Breaking DevOps’ Cycle Of Overcommitment With Better Testing

Learn how implementing modern testing strategies and AI-powered tools can help teams prevent DevOps overcommitment.

Learn how implementing modern testing strategies and AI-powered tools can help teams prevent DevOps overcommitment.

June 23, 2022
Tamas Cser

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Learn how implementing modern testing strategies and AI-powered tools can help teams prevent DevOps overcommitment.
Breaking DevOps’ Cycle Of Overcommitment With Better Testing

In today’s fast-paced corporate environments, software development and testing teams experience a lot of demand and strain. Modern testing teams working with the DevOps model especially suffer from the ultra-competitive environments with brutally speedy and demanding work schedules. Large companies with work schedules that operate at a breakneck pace can often be the breeding ground for overcommitment. Similarly, technical debt can rear its ugly head as inefficient testing approaches cause teams to lose time.

A common form of technical debt is test maintenance overhead and keeping automated tests up-to-date. Unfortunately, it’s all too common for testing teams to spend a majority of their time keeping their existing tests updated. As a result, it becomes harder to deliver on automating more tests for new features and enhancements, causing development schedules to run behind.

The obvious solution here is better testing. Testing has evolved significantly over time. Gone are the days of old-school, legacy testing tools. You can achieve a lot more by making smart, insightful decisions in creating a test strategy that focuses wholeheartedly on sustainable test automation. You can break the cycle of pressure and overcommitment with automated tests that work properly. Testing teams now can go about doing their jobs in a much more relaxed, fun, and productive environment. This is especially significant for modern QA leaders as they bear the burden of the overarching decisions that govern such workflows.

Let us take a look at the common issues that can rise from DevOps overcommitment and how better testing can help deal with them.

DevOps and Legacy Testing

In this day and age, testing teams always face the need to get accustomed to development practices like Continuous Integration and Continuous Delivery, which lead to frequent releases and fast-paced development schedules. In both of these workflows, testing plays a crucial role in ensuring that a high standard of quality is maintained throughout the development process.

However, legacy testing practices can fall short of the demands of the DevOps workflow and become a principal cause of overcommitment and burnout. During the heyday of waterfall methodology, testing was largely done manually and would begin after the software had been completely developed. For this reason, it would be highly susceptible to errors and very labor intensive. It was common for the testing team to be an entirely separate entity from the development team. As a result, the process of finding and reporting bugs, getting them fixed, and then retesting would be a back-and-forth process that required more time and effort. Modern testing solutions in the DevOps environment can mitigate most of these challenges. However, there still remain certain issues that can lead to overcommitment issues.

In modern testing, automation plays a big role in smoothing out the testing process for QA teams. However, automation does have potential downsides. In many cases, it requires the writing of complex code. The failure rates can be high, and tests have to be carefully maintained as applications change over time. Test results need to be checked manually to ensure proper operation, since test failures may be due to issues with the application or test. All this can result in a growing amount of technical debt, leaving modern testing teams more work to do and less time to do it. For QA managers, this represents a critical conundrum that needs addressing.

Tailored Testing for DevOps

The ideal testing methodology for a DevOps environment is called continuous testing, in which testing is automated as much as possible and carried out throughout the software development life cycle. Every individual step involves different kinds of tests, dictated by the needs of the specific step. It is also one cohesive team that handles everything, instead of there being a separate testing team.

One of the most basic aspects of testing for modern QA teams is the “shift left” approach. This pushes testing to earlier stages of the development process. Bugs are, therefore, also found early on. This can go a long way towards improving general quality, reducing the burden on testing teams, and handling overcommitment. For QA leaders, implementing the “shift left” approach meaningfully and finding testing tools that can help accomplish this will be a priority.

Breaking the Overcommitment Cycle

In order to break the overcommitment cycle for DevOps with better testing, certain best practices become apparent. These are designed to increase test coverage, decrease technical debt, and maintain quality standards.

Smart Test Automation

First and foremost, it is crucial to embrace test automation, but in a smart and innovative way. Automation is the mainstay of being able to implement a continuous testing workflow. However, for test automation to work on the behalf of reducing DevOps overcommitment, it needs to be intelligently implemented.

In CI/CD development pipelines, the code is added to a central repository and automatically tested at once. Tests can include unit tests, acceptance tests, integration tests, and functional tests. Later into the development process, there will also be a call for performance tests, load tests, API tests, and endurance tests. The goal should be automating these tests as much as possible with a focus on reducing human intervention.

This is where smart test automation can be a real blessing. Modern testing platforms like Functionize leverage AI and machine learning to create smart tests. These tests avoid most of the pitfalls of legacy test automation with self-healing and self-maintaining tests that use AI to recognize visual elements and accounting for changes automatically. The result is reliable, fast, and fully automated testing that can also generate high-quality insight and reporting.

With Functionize, modern QA teams also have access to an easy workflow that does not involve coding. When coupled with quality test data, good tests cases, parallel testing, and a consistent evolution of the scope of testing, this can be a great formula to really make automated testing count and reduce the cycle of overcommitment for QA teams.

Test Metrics

Another best practice that is highly beneficial in DevOps is using metrics to constantly evaluate the performance of tests. With this evaluation, teams can stay on top of the complete picture regarding software quality, with concrete understanding of the effect code changes have on the testing process.

Functionize provides detailed reporting and dashboards full of rich testing metrics that provide actionable insight. Teams can track metrics like test failure rates, number and distribution of bugs, and test execution times. These, coupled with the use of AI, can help modern QA teams identify key areas of the software that are more highly prone to failures. With the use of historical data analysis and these metrics, tests can be focused more on these areas.

In fact, the use of AI can also pave the way to use predictive analysis. From historical data, the AI can calculate in advance the areas of the software that might possibly be vulnerable to issues. This can help teams create starting test suites that already focus on the problem areas while refining the tests as development progresses. This also presents a productive way for teams to write better test cases and turn out more effective test suites. This helps teams adhere to the prearranged release timeline without any additional stress or overcommitment.

Modular Testing

For QA managers, it can be a good idea to keep the test cases small. While certain areas of complex code might require more complex testing, keeping the tests small is a good idea in general. This is so that teams that clearly identify individual tests and ascertain their purpose and expected outcome. The data generated from these tests are also easier to understand and act on.

This introduces modularity in testing, which can be a boon in DevOps environments. Modular tests can be reused and repurposed. They can be chained together in different orders for different use cases. Overall, such a testing approach not only makes things faster and simpler but also easier to achieve better test coverage and eliminate technical debt.

This is also in line with another best practice in DevOps, Single Responsibility Principle or SRP. According to SRP, one specific part of an application’s functionality should be dictated by one specific class or module of the code. Modularity in both development and testing, when added up, can be distinct time-savers and really help break the cycle of overcommitment. In testing, validation can become more precise, and the quality can improve consistently.

Choose the Right Tool

Most importantly, the right test automation tool can make a large difference when a team is looking to avoid overcommitment issues, keep quality consistent, and still stick diligently to a fast-paced release schedule. Modern testing frameworks like Functionize, using the power of AI and machine learning, can help make the process of test automation more intuitive, effective, and speedy. Modern QA teams can easily create, edit, and repurpose tests and receive rich insights regarding all important metrics. The tests can self-heal and self-maintain, removing the need for human intervention and enabling teams to truly embrace the spirit of continuous testing.

With the right tool, QA leadership can effectively implement better testing. This, more than anything else, is a convincing way to deal with DevOps overcommitment.