8 Alternatives to Jenkins for Testing in Kubernetes

Jenkins was built to automate builds. Somewhere along the way, teams started using it to orchestrate tests too. And for a while, that worked well enough.

But if you are running Kubernetes in production and your test suite has grown past a handful of unit tests, you have probably noticed the cracks. Pipelines that take 45 minutes because tests run sequentially. Plugin conflicts that break your test stage after an upgrade. Groovy scripts that only one person on the team understands. Flaky results because the Jenkins agent environment does not match your actual clusters.

Jenkins is still a solid CI/CD tool. It is not a testing platform. And treating it like one costs you time, reliability, and engineering hours you could spend shipping features.

This post covers eight alternatives for teams that need testing to work natively with Kubernetes, not as an afterthought bolted onto a build pipeline. Some are direct Jenkins replacements for CI/CD. Others, like Testkube, are a different category entirely: a testing layer that works alongside whatever CI/CD tool you choose.

1. Testkube

Best for: Teams running Kubernetes in production that want to decouple test execution from CI/CD pipelines.

Testkube is a test orchestration platform that runs tests directly inside your Kubernetes clusters as native K8s jobs. Instead of embedding test logic into your Jenkins pipeline, you define test workflows in YAML, store them in Git, and execute them independently of any CI/CD tool.

The core difference from Jenkins: Testkube treats testing as its own concern, separate from CI/CD. It is not a Jenkins replacement. Jenkins (or whatever CI/CD tool you use) still handles builds and deployments. Testkube handles test execution, parallelization, reporting, and artifact collection. The two connect through triggers and webhooks, but neither depends on the other. Most teams that adopt Testkube keep their CI/CD tool and add Testkube as the testing layer.

Jenkins is a CI server at heart. It was originally built to automate builds, not to orchestrate tests at scale. Relying on third-party plugins, manual maintenance, and limited scaling introduces real operational risks. Testkube is a Continuous Testing platform built for cloud-native organizations, delivering reproducible test execution across clusters, unified testing workflows, real-time debugging, and test automation that works out of the box.

Why Testkube over Jenkins for testing

Kubernetes-native execution that scales with your infrastructure. Jenkins was built for VM-based workload management. Scaling requires careful capacity planning and manual agent provisioning. Testkube runs your tests as first-class Kubernetes workloads, taking full advantage of horizontal scaling and growing naturally alongside your applications without additional infrastructure overhead.

Vendor-agnostic testing for any framework. At scale, you need to run everything from UI and API tests to load, security, backend, microservices, and cloud integration tests. Testkube is vendor-agnostic: Playwright, Cypress, Selenium, Postman, JMeter, k6, pytest, custom scripts. As long as it can be containerized, Testkube runs it inside your existing infrastructure as Kubernetes jobs.

Built-in observability and faster debugging. Jenkins buries test results within individual builds, offering no high-level overview and making cross-pipeline test navigation difficult. Results can also be deleted quickly. Testkube maintains complete, searchable execution records with real-time logs, artifacts, pod events, and AI-assisted debugging, giving teams both a unified view of testing activities and faster troubleshooting.

Lower maintenance and no scripting or plugin dependencies. Jenkins needs custom scripts and plugins to talk to different testing tools and Kubernetes, which leads to fragile setups and configuration drift. Testkube uses a consistent, declarative way to define test workflows, stores tests as CRDs, and provides multiple ways to trigger tests with role-based access. No plugin sprawl, no script maintenance.

Designed for DevOps and GitOps workflows. Commit-based triggers, Git-based workflow definitions, ephemeral test environments, and multi-cluster deployments all work seamlessly. Tests can be triggered by CI (Jenkins), CD (Argo CD or Flux), on a schedule, manually, based on Kubernetes events, or through AI agent workflows via MCP Server and the Testkube API.

Centralized results across the entire team. Results, logs, and artifacts are centralized in a single dashboard that everyone on the team can access, including QA, product, and engineering. DocNetwork reported that this visibility alone saved them 30 DevOps hours per week because they no longer needed weekly deployment coordination meetings.

