This talk is for DevOps and SRE engineers who are looking to optimize the number of SLOs in their system and find methods to manage a large number of various SLIs for their complex, multi-level service architecture. The talk covers practical methods for calculating SLOs based on multiple SLIs and dependencies, including the reliability of third-party service providers and unknowns. Attendees are expected to be familiar with basic SRE principles and terminology. The talk includes some probability math.

Overwhelmed by the complexity of managing SLOs across your microservices architecture? This talk provides DevOps and SRE engineers with actionable strategies for defining, calculating, and optimizing SLOs in systems with a large number of SLIs.

We’ll explore practical techniques for:

• SLO Targets: Right-guessing and improving your SLO goals.
• SLO Optimization: Right-sizing the number of SLOs to ensure effective monitoring without unnecessary overhead.
• SLO Composition: Mastering aggregation and other methods to derive meaningful SLOs from diverse SLIs.
• Dependency Management: Incorporating the reliability of third-party services and unknowns into your SLO calculations.

The talk will include some probability math to illustrate key concepts.

In my work at Google as a Developer Relations Engineer, I help cloud practitioners to solve a wide range of technical and architectural problems related to running workloads in Google Cloud and hybrid environments. Jump start to Google Cloud. Reach 99.99 SLO. Troubleshoot a problem in real time. Or, evaluate a security posture of your application. All these and many other problems that engineers and architects meet every day. Before Google, I worked in healthcare, interactive TV and gaming industries in many engineering roles including SWE, TL and Cloud Architect. In my free time I enjoy swimming, hiking and horseback riding.