DeveloperWeek Europe 2021 DeveloperWeek Europe 2021
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OPEN TALK: Refining Systems Data without Losing Fidelity


Liz Fong-Jones
Honeycomb, Developer Advocate

Liz is a developer advocate, labor and ethics organizer, and Site Reliability Engineer (SRE) with 16+ years of experience. She is an advocate at Honeycomb for the SRE and Observability communities, and previously was an SRE working on products ranging from the Google Cloud Load Balancer to Google Flights.

She lives in Vancouver, BC with her wife Elly and a Samoyed/Golden Retriever mix, and in San Francisco and Seattle with her other partners. She plays classical piano, leads an EVE Online alliance, and advocates for transgender rights.


It is not feasible to run an observability infrastructure that is the same size as your production infrastructure. Past a certain scale, the cost to collect, process, and save every log entry, every event, and every trace that your systems generate dramatically outweigh the benefits. If your SLO is 99.95%, then you'll be naively collecting 2,000 times as much data about requests that satisfied your SLI as those that burnt error budget. The question is, how to scale back the flood of data without losing the crucial information your engineering team needs to troubleshoot and understand your system's production behaviors?

Statistics can come to our rescue, enabling us to gather accurate, specific, and error-bounded data on our services' top-level performance and inner workings. This talk advocates a three-R approach to data retention: Reducing junk data, statistically Reusing data points as samples, and Recycling data into counters. We can keep the context of the anomalous data flows and cases in our supported services while not allowing the volume of ordinary data to drown it out.