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What is continuous testing?

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Overview

Continuous testing is the practice of executing automated tests throughout the software delivery lifecycle (SDLC) to get rapid feedback on business risks. Unlike traditional testing, which often happens late in the process, continuous testing integrates tightly with your continuous integration and delivery (CI/CD) pipelines and brings testing into every development stage. This tight loop of feedback helps teams find problems earlier and fix them faster.

Continuous testing

Why continuous testing matters

Continuous testing enables high-velocity teams to deliver reliable software at scale. The shift to agile and DevOps means faster release cycles, but speed without control leads to risk. Continuous testing acts as a safety net that evolves with development.

This is why development teams, organizations, and DevOps professionals use continuous testing:

  1. Faster feedback loops: Bugs are caught when they're easiest to fix, dramatically reducing the time between code commit and issue identification. This immediate visibility prevents small problems from becoming major blockers that could derail entire releases.
  2. Improved release confidence: Business stakeholders get better insight into risk before deployment, with real-time dashboards showing test coverage, pass rates, and potential business impact. This transparency enables informed go/no-go decisions based on actual risk assessment rather than gut feelings.
  3. Reduced cost of quality: Catching issues early avoids expensive rework that multiplies in cost as problems move through the pipeline. Fixing a bug in production can cost exponentially more than addressing it during development.
  4. Shorter release cycles: Testing is no longer a bottleneck; it's part of the flow. Automated quality gates eliminate the traditional "testing phase" that often delayed releases, enabling truly continuous delivery.

How continuous testing works

Continuous testing connects your testing automation with your continuous integration tools. Tests run automatically at key pipeline stages, and results feed directly into decision-making processes.

Continuous Testing workflow diagram for DevOps and CI/CD pipelines, detailing stages from source code commit to automated testing and reporting, including CI initiation, build, test execution, and feedback loop

Here's what typically happens:

  1. Commit code: A developer pushes code to a shared repository.
  2. Trigger CI pipeline: A CI tool automatically kicks off a new build process.
  3. Run automated tests: Automated tests execute in sequence, in parallel, or a combination of both: Unit tests, API tests, integration tests, UI tests, performance tests, security tests, and accessibility tests.
  4. Analyze & report: If any tests fail, the pipeline halts or alerts stakeholders with detailed reports.
  5. Improve & iterate: Teams fix issues, enhance test coverage, or adjust infrastructure.

This process, often referred to as testing automation for continuous development, keeps quality in lockstep with code delivery. The process loops continuously.

People, process, and technology

Implementing continuous testing isn't just about tools. It's a cross-functional effort that blends team culture, streamlined processes, and the right technology stack.

  1. People: Developers, testers, and operations must collaborate. Testing is no longer "someone else's job." This cultural shift requires breaking down silos and creating shared ownership of quality outcomes.
  2. Process: Shift-left testing practices and risk-based test strategies guide what to test and when. Teams must define clear quality gates, establish testing standards, and create feedback loops that inform both technical and business decisions.
  3. Technology: You'll need tools that support test automation, CI/CD integration, environment management, and analytics. The technology stack must be reliable, scalable, and provide meaningful insights rather than just test execution.

When these three pillars work in harmony, you gain more than coverage—you gain insight.

Continuous testing vs. automated testing

Many teams confuse automated software testing with continuous testing. While they share common tools and techniques, the strategy and outcomes differ dramatically.

Think of automated testing as the "what" and continuous testing as the "when" and "why."
This chart highlights the key distinctions—especially when it comes to integration, collaboration, and business value:

Category Automated software testing Continuous testing
Definition Use of tools and scripts to execute tests without manual steps Automated testing embedded in CI/CD to provide fast, ongoing feedback on business risk
When it runs Manually or on demand, often outside the delivery pipeline Automatically triggered during every stage of development and deployment
Goal & impact Improve efficiency by replacing manual test execution Reduce risk, accelerate delivery, and improve quality through real-time insight
Pipeline integration May be disconnected from CI/CD and delivery processes Fully integrated with continuous integration testing and deployment workflows
Team collaboration Typically owned by QA; limited collaboration Shared ownership between developers, testers, and DevOps teams

Continuous testing challenges and how to overcome them

Continuous testing brings big benefits, but it also introduces new complexities that can derail even the most well-intentioned implementations.

