There’s no way you talk about software without mentioning testing or software testing. No software should ever be shipped if it hasn’t passed through thorough software testing practices. If one has to be honest, testing assures that what has been built not only works but also works as intended under expected and unexpected conditions.

Testing exposes bugs and performance bottlenecks before they reach users. It challenges assumptions and helps ensure that your software not only exists but also delivers the intended value.

This article will discuss testing and introduce the concept of Test Operations (testOps). By the end of this article, you should see testing in a broader picture and see cases where testOps come in. You’ll also know a variety of the tools you can use to implement testOps in your development workflow.

What is Testing?

Before we get into the testOps discussion further, it is essential that we take a brief look at testing itself. Every software solution, whether it is developer focused or commercial, has requirements that it’s built to meet. Among the phases in a software development life cycle, software testing is one of them. This critical phase aims to detect defects across all parts of the software, helping you confirm that your software delivers value in real world conditions.

Testing checks that you are building the right software (verification) and that the software is built right (validation). That is to say, your software shouldn’t just work, it should also work efficiently and correctly.

Testing can be functional (testing to ensure the software does what the requirements ask of it) or non-functional (making sure the software works fast enough, easy enough, and is secure). Proper testing helps safeguard the reputation of both the software and the organization behind it. Checking each component of the software and how they interact with each other is testing, checking individual components and their results or outputs in isolation is testing, and checking that software can handle unexpected edge cases and malicious inputs is also testing. You deliver with confidence when you test.

Functional testing encompasses several types of testing, including:

• Unit testing: Testing individual units or components of software to ensure it works expected.
• Integration testing: Testing the interaction between units or components to detect interface defects.
• Regression testing: Making sure that existing software functionality still works. Ensures new changes haven’t introduced bugs.
• System testing (end-to-end testing): Testing the complete and integrated software to verify it meets the specified requirements.
• Acceptance testing: Testing the software by using it, and checking that it meets the user requirements.

Non-functional testing would include tests like:

• Performance testing: Evaluating the speed, responsiveness, and stability of the software under a particular workload.
• Security testing: Identifying vulnerabilities and ensuring that the software is safeguarded against threats and unauthorized access.
• Usability testing: Assessing how easy the user interface is for users to interact with.
• Compatibility testing: Checking if the software works as expected across all of the devices, browsers, and operating systems it is expected to.
• Reliability testing: Ensuring that the software performs consistently under specified conditions.

In between functional and non-functional testing lies tests which check that both core functionalities and underlying performance work as expected. For example:

• Smoke testing: A preliminary testing to reveal simple failures severe enough to reject a prospective software release.
• White-box testing: Testing the internal structures or workings of an application, as opposed to its functionality.
• Black-box testing: Testing the external functionalities of the software without knowing its internal workings.
• Sanity testing: A brief run-through to ensure the basic functionalities work correctly after minor changes

These are obviously a lot of terms and a lot of steps, but most of this testing is truly desirable, even if you are creating software for even a small number of users to use.

Flaky Tests

Most of the tests described so far are designed to produce the same output every time. For example, testing the outcome of 1+1 is always 2. If not, you have an issue. Some tests are don’t always produce the same output, even when the core functionality remains the same, and sometimes this is expected, and others not so much. These kinds of tests are referred to as a flaky test, and when unexpected the cause can be difficult to determine and debug.

Inconsistent result outcomes are sometimes caused by external dependencies that may behave inconsistently due to network issues or service downtime, test order due to shared states, or resources interfering with each other when executed in a particular sequence. Sometimes the cause can be due to non-deterministic code like timestamps, concurrent processes or async-await operations leading to unpredictable outcomes. Other causes are mostly environmental, because of variations in test environments. For example, the hardware and/or operating system used, network conditions or configurations, or even the CI solution used. These causes are outside the control of the codebase itself, making it difficult to point out the underlying cause.

There’s always a chance that you’ll come across flaky tests in the software testing phase, no matter how guarded you code your software and write your tests. In software testing, flaky tests are usually challenging to avoid. The root cause can be subtle and environment-dependent, therefore test concepts like mocking and stubbing can help isolate the code under test and eliminate external influences. This approach, combined with consistent infrastructure or environments can help make test outputs reproducible and deterministic.

