Overlooked Bottlenecks in Automated Testing (and How to Fix Them)

The traditional QA testing process has been pushed beyond its limits by the pace of modern development. Accelerated release cycles, increasingly complex architectures, and a pervasive, zero tolerance attitudes towards defects are making it more and more difficult for QA teams to ensure speed, accuracy and confidence in every release.

QA automation may seem to be the obvious answer to this systematic issue. Especially thanks to the continued advancement of AI, automation is a more attractive option than ever to ensure fast feedback loops, early bug detection, and cut long-term costs. But — as is the case when introducing any new technology — diving head first into a solution without the necessary preparatory work is asking for trouble. A sustainable automation process requires a structured framework design, reusable components and, most importantly, continuous optimisation. If ambition outpaces the automation framework you have in place, then your testing process will undoubtedly become unsustainable.

One of the biggest barriers to automated processes is the hidden manual dependencies that slow down test execution. It may sound contradictory, but manual dependencies in an ‘automated’ process are a common cause of bottlenecks. Whether from manual inputs required to start the automation or engineers needing to step in to fix recurring issues caused by an unscalable automation procedure, they can delay releases, reduce confidence in a product, and increase engineering overhead.

An Outcome-Focused Approach to Automated QA Testing

The key to avoiding these systematic issues — whether working in-house or with a QA partner — is to ensure that you understand how critical it is to lay the groundwork of a scalable framework for automation before setting it to work.

Let’s look at a practical example. Engineering Insights was approached by a business looking to help improve their QA test automation scalability and generally improve their processes, as their existing flow was being interrupted by manual user processes, slowing down releases and limiting test coverage. Each test run involved multiple manual steps through the authentication flow, including the creation of a user profile and full verification of a new email address, preventing a reliable CI/CD execution. Once these credentials had been manually prepared, only then could the fully automated stage begin. An automated process that relies on any level of manual input can never be truly scalable and begs the question: could this even be considered an automated process?

Before Automation: Manual Steps

As the client’s product grew, this process was becoming increasingly unsustainable. Every new service added, every environment shift caused by changes and updates, and every database reset complicates processes, resulting in further automated testing bottlenecks in the QA pipeline.

These issues are systematic when it comes to automated QA testing processes. No matter how competent your team is, incremental manual changes can have huge knock-on effects to automation processes, resulting in further manual interference when engineering teams are required to step in to maintain the testing process. It also goes without saying, that time spent fixing recurring issues, is time that your engineering experts are not working on innovation elsewhere. The impact of automated QA testing bottlenecks can insidiously spread throughout the entire business.

The goal of introducing automation to your processes should be to move away from fragile, error-prone setups towards self-sufficient, easily repeatable test systems. The moment a testing process can move entirely away from any manual input, not only is the process now fully automated, but it opens the door for true scaling.

Automation in Practice

With the client having identified the limitations on their semi-automated process, work could begin to shift towards full automation. Engineering Insight’s scalable solution involved generating unique users dynamically and completing email verifications without human oversight. As well as this, the solution would need to remain stable after database resets, flexible to any environmental shifts, and be fully repeatable.

After Automation: Fully Automated, No Manual Dependency

With a new solution built and in place, the entire registration and verification flow was fully automated as part of the test setup. Each test run generated a unique email, completed the registration, retrieved and processed a verification email, and, finally, activated the account — all without any manual input required.

The impact was immediate, unlocking authenticated flow coverage for the client for the first time. Test setup time was reduced significantly from 5-7 minutes to under 30 seconds, while simultaneously reducing engineering overhead by eliminating 8 manual user provisioning steps per test run. With fully automated CI/CD test execution, the solution had increased automation coverage for critical authenticated and end-to-end flows, improving test stability even after database resets and environment shifts. Most critically however, the solution enabled test automation scalability, transforming automation into the accelerator it’s supposed to be, as opposed to the constraint it had become.

The Future of QA Testing

While this is just one example, it’s far from an isolated incident, and accurately forecasts a lot about the future of quality assurance testing. While previously QA was always treated as a step in the delivery — a gatekeeper at the end of a pipeline, frantically working to ensure no bugs or faults slip through — it’s clear that this approach is unsustainable to the more demanding future of development. What’s also clear is that most QA challenges are not tooling issues: they are process and architectural issues. As the pace of modern development continues to increase, the rigidity of QA models needs to adapt towards a more flexible, scalable and rapid model to keep pace. Rigidity leads to things breaking; flexibility results in their ability to expand.

Key to enabling this newly crucial flexibility is the ability to increase test automation scalability by separating it entirely from manual dependencies. True QA maturity can only come from effective automation with easily repeatable tests and environments. With this approach, QA can move beyond being seen simply as a final test and position itself as a growth enabler by empowering larger test suites, more realistic user journey testing and faster, safer releases.

Are Hidden Testing Bottlenecks Disrupting Your QA Process?

If you think that your QA processes aren’t running as seamlessly as they could be, get in touch to learn more about how Engineering Insights can improve your QA maturity.

With an outcome-focused approach, we deliver frameworks that reduce regression testing from weeks to hours, expand coverage and integrate seamlessly into your business.

If you have a fast-moving product and platform team that requires speed, accuracy and confidence in every release, then you can’t afford to risk hidden bottlenecks causing disruption. Get in touch today to learn more.