Testkube vs Jenkins: Platform architecture

Testkube vs Jenkins: Testing capabilities

Testkube vs Jenkins: Developer experience

Trade-offs: Testkube requires Kubernetes. If your infrastructure is not on K8s, this is not the right tool. There is also a learning curve around test workflows if your team is used to defining everything in Jenkinsfiles. The shift from "tests embedded in pipelines" to "tests orchestrated independently" takes some adjustment.

Pricing: Free open source tier. Paid plans use predictable, seat-based pricing rather than consumption-based billing.

2. GitHub Actions

Best for: Teams already on GitHub that want CI/CD and basic test automation in one place.

GitHub Actions runs workflows directly from your repository. For teams that moved to GitHub from Jenkins, the appeal is obvious: no separate server to maintain, no plugin ecosystem to manage, YAML-based configuration stored alongside your code.

For Kubernetes testing specifically, GitHub Actions can spin up ephemeral environments using tools like kind or connect to existing clusters through service account tokens. You define your test steps in a workflow file, and GitHub's hosted runners handle execution.

Where it works well: small to mid-size teams running straightforward test suites. If your tests are self-contained and do not need to interact with services inside your cluster's network, GitHub Actions can handle the job without much configuration.

Trade-offs: Tests run on GitHub's hosted runners, not inside your Kubernetes clusters. That means your test environment does not match production. For teams with strict data sovereignty requirements (a concern we heard repeatedly from enterprise prospects), test data leaves your infrastructure. Parallelization is possible but requires matrix strategies that get complex fast. No native test reporting; you are reading logs or piping results to external tools. And once your test suite grows, the per-minute billing adds up.

3. GitLab CI/CD

Best for: Teams using GitLab for source control that want an integrated pipeline experience with Kubernetes runners.

GitLab CI/CD has a meaningful advantage over GitHub Actions for Kubernetes testing: you can run GitLab Runners inside your cluster. Tests execute as pods in your own infrastructure, which gets you closer to environment parity than GitHub's hosted runners.

The Auto DevOps feature can detect your project type and generate a pipeline that includes testing, but most teams outgrow the auto-generated configuration quickly and end up writing custom .gitlab-ci.yml files anyway.

Trade-offs: GitLab CI/CD is still a pipeline tool, not a test orchestration tool. Test execution is tied to your pipeline stages. If you want to run tests on a schedule, after a deployment, or on demand without triggering a full pipeline, you are writing workarounds. The Kubernetes runner integration helps with where tests run but does not solve how tests are organized, reported, or scaled independently. If your team uses GitHub or Bitbucket for source control, GitLab CI/CD is not a practical option.

4. Tekton

Best for: Platform teams building custom Kubernetes-native CI/CD from the ground up.

Tekton is an open source framework for building CI/CD pipelines that run as Kubernetes-native resources. Tasks and pipelines are CRDs (Custom Resource Definitions), which means they are managed the same way as any other Kubernetes object.

For teams that want full control over their pipeline architecture, Tekton is genuinely powerful. You can build exactly what you need. Testkube actually integrates with Tekton for teams that want Kubernetes-native pipelines paired with purpose-built test orchestration.

Trade-offs: Tekton gives you building blocks, not a finished product. There are no native testing concepts: no test suites, no test matrices, no sharding, no built-in reporting. You are writing significant custom YAML and scripting to get test orchestration behavior that purpose-built tools provide out of the box. The maintenance burden is real. For teams with dedicated platform engineering resources, this can work. For teams that need to move fast, the setup cost is hard to justify.

5. Argo Workflows

Best for: Teams already using Argo CD for GitOps that want workflow automation in Kubernetes.

Argo Workflows is a Kubernetes-native workflow engine that defines workflows as CRDs. It handles DAGs (directed acyclic graphs), parallelism, retries, and artifact passing natively. If your team is already invested in the Argo ecosystem for deployments, Argo Workflows is a natural place to look for test automation.

