Not so long ago, operations specialists worked much like today's data engineers do: with specialized skills, they were the people who kept sites running, who responded to emergencies, and who—unfortunately—spent much of their time dealing with incidents and other "fires." When the DevOps revolution came, this began to change.
Better tools, better practices, and better culture shaped how Ops folks worked. A subset of that DevOps culture soon emerged: Site Reliability Engineers. These were people whose focus was not just on the day-to-day deployment of applications, but running platforms, products, and services with very high performance, very large scale, and with very high demand for reliability. Data Engineering was left out of this revolution.
But it is not too late! By taking concepts from SRE culture, in particular, the theory of Service Level Objectives, we look at how teams operating and developing data platforms and data products can be built more reliably through the use of quantitative measures and product thinking. This talk will discuss concrete examples of the benefits of this approach for data teams and how organizations can benefit from this mindset.
Related Videos: Open Source DatabaseRevision Control for Structured Data - Gavin Mendel Gleason - Percona Live ONLINE 2020
What If We Could Use Machine Learning Models as Tables? - Jorge Torres - Percona Live ONLINE 2020
Mastering Open Source Data Governance - Elisha Chitsenga - Percona Live ONLINE 2020
How can databases capitalize on Computational Storage - PLO October 2020
Availability and Performance Tradeoffs in Global Database Deployments - Kevin Jernigan
Full Observability for Application Monitoring - Markus Strauss - Percona Live ONLINE 2020
Power Hour, Managing Databases at Scale - Peter Zaitsev Managing Databases at Scale - PLO October 2020