The Engine Powering Continuous Testing in Kubernetes
Challenges
CI/CD not built for test execution
CI/CD engines focus on integration and delivery, not scalable test execution, leading to slow, flaky tests and longer build times.
Limited to CI/CD tooling
Tests bound to CI/CD pipelines can't run locally, on schedules, via APIs, or from Kubernetes events—reducing continuous testing opportunities.
Kubernetes-native scaling gaps
Many test runners don't run natively in Kubernetes, requiring custom runners and creating complex DevOps bottlenecks.
Tool-specific scaling complexity
Each testing tool has unique, complex configurations for sharding, parallelization, or matrix execution—worse when not Kubernetes-native.
Third-party cloud reliance
Organizations use external providers despite having scalable in-house infrastructure, adding costs and undermining cloud-native investments.
Not AI ready
Script-based test execution makes it difficult for AI agents to trigger specific tests needed for code changes.
Solution
Agent Execution
The agents execute containerized testing tools or scripts directly within your Kubernetes clusters.
Control Plane Configuration
The control plane provides agents with the configuration necessary to execute the desired tests, including tool selection, source code locations, scaling parameters, and artifact collection instructions.
Unified Reporting
All executions are aggregated for reporting and passed to the observability tooling.
Features
Our K8s-native platform orchestrates tests across geographically distributed agents within your environment—trigger via CI/CD, GitOps, or APIs, leverage built-in parallelization and sharding, and gain unified visibility across all executions, with zero third-party cloud costs.
Flexible triggers
Tests can be triggered from CI/CD systems, manually, on a schedule, via APIs, or by Kubernetes resource changes. This supports true GitOps workflows, e.g., triggering tests on every image update.
Kubernetes-native scaling
Agents leverage native Kubernetes constructs for test execution and scaling, while also supporting parallelization, sharding, and matrix testing at the tool level.
Multi-agent Architecture
Tests can be orchestrated to execute on geographically distributed agents for distributed load-testing and multi-region deployments.
On-premise execution
All agents run within the customer’s environment—no third-party cloud costs, full control over infrastructure.
Execution Insights
The control plan tracks and aggregates all executions across all agents, enabling cross-environment reporting and dashboarding.
Ephemeral services
The engine can spin up temporary services as part of test workflows, ensuring consistency across clusters and geographies.
Head-to-Head: Test Execution Without Limits
| Testkube | CI/CD Runners | SaaS Testing | |
|---|---|---|---|
| Kubernetes-native scaling |  Agents leverage pods, sharding, parallelization, and matrix execution |  CI runners not built for scalable test execution | Limited to vendor-managed infra, scaling costs add up |
| Flexible triggers | Run tests from CI/CD, APIs, schedules, manual triggers, or Kubernetes events | Bound to build pipelines, little flexibility | Tests tied to SaaS UI or limited API hooks |
| On-premise execution | Run inside your infra, no third-party cloud costs | Dependent on CI/CD cloud runners | Reliant on vendor infra, higher costs and compliance risks |
| Multi-agent architecture | Orchestrate tests across geographies for distributed load testing | Not natively supported | Limited to vendor's regions, not customizable |
| Ephemeral services | Spin up test environments/services inside Kubernetes | Requires custom scripts or extra DevOps overhead | Limited sandboxing, tied to vendor capabilities |
| Execution insights | Centralized reporting across all agents & environments | CI logs only, fragmented visibility | Basic dashboards, siloed from CI/CD workflows |
| AI-ready execution | AI agents can target tests directly from workflows | Script-based triggers, not AI compatible | SaaS execution workflows not designed for AI |
How DocNetwork Saved 30 DevOps Hours Every Week
"Testkube gave us exactly what we needed. A simple, Kubernetes-native tool that fits into our workflow and helps the whole team, technical and non-technical, build better software faster."
Real-World Use Cases
See how Testkube's Execution Engine adapts to your unique testing needs across different environments and workflows.
- Continuous Testing with AI
- Flexible Triggers and Scheduling
- Ephemeral Environment Testing
- Load Testing Orchestration
- Optimize Kubernetes Resource Usage
A 30-Minute Chat to Turn Bottlenecks into Breakthroughs
Bring your stack and goals. We'll show how Testkube runs your tests in Kubernetes so you ship faster with confidence.
Talk through your current setup
CI, test types, environments, bottlenecks like flaky runs or long queues.
Get clear options
Parallelization, on-cluster execution, cost control, how Testkube fits with your CI.
See how you stack up
We compare approaches and outline a simple pilot you can validate in days.