trigger stage involves creating precise test cases that are appropriate for evaluating the technically of the product without squandering time on pointless test cases.
As a result, three considerations must be made when planning the triggering phase:
At the beginning, plan out the testing.
Think about testing in general, including integration testing.
Use testing for code deployment and verification.
The triggering step, therefore, requires careful design and mapping out in alignment with the automated test life cycle. If the QAOps team manages this phase smoothly, it can persuade the entire team to release the product.
Implement:-
The implementation phase is the following step in the QAOps process. In this stage, the parallel testing that was approved in the trigger step is put into practice.
Several important criteria confirm the execution planning in the SDLC:
- Tests running in parallel to start the procedure
- Choosing the appropriate support for each integration test
- Evaluating the procedure’s ability to scale
- Ensuring that the tests are run as necessary in the correct order
- Dividing up the workload of the implementation tests between other departments
- Ensuring that all necessary framework and infrastructure are available for the execution of the entire procedure
Report:-
The report phase, which includes reporting the outcomes of the trigger and implementation processes, is the final stage of the QAOps lifecycle. The entire procedure produces a final report, providing a detailed description. The ideal reporting module design includes a summary and comprehensive information, all within a snapshot.
Furthermore, the reporting module includes and stores the history of previous tests that different stakeholders can use for comparing and assessing the results.. Such reports must to be readily available and available upon request.
The QAs were required to focus on a few key topics in order to comprehend the report module design:
- Detailed views and snapshots of the entire project
- Focus on the underlying reason for the different processes required.
- Rapid provision of accurate results without ambiguity
- Make sure the report is readily available when needed.
- Complete report details so they can be consulted once more during the following debugging process
- Assessing report scalability while handling a massive amount of data
Techniques used in the QAOPS Framework:-
For shorter testing cycles and improved software quality and stability, QAOps makes use of the following group of test approaches.
- Automation Testing :-
The QAOps framework accelerates the software testing process by utilizing automation to examine the product’s quality. Before creating an automation framework, QA engineers must research the product to better understand its requirements, features, and objectives. Additionally, collect the data needed for flawlessly developing the automated test programs.
Following completion of this investigation, QA teams can integrate the codes into the QAOps pipeline. Test data is more relevant thanks to automated testing, which also saves valuable time.
- Parallel Testing :-
In QAOps, teams simultaneously run multiple test cases on an app and its component parts across different OSs and browsers during parallel testing. This approach is ideal because automated tests can significantly reduce the overall testing time.
Given the parallel data, parallel test performs well with QAOps, providing quicker tests inside the delivery pipeline.
QAs can start CI/CD pipelines with smoke and automated tests in numerous concurrent streams when server capacity permits.
Utilizing a real device cloud is essential to managing the additional data processing load required for running numerous tests concurrently.
- Scalability Testing :-
As a standard QAOps procedure, QA teams should make sure that their infrastructure is scalable and use scalability tests in the pipeline to accelerate testing when appropriate.
By changing the test loads, a scalability test aids in defining the performance of an application or system in various contexts.
The results of such testing show how the system or app will behave under real-world conditions.
This knowledge is essential since testing in a CI/CD paradigm needs to scale up and down in unison with the pipeline.
This makes it easier to spot “flaky” tests—those that produce both a passing and a failing result using the same piece of code. Prior to the SDLC, identifying unstable tests helps teams identify and remove them from their app.
- Regression Testing :-
When the software has already been developed and released, a regression test is performed. Additionally, QA teams might carry out this testing if it’s necessary to update the current framework & republish the product on the market.
As it seeks to add new functionalities to the product, this testing might occasionally cause duplicate problems in the product. QA teams can streamline this process without spending significant time and resources on changes to prevent this error.
- Exploratory Functional Testing :-
This type of testing is used to make sure the final product reaches the desired output. Here, the entire testing process depends on the QA engineers’ expertise because they must take into account potential problems or vulnerabilities in the system and address them before the launch. In order to proceed depending on the current state of the app, QAs must think outside the scripted code.
- Geolocation Testing :-
Every product development business has to know whether a web app they are creating will work in a particular environment. Your test engineers can work together with the operations team using QAOps to become more familiar with these internet standards.
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