Best Chaos Engineering Tools for Kubernetes

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

Your digital business services must be reliable and can only be provided by digital immunity against software and infrastructure failures. ChaosNative Litmus makes it easy to introduce chaos culture into your DevOps and takes control of your business' service reliability. ChaosNative Litmus is a robust LitmusChaos chaos engineering platform that Enterprises can use. The product provides enterprise support as well as chaos experiments for virtual environments, popular cloud infrastructure, and services. ChaosNative Litmus can be integrated into your DevOps tools. LitmusChaos is the core of ChaosNative Litmus. All the power of open source Litmus can be carried into the open core ChaosNative Litmus. ChaosNative Litmus works the same way as open source Litmus.

Our experiment editor makes it easier to reach reliability. You have complete control over your experiments. All are designed to help you achieve goals and safely implement chaos engineering in your organization. Steadybit extensions allow you to add new targets, checks, and attacks. The targets are easily selected using a unique discovery and selection procedure. Export and import experiments in JSON or YAML to reduce friction between teams. Steadybit’s landscape allows you to see the dependencies and relationships of your software. This is a great way to start your chaos engineering journey. Divide your system(s), using the powerful query language based on the information you use elsewhere, into different environments. Assigning environments to specific teams and users to prevent unwanted damage.

Validate your app's performance and quality with real-world traffic scenarios. Preview code performance to quickly identify problems and ensure your app is running optimally when the time comes to release. To better prepare for production, mimic real-life scenarios, simulate load, and create intelligent simulators of third-party or internal backend systems. You don't need to create expensive new environments every time you test. Cloud costs are further reduced by the autoscaling feature. You can ship more code faster by avoiding complex frameworks, manual test scripts, and homegrown frameworks. You can be confident that your new code changes will handle high traffic scenarios. Protect the customer experience, prevent major outages and meet SLAs. Simulate internal and third-party backends to ensure more reliable and affordable testing. No need to create expensive, end-toend environments that can take days to deploy. Migrate seamlessly off legacy architecture without affecting the customer experience.

Maintain customer trust by overcoming downtime. NetHavoc is able to change performance engineering and quality delivery on a large scale. Deal with uncertainty in real-time before it becomes a problem. NetHavoc deliberately breaks the application infrastructure to create chaos within a controlled environment. Chaos engineering is a strategy that aims to observe how an application behaves when it fails and make it more powerful. Early investigation is the key to ensuring application infrastructure is resilient during production. Discover the vulnerability of an application. Expose hidden dangers and reduce uncertainties. Prevent malfunctions that could affect user-facing issues. Consume CPU cores, or utilization. Validate real-time usage cases by injecting different types of havoc n times on the Infrastructure layer. Interject havocs seamlessly using the API and an agentless approach. You can specify a specific time for havocs or a random range of time.

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.

Chaos doesn't have a place in the management of complex systems. Continuous verification gives proactive insight into complex systems. Continuous verification uses experimentation in order to find security and availability flaws before they become business-disrupting events. Our software & system complexity continues to grow. The development teams need to find a way of preventing costly security and availability incidents. It is necessary to find weaknesses in a proactive manner. Continuous integration and continuous delivery has helped successful developers to move faster. Chaos engineering principles are used to prevent costly security and availability incidents. Verica gives you confidence in even the most complex systems. Chaos engineering uses the rich history and empirical experiments to discover vulnerabilities in complex system. A tool that integrates Kubernetes, Kafka and other enterprise tools out of the box.