talk-data.com

This talk is about using synthetic monitoring to reduce MTTD&MTTR significantly and achieve high devops maturity. Daniel is a big believer in synthetic monitoring as a concept to build reliable production services. If engineers are supposed to run what they build, they need monitoring tools that work for them. He has built his own custom solutions in the past using Jenkins or GH Actions and later used SaaS tools for this. He would like to share his experience getting frontend engineers to build monitoring and get everyone on an engineering team to care about production system reliability. Daniel Paulus has taken a unique journey from military officer to tech leader, and he’s now the VP of Engineering at Checkly. Along the way, he’s worn many hats— from engineering lead to director —learning how to build strong teams and solve tough challenges. Outside of work, Daniel lives near Berlin with his family and four kids, while also finding time to maintain an open-source project. Whether it’s scaling teams or debugging code, he’s passionate about technology and enjoys sharing his knowledge with others.

After years of working and coaching teams to implement SLOs, it’s becoming incredibly clear to me that the greatest challenge that engineering and product teams face is finding the right SLIs. SLOs are hard to get right, and it generally takes time and multiple iterations to tweak, tune, and adjust them so they’re providing value to inform when we need to take action to defend the reliability of our systems. However there is an underlying assumption that the SLI itself is/has been providing value. As hard as SLOs are to get right, thinking of a good SLI is also difficult. This especially complicates things for engineering teams that don’t have a product person. As a result, they often struggle to identify what are key user / customer journeys. This talk will attempt to provide attendees with additional guidance to help them think more clearly about and create better SLIs. We’ll break SLIs up into three (3) categories – Customer / User Experience, Supporting Services, and Management/Reputation. For each of these categories, I’ll discuss three relevant SLIs of each (e.g., application metrics, network metrics, Public Sentiment, etc.), some best practices, common pitfalls, and how the signal for each of the nine (9) metrics can be developed further to become more mature over time. Sal Furino is a Customer Reliability Engineer at Bloomberg. During his career he’s worked as a TPM, SRE, Developer, Sys Admin, and IT support. While not working he enjoys cooking, gaming, and traveling. Sal lives in Queens and has a BS in Applied Mathematics from Marist College.