Common challenges that teams face include:

Unstable environments: Tests fail due to misconfigured or unavailable services, creating a nightmare scenario where teams lose confidence in their test results. Environmental instability can turn continuous testing from a safety net into a source of constant frustration, leading to "test blindness" where failures are ignored.
To overcome this, use containerized test environments for consistency. Containers provide identical environments across development, testing, and production. Tools like Docker and Kubernetes ensure that environmental differences don't cause test failures, while also enabling rapid environment provisioning and teardown.

Test flakiness: Inconsistent results erode trust in automation, forcing teams to re-run tests multiple times or, worse, ignore failing tests altogether. Flaky tests are productivity killers that can make continuous testing feel like a burden rather than a benefit.
To overcome this, adopt service virtualization to simulate dependencies: When external services are unavailable or unreliable, service virtualization creates predictable, controllable simulations. This approach eliminates dependencies on third-party systems and reduces test flakiness caused by network issues or service outages.

Long feedback loops: Slow test suites can delay the pipeline, defeating the entire purpose of continuous integration. When tests take too long, developers either skip them or batch changes, destroying the rapid feedback that makes continuous testing valuable.
To overcome this, prioritize and parallelize tests to shorten execution time. Run the most critical tests first and execute independent tests in parallel. Smart test selection based on code changes can dramatically reduce feedback time, while parallel execution maximizes infrastructure utilization. Getting continuous testing right requires discipline, but the payoff is worth it!

The continuous testing tooling landscape

Effective continuous testing relies on a set of integrated tools that support automation, orchestration, and visibility across the software delivery pipeline. These tools aren't just about executing tests—they ensure the right tests run at the right time, in the right environments, with meaningful feedback.

Here are the key categories of tooling to consider:

  1. Test automation frameworks: At the heart of continuous testing are automated test scripts for unit, API, UI, performance, and security testing. These frameworks provide structure for writing and organizing tests, executing them at scale, and reporting results consistently across test types. o9 Solutions found that they could accelerate test script creation by up to 70% with OpenText Core Performance Engineering.
  2. Test environment management: Reliable, production-like environments are essential for valid test results. Environment tools support dynamic provisioning, configuration, and isolation—often through containers or virtual environments. They also help simulate unavailable or third-party services through virtualization or mocking techniques.
  3. Test data management: Good tests need good data. These tools enable teams to generate, mask, or refresh test data sets across environments while ensuring compliance with privacy regulations. Proper test data reduces flakiness and increases confidence in test outcomes.
  4. Test reporting and analytics: Continuous testing produces a high volume of test results. Reporting tools help distill that data into actionable insights—identifying trends, highlighting regressions, and supporting go/no-go decisions based on business risk.
  5. Collaboration and governance tools: Finally, tools that enable version control, traceability, and auditability play a vital role in aligning testing with development, security, and compliance requirements.
  6. CI/CD orchestration tools: These tools trigger automated tests in response to code changes. They manage the flow of builds, tests, and deployments, ensuring that testing is embedded into every stage of delivery. They also allow for pipeline customization, conditional logic, and integration with notifications and analytics systems.

Strengthen your continuous testing strategy

Continuous testing is only as strong as the platform behind it. Whether you're scaling automated software testing, improving test environments, or integrating quality gates into your DevOps workflows, OpenText can help you get there faster—with less risk.

Explore our testing solutions and our software delivery platform to see how we're helping teams deliver quality at speed.

Related products

OpenText™ Functional Testing

Accelerate test automation with the power of AI

OpenText™ Performance Engineering

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OpenText™ Core Software Delivery Platform

Supercharge efficiency and deliver business value with a seamless, connected, end-to-end DevOps platform fully powered by SaaS

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Footnotes