It runs in your cluster, scales with Kubernetes, and integrates with the GitOps workflows your team likely already has in place.

Trade-offs: Argo Workflows is a general-purpose workflow engine. It does not know what a test is. There is no concept of test suites, test results, pass/fail reporting, or test-specific artifacts. You will build all of that on top of it. For teams running a handful of automation tasks, that is manageable. For teams with complex test matrices across multiple environments, the custom scripting required starts to look like maintaining an internal testing platform. At that point you are choosing between building the thing or buying the thing.

6. Sauce Labs

Best for: Teams that need broad browser and device coverage for UI testing.

Sauce Labs is a cloud-hosted testing platform focused on cross-browser and cross-device testing. It maintains a large grid of real browsers and mobile devices, which makes it the go-to choice for teams whose primary concern is "does our app work on Safari 17 on an iPhone 15."

For that specific use case, Sauce Labs is hard to beat. The device coverage is extensive, the infrastructure is managed, and the setup is fast.

Trade-offs: Sauce Labs tests run in their cloud, not in your Kubernetes clusters. There is no environment parity with your production infrastructure. If your testing needs go beyond browser and device testing (API testing, load testing, integration testing, security testing), you are either running a second platform or stretching Sauce Labs beyond its strengths. The consumption-based pricing scales with usage, which means costs can spike unpredictably as your test suite grows. And for teams with data sovereignty requirements, having test execution leave your infrastructure entirely is often a non-starter.

7. BrowserStack

Best for: Similar to Sauce Labs. Browser and device testing with a managed grid.

BrowserStack offers the same core proposition as Sauce Labs: a cloud-hosted grid of browsers and devices for UI testing. The device lab is comparable, the setup experience is similar, and the trade-offs are nearly identical.

Where BrowserStack differs slightly: its Automate product has a bit more flexibility for Selenium and Appium-based test suites, and its pricing structure has different breakpoints that may work better depending on your team size and test volume.

Trade-offs: Same fundamental limitations as Sauce Labs. Tests run outside your infrastructure. Not Kubernetes-native. Consumption-based pricing. Limited to UI and browser testing. If your testing needs are broader than "does this render correctly in Chrome, Firefox, and Safari," you will need additional tooling.

8. CircleCI

Best for: Teams that want a managed CI/CD platform with strong parallelism for test suites.

CircleCI is a cloud-hosted CI/CD platform with a good story around test parallelism. Its test splitting feature can distribute tests across multiple containers based on timing data from previous runs, which helps keep pipeline times down as suites grow.

For teams migrating from Jenkins that do not necessarily need Kubernetes-native testing, CircleCI removes the operational burden of maintaining a Jenkins server while improving test execution speed through parallel containers.

Trade-offs: Tests run on CircleCI's infrastructure, not yours. The parallelism is useful but operates at the CI/CD level, not the Kubernetes level. You cannot test how your application behaves inside a Kubernetes pod because your tests are not running inside Kubernetes pods. The self-hosted runner option exists but adds back the operational overhead you were trying to avoid. Credit-based pricing means you are paying for compute time, which gets expensive at scale.

Side-by-side comparison

When to use what (decision guide)

Start here: Where do your tests need to run?

If the answer is "inside our Kubernetes clusters, in the same environment as production," your options are Testkube, Tekton, or Argo Workflows. Everything else runs tests outside your infrastructure.

Next: How much do you want to build versus buy?

If you have a dedicated platform engineering team and want full control over every piece of the testing pipeline, Tekton or Argo Workflows let you build exactly what you need. If you want test orchestration that works out of the box (reporting, parallelization, artifact collection, multi-framework support), Testkube provides that without the custom engineering.

Next: What types of tests are you running?

If your primary concern is cross-browser and cross-device UI testing, Sauce Labs or BrowserStack are purpose-built for that. No Kubernetes-native tool is going to match their device lab coverage. If you need API testing, load testing, integration testing, E2E testing, or a mix of all of these, you need something broader.

Next: Do you want testing coupled to your pipeline or independent?

