Today’s distributed, cloud-based environments are incredibly complex. Not only does each component depend on many others, but modern systems are also highly dynamic—changing frequently as teams push new code or make updates to infrastructure.
Taming this complexity to ensure reliability requires end-to-end observability to understand how components depend on each other. Additionally, proactive Chaos Engineering combined with AI-driven observability lets you uncover “unknown unknowns” that impact how your system will respond to different failure scenarios.
Join Gremlin and Dynatrace as we discuss techniques for maintaining and improving reliability in complex cloud environments. We will cover how to establish end-to-end observability across your environments and how to map their complex relationships. We will then provide a framework for safely and thoughtfully conducting Chaos Engineering experiments with Gremlin.
Finally, we will share how teams can incorporate continuous chaos experimentation into build and deploy pipelines using the concept of “quality gates” in Dynatrace to help you establish and adhere to reliability SLOs.
Learn the history, principles and practice of Chaos Engineering
Discover how to improve your teams on-call skills
How observability and chaos work together to improve the reliability of distributed systems
How to use Gremlin and Dynatrace to enable your engineering team to have continuous improvement
Gremlin empowers you to proactively root out failure before it causes downtime. See how you can harness chaos to build resilient systems by requesting a demo of Gremlin.Get started
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