Gremlin Inc., a chaos engineering leader, has partnered with Dynatrace, which specializes in observability and application performance monitoring. Together, they are launching a new integration. This partnership aims to simplify reliability testing in Kubernetes environments.
This collaboration simplifies fault-injection testing workflows, enabling organisations to better support reliability programmes and maintain their Kubernetes applications in the desired state.
“With this new integration, Gremlin and Dynatrace are simplifying how organizations introduce fault injection into their Kubernetes environments,” said Samuel Rossoff, CTO of Gremlin. “Many teams have faced challenges operationalizing reliability testing across complex cloud-native architectures, often requiring multiple manual steps to identify and target the right resources. By combining advanced AI observability and topology insights with Gremlin’s fault injection and reliability capabilities, customers can more easily identify, test, optimize, and strengthen critical services at scale.”
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Beginning immediately, Kubernetes services are automatically discovered within Gremlin, powered by Dynatrace’s AI-driven observability and topology mapping. Health checks are subsequently applied to Kubernetes objects, allowing organisations to efficiently implement standardised reliability testing and gain deeper insights into their environments.
“Kubernetes is the foundation of modern cloud-native infrastructure, supporting a wide spectrum of organisations, from nimble startups to global enterprises,” said Wayne Segar, Global Field CTO at Dynatrace. “As AI-driven innovation accelerates, the reliability of Kubernetes becomes mission-critical. Our partnership with Gremlin simplifies chaos engineering, helping teams ensure resilience and performance across complex, distributed systems.”
Gremlin and Dynatrace make fault-injection testing faster, simpler, and safer. This supports their common goal: helping engineering teams create resilient systems. It also aims to reduce risk and ensure reliability at scale.