Continuous Testing for the Cloud Native Era

The modern cloud native stack excels at automation and control, enabling automated deployments for faster and more reliable releases.  In today’s landscape, where a single deployment can impact millions of users, the stakes for quality have never been higher. We version control our infrastructure, applications, and even documentation, but the tests are scattered across the CI pipeline, local machines, or shared environments. 

We’ve built sophisticated cloud native platforms that can automatically scale, heal, and update themselves. Yet, our testing practices are stuck in the past and often prove to be bottlenecks in our delivery pipelines. This disconnect between traditional testing practices and modern deployment capabilities hinders business velocity.

In this blog post, we’ll look at the challenges with traditional testing practices in the cloud native era and understand the need for continuous testing.

Testing Challenges When Going Cloud Native

The mismatch between modern deployment practices and legacy testing methods can create several challenges. Let's examine some of them.

Current Challenges

Testing in most organizations is a reactive process triggered by code commits or scheduled runs. This approach leaves significant gaps between deployment and validations. When tests are executed in isolation, issues arise late in the deployment cycle, making fixes costlier and more complex to implement.

Microservice architecture leads to environment inconsistencies. For instance, the production environment would leverage Kubernetes and GitOps practices, while the testing environment often relies on manual configuration. This leads to configuration drift between developers’ local setups, CI pipelines, staging, and production. 

Modern observability tools provide deep insights into applications and infrastructure, but test coverage often remains opaque and disconnected. This poor visibility affects the team’s ability to track which microservices were tested adequately, which is a challenge, especially as the number of microservices grows.

The “works on my machine” syndrome is amplified in cloud native scenarios, as a test passing locally might fail in CI due to differences in environments, such as containers, networks, and security policies.

Business Impact

These challenges are technical; however, they can adversely impact business outcomes. 

Your releases can be delayed when the test environment doesn’t accurately reflect the production setups. In such situations, teams struggle to resolve environment-specific issues, which also affects their overall productivity. 

Further, your engineers spend hours debugging tests that arise due to environment inconsistencies rather than actual code. A simple deployment that should have taken a few minutes can stretch for a few days as teams figure out the reasons for the failure of the tests.

This adds to your costs as organizations maintain multiple test environments—development, staging, QA, and pre-production—each with its own configuration, adding to the maintenance overhead. The costs also multiply with every new service added to the ecosystem. 

This ripple effect first affects the team’s confidence in testing, which means the team either delays deployment to conduct extra tests or releases them with reduced coverage, which eventually adds to the technical debt. This debt compounds over time, making the test suite unreliable.

Continuous Testing: A Strategic Necessity

As cloud native becomes the default way to build and deploy applications, it introduces more complexity, and traditional testing no longer suffices. Applications are broken down into smaller pieces which are deployed on cloud-hosted infrastructure and loosely coupled via event driven architectures. That’s where continuous testing becomes a strategic necessity to ensure continued integrity of your applications functionality. 

Continuous testing adds validation to every phase of the development cycle. Instead of treating testing as a phase, it becomes part of every stage. For instance, when an interface definition changes, API contract tests run automatically. At the same time, organizations can leverage chaos testing practices to continuously verify system resilience in Kubernetes clusters. 

Integrating testing earlier in the development cycle—shift left—ensures that developers run integration tests locally by setting up ephemeral environments. At the same time, automated security scans can validate the dependencies during code commits. Simultaneously, you can extend testing to production using canary deployments to ensure real-world validation of microservices behavior. 

Take The Shift Right Advantage

Early testing helps you catch many issues, but production environments present unique challenges that can only be validated under real-world conditions. Progressive delivery practices enable safe testing in production, complementing the shift-left approach. 

Techniques like canary route a small percentage of traffic to a new application version, allowing teams to validate the performance with actual user behavior. You could use feature flags for fine-grained control that enables teams to perform A/B testing in real-world scenarios and gradually enable new functionality. 

Such practices provide insights that are difficult to discover in staging environments. Utilizing these practices with monitoring and chaos engineering guarantees reduced deployment risks and shorter feedback loops between development and real-world usage.

Implementing Continuous Testing in a Cloud Native Infrastructure

Treating test suites with the same rigor as production workloads is key to successfully implementing continuous testing. With Kubernetes powering most of the cloud native applications today, you want your traditional tests to be converted to Kubernetes resources so that each of them is versioned and follows a declarative manifest that can be deployed and managed like any other Kubernetes resource. 

From API tests to end-to-end system tests, all must be version-controlled alongside the application code to enable GitOps practices for managing tests. This approach ensures that test environments are reproducible and mimic the production environment.

Provisioning your environment must be code-driven and use Infrastructure as Code to spin up isolated test environments that mirror production configurations. These ephemeral environments, provisioned for test execution, are torn down, eliminating any configuration drift and reducing costs and maintenance overheads. 

Testkube brings all of these practices together in a Kubernetes environment. It transforms your existing tests from tools like Cypress, Postman, or k6 to Kubernetes resources, making them deployable through standard Kubernetes tools. 

With Testkube, teams can:

• Orchestrate test execution across different environments
• Configure the execution of  tests and their dependencies in a single yaml file - as a Kubernetes resource
• Get consolidated test results and metrics with a built-in dashboard
• Integrates with CI/CD tools like GitHub Actions, Jenkins, and ArgoCD, also with CI tools like CircleCI

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Testkube provides a standalone Open Source Agent that is deployed in your Kubernetes infrastructure for vendor-agnostic test execution and a commercial Control Plane that can be used to manage multiple agents with additional features for parallelization, orchestration, RBAC, centralized troubleshooting and reporting, etc.

Business Case For Continuous Testing

Every minute of downtime not only impacts customers but also impacts your revenue. Hence, continuous testing becomes a competitive advantage and a business differentiator that is just a technical practice. 

With continuous testing, organizations can reduce time-to-market while maintaining high quality standards. By detecting issues early in the development cycle, organizations can reduce the fix costs up to 100% compared to fixing issues in production. At the same time continuous feedback loops help prevent defect leakage to your customers. 

Further, instead of running the entire test suite for every change, you can implement risk-based testing to execute only relevant tests. This effectively utilizes your cloud resources, as environments are spun up only when needed and scale based on test demands. This can help reduce testing infrastructure costs by up to 50%.

With quicker feedback loops, developer productivity boosts. When developers receive test results in minutes rather than hours, they can fix issues immediately, speeding up the development process and improving code quality. 

To sum up, continuous testing is a strategic need and not just another technological adoption. As organizations continue to build and deploy on cloud, those who implement continuous testing will be positioned to deliver high-quality applications faster and more reliably.

Reach out to us to discover how Testkube can help you implement continuous testing. You can also join our Slack community to start a conversation or read Testkube documentation. The question isn’t about whether to adopt continuous testing, but rather how quickly you can begin your journey.