DevOps is the combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity.
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.
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:
- Software testing: simple unit, regression, or end-to-end tests are commonly automated
- Infrastructure management: reduce repetitive setups, configurations, and maintenance of IT infrastructures like servers and networks
- Log management: automated logging tools will help handle a larger volume of data better, from application requests to error messages
- Monitoring: gives an accurate and up-to-date reflection on the system’s health and performance trends of all testing activities
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:
- Continuous integration (CI): continuously integrate or merge new codes into a central repository (mainline) and compile them into builds.
- Continuous testing: validating code and product quality from its build with automated unit, integration, or end-to-end tests to search for bugs or if anything had broken from the commit
- Continuous delivery (CD): after recent code submissions are pushed to staging, CD supports developers to manually cherry-pick qualified release candidates to push to production
- Continuous deployment (CD): extends continuous delivery by automatically shipping every successful build to production before running end-to-end tests to make sure there are no regressions
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, an instance with exploratory testing is 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 testing pyramid is a pretty straightforward concept that focuses on three keywords: granularity, isolation and integration.
- Granularity: the measure of how integrated or isolated your tests are
- Isolated tests: refer to testing the individual components that are less connected from your application as a whole (unit and integration tests)
- Integrated tests: look at tests that drill down into your application from top to bottom from an end-user point of view (end-to-end tests)
For smaller-scope unit and integration tests that only check the function or class of your codebase work, they would be considered isolated and subsequently have a much faster execution time. With the ability to give back results to changes you have made in a fraction of a minute, these tests should be placed in the initial stage of your development project timeline.
In contrast, as you reach further down into the later stages of the SDLC, tests like end-to-end are considered to have a broader scope, be more integrated, and take up to days, or weeks, to complete. Why? Because this system-level testing checks the entirety of your software, which can be innately flaky and a real pain to maintain.
How can I maximize test automation efficiency in DevOps? 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:
- Selecting the right tool and framework
- Understanding testing basics
- Defining performance metrics to see pass and fail patterns
- Developing good documentation practices and leveraging them into your CI/CD process
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 be able to picture what testing strategy that excels in a DevOps culture needs to have. It’s a lot to take in, but not impossible to achieve.
We now know that the tools selection step is one of the many factors that will either make or break your path to an optimal testing plan.
For teams with large skill gaps, say transitioning manual testers and automation freshers without coding expertise, a tool that simplifies automation complexities is much needed.
Test automation and orchestration done right. As the most compatible Selenium alternative, Katalon Studio’s low-code approach speeds up from your test creation stage to reducing maintenance burdens using:
- Keyword-driven testing
- Self-healing mechanisms
- Smart Wait
- Page-object model and BDD design support
Extending further to orchestration capabilities, TestOps lets you easily schedule and trigger regressions or builds with customizable frequency, accompanied by smart auto-distributed and parallel executions to cut down their completion time.
Embracing shift-left practices. TestOps provides a collaborative dashboard, enabling developers to participate earlier on in the testing lifecycle. With native integrations to top CI tools (e.g., Jenkins, Azure DevOps, CircleCI), unit test and integration test reports can be automatically drawn, stored, and centralized into a single place. This helps:
- Speed up failure or flakiness investigation with historical trends
- Trigger alerts on all incidents right on common project management platforms (e.g., Slack and Jira)
Proactive continuous monitoring. From QA engineers to managers and business analysts, TestOps platform organizes all operational and development activities into a real-time and easy-to-understand snapshot. Teams could benefit from:
- Straightforward task delegation processes with owner’s and creator’s id of builds and tests
- Smooth-functioning quality gate to oversee all issues on both the pre and production environments
- Visualized execution results and insightful reports to identify the actions to be taken
We hope these insights were helpful for you to build a DevOps testing strategy for your team.
Remember, a perfect solution for one organization would not necessarily be the best for yours. Having helped over 100,000 businesses and teams customize their testing strategies, view a demo with Katalon experts to get your tailored plan up and running with Studio and TestOps.
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