QA’s role in a cloud move: before, during, and after

Moving to the cloud is becoming a standard part of business today. It promises agility, speed, and innovation. However, that promise often comes with complexity.

We have all heard the stories or perhaps lived them. Projects take longer than planned. Final costs are a surprise. And when systems finally go live, users find bugs that should have been caught months ago.

To avoid these issues and ensure project success, quality assurance must be treated as a strategic partner from day one. Rather than acting as a testing team brought in at the end, QA functions as a continuous process to manage risk throughout the project life cycle.

In the article, let’s analyze.

Before the move

This is where you lay the foundation for success. This stage prepares the ground for the entire project. The goal is to identify risks, define success criteria, and build a robust plan. Skipping this step is like migrating blind.

Preventing surprises with a risk-first strategy

QA’s first job is to ask what could go wrong. Together with architects, they identify high risk areas of the application and their critical functionalities, along with complex integrations and key data flows. This collaboration shapes the overall test strategy and specific test plans, and helps define quality gates, which are checkpoints the project must pass. The business benefit is de risking software delivery. By identifying expensive problems early and planning how to mitigate them, the team prevents budget busting surprises later.

Defining what success looks like

How do you know if the new cloud system is an improvement? First, business and technology leaders agree on what success means in practical terms. That might include more reliable customer journeys, stronger brand perception through fewer incidents, or lower operating costs compared with on premises hosting.

From there, the team selects a small set of performance and experience indicators that express those goals, such as response times for key user journeys, availability targets, and the volume of concurrent users that must be supported. QA makes sure these expectations are testable and that there is a clear baseline from the existing system, using results from earlier performance work and production monitoring.

After the migration, results from performance tests and live system metrics show whether the new environment meets or exceeds those expectations. These same measurements also support the ROI story for both the migration and any further test automation and optimisation.

Building the engine for speed and safety

What about legacy test scripts? In most cloud projects, the application and its architecture change significantly, so test automation also has to evolve. QA teams review which existing scenarios are still relevant, then design a focused automation suite for the target cloud environment, reusing only what remains reliable. The benefit is speed and reliability. This framework accelerates both the migration itself and future development in the cloud.

Planning for new cloud-native challenges

The cloud brings unique complications. QA needs to plan for them:

• Data and logic integrity. QA validates that data arrives in the target cloud system complete, consistent, and usable. Typical checks include comparing record counts and key aggregates across source and target, and confirming that core business workflows still behave correctly with migrated data. The goal is to ensure that data movements and transformations do not break business rules or reporting.
• AI-powered planning. Architects, developers, and QA can increasingly use GenAI tools to scan code bases and integration maps to highlight complex areas that merit extra testing. Similar techniques can support data validation by spotting anomalies or unexpected patterns in migrated datasets. Used alongside expert review, this gives teams an additional signal when estimating effort and deciding where to focus risk based testing.

During the move: the command center in action

As apps and data start moving, QA stays embedded in the command center, validating components in real time as they land in the new environment.

Protecting the crown jewels: automated data checks

This is a critical task during the transfer. As data moves or is transformed, automated tools run checks like row counts and checksums. This acts as a strong safeguard against catastrophic data issues, providing high confidence that the data arriving in the cloud is complete, consistent, and aligned with the migration rules.

Automated functional scans

The process is often too fast to test everything manually. Running everything continuously can be noisy during active migration. QA prioritizes the automation of critical business journeys and the migration runbook itself first, expanding coverage to edge cases only once the environment stabilizes.

Functional and integration testing

While automation runs, human testers perform exploratory and structured functional tests on the target system with migrated data, checking complex connections between services. Together, automated and manual testing ensure core business processes, often supported by multiple applications, remain functional and undisrupted.

Security and compliance checks

Moving to the cloud can open unexpected security gaps across the source environment, the migration channel, and the new cloud platform.

Security and QA teams work together on vulnerability scans, configuration reviews, and, where appropriate, penetration testing. Security requirements and acceptance criteria are defined up front, and test suites are designed to verify them. The benefit is reduced risk of breaches or fines and stronger alignment with regulations such as GDPR or HIPAA.

Migration rehearsals and resilience testing

You do not want the go live night to be your first attempt. QA supports dry runs in a staging environment to rehearse the real migration end to end. These rehearsals validate that source systems can provide data at the expected pace, that the target cloud platform can absorb and transform that volume, and that the migration tools and channels are secure and stable. They uncover hidden problems and validate the rollback plan. QA may also work with SRE teams on resilience testing, including selected chaos experiments, to check that the system can recover from failures. Together, this gives the business confidence in the cutover timeline and the rollback procedures.

After the move: from stable to optimized

You are live. The work now shifts from defense to optimization. The system is running, and the new goal is making it stable, fast, and cost-efficient.

Post-migration validation (automated smoke testing)

The moment the system is live, QA runs fast automated smoke tests to check critical business functions. Can users log in? Can a customer complete a purchase? This provides immediate confidence to stakeholders that critical functions are operational at the moment of cutover.

Performance and load testing (simulated peak load)

The system works, but does it scale? QA compares the new system’s performance to the baseline captured earlier. They simulate peak traffic, like a Black Friday rush, to ensure the cloud environment handles the load as expected. This protects the customer experience and confirms the system is ready for growth.

Conclusion: your playbook for success

Viewing QA as a continuous process through the before, during, and after stages reveals its true value in ensuring project success.

The risks of neglecting this are real: failed projects, data issues, security gaps, and unexpected costs. A strong, end-to-end QA strategy acts as the project’s playbook, turning a high-risk initiative into a controlled, well-executed transition. This approach helps you migrate to the cloud ready to succeed.

Ready to move to the cloud without the headaches? Contact a1qa’s experts today