Test Debt

There are technical debts that arise in the software development life cycle which arise when shortcuts or compromises are made to meet deadlines and reduce development time. Among these, issues related to inadequate testing, manual testing, incomplete test coverage or poorly maintained tests are what is referred to as Test Debt.

It is understandable to prioritize speed and release software as fast as possible; however, neglecting proper testing practices during the development phase often leads to long-term consequences, requiring extensive time and resources to address. Test debt can accumulate quickly, and make software prone to bugs, increase maintenance costs and slow down future development cycles. Integrating robust testing practices at the early stages of development, test automation and continuous review of tests can help prevent test debt.

What is testOps?

TestOps is the combination of testing practices and operational strategies to ensure testing is not just effective, but also efficiently integrated into software development and delivery processes. testOps prioritizes automation; from test execution and reporting to enabling faster feedback.

When the word “testOps” is used, most developers tend to think only of running tests in a CI/CD workflow or automating test runs so that for every code push, tests are triggered automatically to validate code changes. While this is part of testOps, it is way more than that. TestOps encompasses the entire product testing life cycle, from identifying test requirements, scope and software goals, test organization, and test monitoring to generating reports and feeding learnings back into the testing cycle.

TestOps aims to ensure software quality through continuous testing and continuous integration. testOps boost collaboration between the developer’s team and the testing and operations teams. It focuses on improving and managing test environments and handling test related challenges to enable teams to release high quality software faster and more efficiently.

TestOps is typically carried out in the following stages:

Planning: At this stage, you and your team identify the testing requirements, the scope of testing activities, and who is responsible for executing specific tasks and deliverables. Also at this stage, you and your team map out the testing strategy and prioritize the testing practices to adopt that align with the goals of the software in question. For example, the type of tests to be carried out before the first release, the timelines for each phase of testing, and so on. The planning stages asks, “what are we testing? How do we test it? Who should test it? And when do we consider the test activity as done?” Coupled with considering other factors necessary to ensure a well-organized and efficient testing process.

Management: As the software grows, the need for testing increases, and therefore testing becomes complex. This is because new features are continually added, testing now needs to cover both new and existing functionalities and the number of people involved tends to increase in size. This stage checks that test conventions are followed, and tests are properly coordinated and organized, with clear delegation of test-related tasks among team members.

Iteration becomes a key part of the process, confirming that tests are continually updated and refined as the software in question evolves, that tests are executed on predefined environments or using predefined tools, and that tests are analyzed using the agreed tools and metrics.

A lot of tracking is involved in this stage also, checking that tests are executed in a structured manner, the testing progress is properly tracked, and that the resources and outcomes are in line with the software’s goals and timelines.

Control: This stage checks that the testing process doesn’t deviate from the plan, and if so enforce corrective actions where necessary. In simpler terms, this stage checks if testing processes are in accordance with software specifications, if resources are properly utilized, are there any risks or trade offs to consider and is there any need to reassign tasks. Additionally, it confirms that the entire testing process is documented and reviewed by the appropriate test leaders. This stage’s primary goal is to ensure that the testing process remains focused and efficient.

Insights: Analyzing the result of the testing process, extracting actionable information, evaluating outcomes and patterns and uncovering areas of improvement is what this final stage is all about. At this stage teams ask the following questions; were the objectives met, were there any recurring issues or bottlenecks, did the testing process contribute to the software quality? If so, how?

Detailed reports and metrics from sub testing teams are usually presented and discussed in this stage. The goal is to assess the software’s performance and reliability. Here teams talk about test coverage and the effectiveness of the adopted testing approach, automated testing, manual testing or both.

Critical metrics used to measure the success of TestOps

The metrics used to measure the success of testOps depend on the software, though not entirely, here are metrics that are considered more critical.

Test coverage: This is a measure of how thoroughly the software has been tested. Coverage on its own or in general means “to what extent” or “how far.” If the test coverage is high, then your team has done a great job in testing all aspects of the software, from core functionalities to edge cases. Additionally, high test coverage means that your team has tested all essential parts and thus, it’s safe for release. Therefore, tracking test coverage is important, if test coverage is low, then your team needs to reassess and increase the number of tested features or code.