If you are fine with tests running as pipeline stages (and do not need on-demand, scheduled, or deployment-triggered test runs outside of CI/CD), GitHub Actions, GitLab CI/CD, or CircleCI work. If you need testing to operate as its own layer, decoupled from build pipelines, Testkube or Argo Workflows are the right fit.

How to choose

The right tool depends on what you are actually trying to solve.

If your primary pain is that Jenkins is hard to maintain and you want a simpler CI/CD tool that also runs tests, GitHub Actions, GitLab CI/CD, or CircleCI will reduce operational overhead.

If your primary pain is that tests do not run in the same environment as your application, and flaky results from environment mismatch are costing your team time, you need something Kubernetes-native. That narrows the list to Testkube, Tekton, and Argo Workflows.

If your primary pain is browser and device coverage for UI testing, Sauce Labs or BrowserStack are purpose-built for that and will serve you better than any CI/CD tool or Kubernetes-native platform.

If your primary pain is that testing is too tightly coupled to your CI/CD pipeline, and you want to run tests independently (on schedule, on demand, triggered by deployments, across environments), that is specifically what test orchestration is built for.

Most teams dealing with Kubernetes at scale end up needing some combination of these tools. Jenkins (or its replacement) handles builds and deployments. A browser testing service covers UI coverage where needed. And a test orchestration layer manages everything else inside the cluster.

FAQ

Can I use Testkube with Jenkins instead of replacing Jenkins entirely?

Yes. Many teams continue using Jenkins for CI but offload testing to Testkube. Testkube has a native Jenkins plugin that lets you trigger test runs from your existing Jenkins pipelines. Jenkins triggers the workflows managed by Testkube, and Testkube handles execution, observability, scaling, and artifacts. There is no T (testing) in CI/CD — that is the gap Testkube fills.

Is Jenkins actually bad at testing, or is it just a configuration problem?

Jenkins can run tests. The issue is that it was not designed for test orchestration. Scaling tests requires pre-provisioned agents or complex cloud setups. Reporting is basic. Parallelization requires plugins and scripting. And test logic gets tangled with build logic in Jenkinsfiles. Jenkins needs custom scripts and plugins to talk to different testing tools and Kubernetes, which leads to fragile setups and configuration drift. For small test suites, this is manageable. For teams running hundreds of tests across multiple environments, the maintenance cost compounds.

How do tests actually run in Testkube vs Jenkins?

In Testkube, tests run as first-class Kubernetes workloads inside your clusters, using containers that match your production environment. In Jenkins, tests run on runners or agents that may not match production, with execution tied to pipeline stages and limited by agent capacity.

Which platform supports more testing frameworks?

Testkube is vendor-agnostic and supports any container-based tool: Playwright, Cypress, Selenium, Postman, JMeter, k6, pytest, custom scripts, and more. Jenkins supports frameworks through plugins, but each integration requires separate configuration and maintenance, and some plugins lag behind or introduce conflicts.

What if we are not on Kubernetes yet?

If your infrastructure is not on Kubernetes, Testkube, Tekton, and Argo Workflows are not the right fit. GitHub Actions, GitLab CI/CD, or CircleCI would be better starting points for decoupling from Jenkins. Once your infrastructure moves to Kubernetes, you can revisit the Kubernetes-native options.

How does Testkube handle test frameworks we already use?

Testkube is framework-agnostic. It supports k6, Playwright, Cypress, pytest, JMeter, Postman, Selenium, custom scripts, and any other tool that can run in a container. You do not rewrite your tests. You define a test workflow that tells Testkube how to execute them.

What about costs compared to Jenkins?

Jenkins is free but not cheap. You pay for the infrastructure to run it, the engineering time to maintain it, and the hours lost to slow, flaky tests. Cloud CI/CD tools replace server costs with per-minute pricing. Testkube uses predictable seat-based pricing and runs on your existing Kubernetes infrastructure, which means no separate compute bill for test execution. Since tests run from inside your clusters, there is also no need to compromise network policies or firewall rules to give tests access to your applications and services.