DevOps is the combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity.
- AWS
As the definition suggests, speed and reliability are the two main objectives in a DevOps testing strategy.
The traditional independent-working mindset would be removed by tightening the Dev (development) and Ops (operations) functions together. The process, in turn, makes tight delivery schedules for processes at scale less of a nightmare.
So what does testing in a DevOps environment look like? Two simple concepts: test automation and continuous testing.
The myth that “automating as much as possible” is always the go-to strategy when testing in DevOps is sadly, untrue.
Automation’s primary job is deducting manual-intensive workloads, not removing them completely.
Some examples of mundane tasks that don’t require human intervention include:
Continuity is simply a “must” in the development and deployment process to adhere to DevOps’ aim of quality-at-speed deliveries.
Before going in-depth on continuous testing, we need to talk about CI/CD first.
CI/CD is short for continuous integration and delivery (or development).
In essence, this is a pipeline made up of different tools and entirely supported by automation.
Playing an integral role in DevOps automation and testing strategies, its four main parts are:
We hate to break it to you, but no – there isn’t a one-size-fits-all for a DevOps testing strategy.
Given that every team is on a different page of development and constraints, designing a single path for everyone to follow will not work.
However, there still are some overlaps in a testing strategy that teams can leverage.
With the whole-team approach, the DevOps paradigm heightens the value of shared ownership. DevOps also strives to lower the frequency of handovers or manual sign-offs throughout the software development life cycle (SDLC).
To make this possible, both the development and operations team would need to be self-willed in keeping one another’s affairs in mind from the start.
As for testing, in particular, it no longer is a one-man’s job for a designated tester. But instead, it necessitates the involvement of development teams, developers to be precise, to ensure non-buggy rollouts.
Ideally, the process would look something like this.
Becky, a developer, writes her code on GitHub and commits it onto the mainline. She then monitors the pipeline by waiting for CI tools, like Jenkins, to run unit and integration tests and review the new changes that have been made.
Here, the application of CI tools helps to spot integration bugs, code errors, or logic earlier.
Subsequently, if the test results come back with failures, Becky can directly fix the artifacts on the build or branch.
After the build passes, she can then deploy it to the staging environment. Immediately, the testing team receives real-time notifications from their team’s communication platform – Slack.
Joey, the tester, comes in. One thing to note here is that Joey can now focus more on the testing and maximize its coverage. Why so?
Since Becky’s commits have been thoroughly tested with CI, most bugs have been fixed ahead of time. Joey’s usual time to log bugs is now greatly freed up.
He will now manually explore/test the new changes on staging and develop new scenarios. Following this, end-to-end tests would also be done with an automation testing tool, like Katalon Studio or Selenium.
Through this process, we can already see the formation of a cross-functional team. And the result? The failure or success of the end -product is no longer a game of pointing fingers but a lesson to learn in finessing collaborative work.
We have reached the common ground that automation fosters scalability and agility throughout the testing lifecycle. However, properly implementing automation testing in DevOps is another puzzle to solve.
Below are a few questions most teams encounter and a few recommendations to tackle them.
Determining what to automate relies on factors like execution time, test frequency, resources requirement and the test cases’ characteristics.
An example of what you should automate is regression testing, as it needs to be done for each release.
But exploratory testing? It's something you should not. This is because tests like these call for personal judgment and taking in the insights from previous test runs.
Operating in an environment where new codes are constantly merged with CI, we need to reiterate the importance of automation suites in generating faster feedback. But this time, you would need to know how to divide and arrange your tests, or in technical terms, what to shift left or right.
To reduce obscurities and potential test duplications, tests need to be sorted in terms of their granularity. What does this mean? Here’s a quick breakdown.
The test pyramid is a pretty straightforward concept that focuses on three keywords: granularity, isolation and integration.
Unit and integration tests are isolated, fast, and ideal for early-stage development since they validate individual functions or classes.
In contrast, end-to-end tests are broader, slower, and better suited for later stages. They check the whole system, often flakier and harder to maintain.
The answer to this question varies depending on the problems and goals that your team is trying to solve or to achieve. Nevertheless, you can make the most out of the capabilities of automation by:
After mapping out the automation testing strategy, the next step is DevTestOps orchestration, delivering your overall ROI with effective coordination of relevant tasks, tools suite, and a practical vision of outcomes.
Now that operations have expanded to a much larger scale, keeping everyone posted on the performance and how everything would work in the hand of the user (synthetic monitoring) is crucial. This strategy would allow all members to be notified of any arising issues and handle them on time with the right insights.
To make the monitoring process smoother, your team should consider:
Choosing the right tool stack and technologies isn’t about going with the best or cheapest one, but rather the one with the highest interoperability with your current infrastructure and team’s skill sets.
Open-source options are the most popular. Let’s take Selenium for test automation as an example. Despite being the most well-known, it comes with a lot of high-level requirements a lot of teams fumbles to meet.
Adopting Selenium additionally comes with prerequisites including programming knowledge to maintain the framework and additional expertise to create and run tests.
Furthermore, many open-source toolsets do not come with native integrations with CI tools or common ecosystems, adding extra coding and workarounds. So even though you are not spending a single dime out of your pocket, the trade-off of time to compensate for its learning curve is what you are essentially paying for.
Conversely, buying licenses from commercial tools or a whole tool stack from a single vendor such as Atlassian or Azure DevOps increases the financial investment you would have to make. But, in return you get your money’s worth with dedicated technical support, personalized training, and stable releases for continuous product improvements.
By now, you should have a clear picture of what a strong testing strategy looks like in a DevOps-driven environment. It’s complex, but absolutely achievable.
One key factor in that success is tool selection. For teams with wide skill gaps, especially those transitioning from manual testing or new to automation, choosing tools that abstract away coding complexity is critical.
Katalon Studio, a leading low-code alternative to Selenium, accelerates test creation and eases long-term maintenance with features like:
Keyword-driven testing
Self-healing mechanisms
Smart Wait
Page Object Model and BDD support
TestOps expands into orchestration with customizable scheduling, automatic test distribution, and parallel execution, which cut regression runtimes significantly.
Meanwhile, TestOps offers real-time visibility across QA and dev workflows, enabling:
Clear ownership and traceability for builds and test runs
Quality gates across pre-prod and prod
Actionable insights through visual reports
These tools can help you operationalize DevOps testing efficiently—but remember, there’s no one-size-fits-all solution.
To tailor the right strategy for your team, connect with Katalon experts and explore how Studio and TestOps can work for you.