Test coverage can be any of these: code coverage, risk coverage, product coverage or scenario coverage. Most QA engineers perform other types of test coverage, either way, this metric measures the extent to which the software has been tested. This metric is typically calculated in percentage (%) that is, the number of code or features divided by the total number of elements that should be tested, then multiplied by one hundred.

Teams are mostly required to set coverage goals and focus on critical and high-risk areas of the software they want to test. One hundred percent test coverage is not always practical or necessary.

Test execution time: The number of tests tends to grow exponentially when the software you are testing begins to grow or scale. Whether the number of test cases are small or large in size or complex, short test execution times are desirable and thus help to speed up the feedback loop. Long test execution times on the other hand indicate issues especially when automated like in continuous integration or testing pipelines. Short test execution times don’t always mean your testOps strategy is efficient, most times it can be as a result of unintended shallow testing.

Therefore, testOps teams are required to closely track test execution times and ensure that tests are both efficient and comprehensive. It’s important to ensure that short execution times do not come at the expense of coverage or accuracy.

Feedback loop time: This is the duration it takes for the feedback from conducted testing activities to reach the appropriate stakeholders. Fast and efficient feedback loops are essential to maintain increased development speed and quality. Developers and testers collaborate more effectively if the feedback loop is timely. This metric is also affected by the test execution time. If the test execution time is prolonged the feedback loop is delayed. Therefore, teams are required to incorporate parallel testing to reduce test execution time and automatically generate testing reports to other stakeholders to accelerate the feedback loop time.

Test cycle time: This metric is all about measuring the time required to complete an entire testing cycle, from initial planning to the final reporting of results. Longer test cycle times indicate problems in the adopted testing strategy or testing process. In situations where new releases for software are frequent, long test cycle times can hinder delivery schedules and overall productivity. If your team has created a balance between speed and thoroughness in ensuring software quality on time, then the testOps process or strategy is efficient.

Other metrics are mostly generic and tied to the testOps team or software requirements, for example, the percentage of automatable test cases and defect-related metrics like defect detection rates and detection resolution percentage. Again, the metrics depend on the testOps team, and the complexity and nature of the software that is being tested.

How TestOps handles flaky tests and test debt

The primary goal of testOps is to ensure test activities are carried out in a structured manner. This also includes addressing testing challenges appropriately by implementing strategies to identify, manage, and resolve issues that compromise the reliability of testing processes.

Flaky tests are identified through inconsistent results and test debt caused by poorly testing design, inadequate test coverage, and a drift in project priorities. Again, these issues are almost impossible to avoid and therefore, the structured approach that a properly organized testOps strategy offers can help handle these cases efficiently. In testOps priorities are outlined, usually at the planning (test design) stage. If all priorities are addressed (whether automatically or manually) then test debt is minimized, keeping in mind that the test left to be carried out is of low impact at a particular time or phase of the software in question.

TestOps, again, is fundamentally about deciding on what testing methods or strategies to adopt and then learning from results and making adjustments in testing activities. Since testing processes are consistently analyzed and there is an established feedback cycle involved, the testOps teams can always generate reports to the engineering team or appropriate stakeholders highlighting the number of flaky tests identified, thereby enabling the engineering team to make code refactoring to eliminate the cause of inconsistencies. This collaborative approach is one of the benefits of testOps; analyzing results and communicating to the right stakeholders.

Risks of not adopting TestOps

If you don’t adopt testOps, even on a small scale; then your software is not qualified for release or in other words, not qualified for production. This isn’t to say that your code isn’t fit to be used, but having the rigor built into your releasing process that testOps provides, helps you to qualify that it is ready for production.  Software testing is a very important part of the software development cycle, and if software testing isn’t carried out in a structured and efficient manner, you should be ready to face the following challenges:

