Use Cases

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Scenario #1: One Shared Service for Every Team

Thirty teams, thirty ways of running agent-written tests, and an auditor asking how test selection is decided.

Scenario #2: Scripts to Manage the Scripts

Someone built a testing platform nobody decided to build. One person understands it, and that person has given notice.

Scenario #3: The Agents Tested It. Nobody Knows What.

Each agent runs its tests in its own sandbox. When the VP asks what the agents tested last week, nobody can answer.

Replace SaaS Load Testing with Your Own Kubernetes Clusters

You already own a load testing platform. Stop paying a SaaS per virtual user and run k6, JMeter, and Gatling in-cluster.

AI Test Authoring

Test coverage falls behind because writing tests does not scale. Describe a test in plain language, and Testkube writes it in your framework and runs it on real infrastructure.

AI-Driven Test Selection for Smart Suites

Running every test on every commit wastes time and infrastructure. Testkube AI agents read the diff, classify the change, and run only the tests that map to it.

Flaky Test Detection & Diagnosis with AI

When a test fails in Kubernetes, the cause is often your cluster, not your code. Testkube gives platform engineers the observability and AI analysis to tell the difference, fast.

Cross-System Root Cause Analysis

Give agents access to source code, infrastructure, and observability tools to correlate test failures with what's actually happening across your environment.

Automated Remediation

Go beyond analysis. Let AI agents diagnose failures, propose fixes, and open pull requests, with human review built in.

Advanced Troubleshooting & Failure Analysis

Connect agents to GitHub, Kubernetes, and observability tools so they can correlate test failures with code changes and infrastructure state automatically.

Infrastructure Testing in Kubernetes

Learn some infrastructure testing strategies to ensure production readiness.

Geo-Distributed Clusters with Multi Cluster Kubernetes

For production environments with geo-distributed clusters, Testkube ensures that all clusters run the same tests, helping to manage multi-cluster Kubernetes environments.

ArgoCD + Testkube = Better Together

Implementing GitOps for application and infrastructure operations has numerous benefits around version control, collaboration, and rollbacks.

Automated Testing in Cloud Native CI/CD Pipelines

Transform automated testing in cloud-native environments with Testkube's K8s-native test execution control plane that eliminates the complexity + friction of integrating testing into CI/CD pipelines.

Ephemeral Environment Testing in Kubernetes

Ephemeral environments are becoming the standard for fast-moving software teams. Test every branch, run every PR, and keep every result—even in short-lived environments with Testkube.

Reliable Local & Ephemeral Kubernetes Testing

Testing Kubernetes applications shouldn't wait until staging or rely on fragile, manual scripts. Bring production-grade testing to every developer environment with Testkube.

Scale Your K6 Tests

Testkube is a better orchestration platform for K6 scaling. It also provides heterogenous support for all testing tools, not just K6.

Geo-Distributed Load + Functional Testing with Testkube

Applications used by geographically-dispersed users can require load+functional testing from multiple locations. Run tests from any region using your own clusters and full control with Testkube.

Optimize Kubernetes Resource Usage for Automated Testing

DevOps + platform engineering teams need to allocate the right K8s resources to pods for automated testing. Identify resource consumption with Testkube's dashboard to manage K8s cost management.

Leverage Existing Kubernetes Infrastructure for Test Execution

Consider insourcing test automation execution to your existing K8s infrastructure. Insourcing involves moving many test executions from these cloud testing platforms to on-premise infrastructure.

AI-Assisted Test Debugging

When running automated tests in your CI-CD pipeline: debugging adds up. Now AI-assisted debugging finds root cause of test failures in minutes, not hours.

AI-Fueled Development is Reshaping Automated Testing and CI/CD Pipelines

AI is making it easier to scale test creation, and platform teams are already raising the bar on quality expectations. Continuous Testing addresses the bottlenecks created by the new "AI velocity.""

AI SDLC

See what your AI agents tested, where it ran, and what passed, with every run landing in one place inside your infrastructure.
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Artificial Intelligence

Leverage AI-powered insights to debug faster and ship with confidence in the age of AI-generated code.
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Accelerate Application Delivery

Ship faster with confidence. Automate testing at every stage of your pipeline to support modern development practices.
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Improve Application Quality

Ensure consistent quality across geographies and environments with comprehensive testing orchestration.
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Reduce Costs

Optimize infrastructure spending by leveraging existing Kubernetes resources for efficient test execution.
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Run any test, anytime, anywhere

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