Thursday, February 18, 2021
A key challenge when working with software is that it’s invisible. It does not inherently lend itself to the universal DevOps goal of “Telemetry Everywhere.” While engineers consciously code their product to emit metrics, logs and traces that allow them to observe the invisible, traditional monitoring methods fall short of generating meaningful data about incidents, leaving teams with excess toil when things break. This talk will explore the relationship between observability and SDLC practices which allow AI to lead the Ops side of DevOps, so developers and SREs can move faster, innovate more and operate less.
Attendees will learn:
- How introducing visibility and control over incidents earlier in the development cycle can reduce toil.
- How to leverage Service Level Objectives (SLOs), error budgets and the ‘wisdom of production’ to improve the Ops part of DevOps.
- Methods for using AI-driven observability to turn every incident into a learning opportunity.
Discover how AI-driven observability methods help improve practices from Site Reliability Engineering to Continuous Integration and Deployment, and supports the transition from project to product-centric ways of working.
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