• Inefficient testing workflows: Software testing becomes a cumbersome process if not properly planned and standardized. Testing becomes disorganized and fragmented; leading to repeated efforts, wasted resources, and miscommunication. When testOps is in place (and done correctly), this doesn’t happen.
• Accumulated Test Debts: TestOps make sure priorities are set and tests are well-organized. If you and your team don’t adopt testOps, testing priorities may be misplaced, testing activities may be carried out haphazardly and you risk accumulating a high level of test debt.
• Inability to Scale Testing Efforts: Without testOps in place, testing becomes a burden and overwhelming as the software grows. At this point, you and your team will find it difficult to keep up with development and scale testing efforts.
• Lack of Transparency and Visibility: Without testOps, tests’ progress and results are not centralized, causing a lack of transparency. This makes it difficult for stakeholders to gain visibility into the status of the testing process; this can lead to misalignment between development and quality assurance teams.

Other challenges include slow feedback loops where test defects and issues will be delayed, thereby impacting the speed at which developers can address and fix problems, especially for Flaky tests, accidentally pushing defects to production due to inefficient testing practices, and so on.

Pitfalls Organizations Should Avoid when Transitioning to TestOps

While adopting testOps is a good idea, there are some pitfalls that you, your team and your organization as a whole should be aware of. These goes as follows:

• Improper planning: If there are no roadmaps or clear objectives defined, then your organization is not ready to adopt testOps. When specific objectives are established then the transitioning process is backed up with a solid framework to help move toward effective TestOps implementation.
• No dedicated team: Without a dedicated testOps team, your organization will face difficulties in managing and executing testOps processes; which will lead to inefficiencies and misalignment with development goals.
• Resistance to Change: The technology industry will always evolve. If your organization faces resistance from team members in terms of acquiring new skills/techniques, adopting new tools, workflows, or responsibilities then your organization is not ready for testOps, because the same applies to testOps. Resistance to change will hinder testOps process and reduce its intended value.
• Inefficient feedback cycle: Before transitioning into testOps there should be a feedback cycle established. This is because fast and efficient feedback cycles make stakeholders receive timely insights from test results. If an efficient feedback cycle is not in place, your organization risks delay in bug fixes, quality degradation, and frustration among stakeholders.
• Scaling too quickly: Even if there is adequate preparation in place, you shouldn’t attempt to implement testOps across the entire organization simultaneously. Instead, start small, refine the testOps process if needed, and scale gradually based on lessons learned. Trying to scale too quickly without solidifying the foundational processes can lead to wasted resources, confusion, and inefficient workflows.

Tools commonly used in TestOps to Facilitate Testing

Diverse tools can be integrated into testOps processes to optimize and streamline testing workflows. These tools fall into multiple categories and address testing, monitoring, and automation needs.

• Test management tools: These tools are responsible for managing, organizing, and tracking test cases and their execution. The tools that fall into this category are TestRail and Zephyr. TestRail is a web-based test case management tool. TestRail can be used to track all QA activities and is only available as a commercial product. Zephyr on the other hand is a test case management tool as well and can also be used to track all QA activities. Its test management features integrate well with Jira; which is good for teams already using Jira as their project management solution.
• Automation Testing Tools: TestOps tools that fall into this category are used to automate repetitive testing tasks. Tools like Selenium and Cypress fall into this category. Selenium is open source and is used for automating web applications for testing purposes, while Cypress is good for end-to-end testing of modern web applications. Other good tools in this category are Nightwatch, Playwright, and Puppeteer.
• Performance Testing Tools: Tools in this category measure the responsiveness, stability, and scalability of applications under varying conditions or workloads. Tools in this category are Apache JMeter, Gatling, Locust, BlazeMeter, and so on.
• Test Reporting Tools: Examples of tools in this category are Allure Report and ReportPortal. These tools don’t just provide an analysis of test executions, they also provide intuitive visualizations, logs, and metrics to keep teams informed and track test results effectively.

Conclusion

This article has introduced you to testing and the concept of testOps. In this article, you have learned testing concepts like flaky tests, test debts, and test operations (testOps). While testOps are for medium to large teams and organizations with complex projects, writing a simple unit test with Pytest, Jest, or Vitest and automating these tests with GitHub actions or Travis CI reflect a part of testOps, in a very small scale for solo developers.

With all you have learned in this article, what is holding you back from diving deeper into testOps and introduce it to your team? Please share your thoughts in the comments!