Meet the Author
Irving Popovetsky
Director, Customer Architecture
Irving is Director of Customer Engineering at Honeycomb. He's been doing ops stuff and/or helping his fellow ops people live better lives for the past 24 years, the past 7 of those in Customer Success roles. Prior to joining Honeycomb in 2019, he was the first Customer Success Engineer and later Principal Customer Architect at Chef software during a 6 year tenure.
Explore Author's Blog
Data Strategy for SREs and Observability Teams
The idea that telemetry data needs to be managed, or needs a strategy, draws a lot of inspiration from the data world (as in, BI and Data Engineering). Your company most likely has a data team that manages the data warehouse(s), data pipelines, data sources, and reporting tools. These teams are also constantly balancing costs with their user and stakeholder needs, usability, data retention, granularity, etc. Sound familiar? That’s because if you’re working on observability data, these teams are at least several years ahead of you in addressing these tradeoffs and considerations—and can teach us quite a lot.
Achieving Great Dynamic Sampling with Refinery
Refinery, Honeycomb’s tail-based dynamic sampling proxy, often makes sampling feel like magic. This applies especially to dynamic sampling, because it ensures that interesting and unique traffic is kept, while tossing out nearly-identical “boring” traffic. But like any sufficiently advanced technology, it can feel a bit counterintuitive to wield correctly, at first.
