The conference presentation discusses the importance of standardizing observability data and bridging the gap from a correlation perspective to make it more efficient and transformable. The goal is to reduce developer toil and help end-users correlate their data across systems.
- Observability data is difficult to analyze due to the large amounts of data emitted from cloud infrastructure, applications, and services
- Querying should be thought of as querying as code
- The primary problem is bridging the gap from a correlation perspective to make it more efficient and transformable
- The goal is to reduce developer toil and help end-users correlate their data across systems
- The work group will research, analyze, and make recommendations for future working groups or projects to implement a standard
The speaker, Chris Larson, who has been in observability for quite a while, has seen the problem of query languages over time and trying to correlate all these signals. He wanted to jump back into the industry and try to corral everybody, all the vendors, the end-users together and see if they could come up with some kind of query standardization across the industry that might unblock migrations and customer acquisition coming forward.