Best Software Testing Tools for Kubernetes

Codebeamer is an Application Lifecycle Management platform (ALM) for advanced product and software design. The open platform extends ALM functionality with product line configuration capabilities. It also provides unique configurability to complex processes. Incorporate product teams in automotive engineering and industrial manufacturing. Optimize the delivery and production of complex automotive technology products. Codebeamer provides a complete lifecycle management solution that includes all-in-one requirements and risk management capabilities.

Each module can be used independently or together to create a powerful unified pipeline that spans CI, CD and Feature Flags. Every Harness module is powered by AI/ML. {Our algorithms verify deployments, identify test optimization opportunities, make cloud cost optimization recommendations, restore state on rollback, assist with complex deployment patterns, detect cloud cost anomalies, and trigger a bunch of other activities.|Our algorithms are responsible for verifying deployments, identifying test optimization opportunities, making cloud cost optimization recommendations and restoring state on rollback. They also assist with complex deployment patterns, detecting cloud cost anomalies, as well as triggering a variety of other activities.} It is not fun to sit and stare at dashboards and logs after a deployment. Let us do all the boring work. {Harness analyzes the logs, metrics, and traces from your observability solution and automatically determines the health of every deployment.|Harness analyzes logs, metrics, traces, and other data from your observability system and determines the health and condition of each deployment.} {When a bad deployment is detected, Harness can automatically rollback to the last good version.|Ha

Even if you have the best developers, every test makes them slower. 80% of your software testing is pointless. The problem is that you don't know which 20%. We use your data to find the right 20% so you can ship faster. We offer shrink-wrapped predictive testing selection. This machine learning-based method is used by companies like Facebook and can be used by all companies. We support multiple languages, test runners and CI systems. Bring Git. Launchable uses machine-learning to analyze your source code and test failures. It doesn't rely solely on code syntax analysis. Launchable can easily add support for any file-based programming language. This allows us to scale across projects and teams with different languages and tools. We currently support Python, Ruby and Java, JavaScript and Go, as well as C++ and C++. We regularly add new languages to our support.

Software developers often build source code and test it on their own machines. EngFlow Remote Execution distributes builds, tests and results across a cluster to speed up the process. You can review your build and test it on any device, whether it's your laptop, desktop, or a colleague's. It's a game changer for remote collaboration. Console output can be confusing and verbose. To help you find what you are looking for, we split the data into views. One view shows the entire console output, streaming live as your builds or tests are completed. Test and build setups can vary between machines. We provide details about each execution, including platform, git branch, commit and implicit flags. This allows you to reproduce a run for both debugging purposes and to recreate a previous release.

Chaos Engineering provides everything you need to quickly and easily build reliable software. Gremlin offers a comprehensive list of failure modes that you can use to test your system. This includes bare metal, cloud providers, containerized environments and kubernetes. Throttle CPU, Memory and I/O. Reboot hosts, kill processes, travel in the time. Introduce latency, blackhole traffic and lose packets to fail DNS. Your code should fail. Failing to perform serverless functions may cause delays. Limit the impact to one user, device, or percentage.

Define a test execution consisting of a tool, test repository, and any arguments/parameters. Testkube workflows allow you to run any testing tool out of the box, or create your own custom workflow. Combining similar or dissimilar workflows for test execution into suites. Create a searchable repository for ready-to-run tests. Use proactive triggers for test executions based on CI/CD events. You can do this manually or according to a schedule. Listen for Kubernetes events, like deployments, to trigger test executions automatically. Use Kubernetes' native scalability in order to increase the number of simultaneous test executions. Scale load tests from 1 to 1,000 using advanced scaling capabilities. Parallelize functional tests for faster completion. Access logs and other artifacts generated by test tools in a central repository. Find errors quickly by highlighting failure-related keywords in the log.

Shift testing to one side and identify issues earlier when they are simpler and more cost-effective. Developers can do better integration testing, reduce dev cycles, and increase productivity. More reliable products will be possible with shorter and more thorough integration feedback cycles. Testcontainers Cloud allows developers to run reliable integration testing, with real dependencies defined and coded, from their laptops to the CI of their team. Testcontainers is an Open-Source framework that provides lightweight, throwaway instances of databases, message brokers and web browsers. It can also run just about any other application that can be run in a Docker Container. No need to create mocks or configure complex environments. Simply define your test dependencies in code and run your tests. Containers will be created and deleted.