Pastries with SREs: Holding onto extra observability data and desserts

In this episode of Pastries with SREs, we dig into why you should keep all of your observability data, even if you don’t need it quite yet.

We explore:
Why “unknown unknowns” are a huge risk in observability
The value of full-fidelity data ingestion and enriched logs
How data lakes and object storage help you retain everything cost-effectively
Ways to avoid gaps in observability data that can undermine root cause analysis
How long-term data storage can help with audits and compliance

With enriched logs and flexible, cost-effective storage, you can stop worrying about what you might need later and start answering questions with confidence, no matter when they arise.

00:00 – Why unknown unknowns break observability
00:42 – Real customer outage: missing logs = no RCA
01:47 – Ingesting everything without blowing your budget
02:06 – Using object storage + data tiering to cut costs
03:08 – From monitoring to true observability (key difference)
03:33 – Data lakes vs. data mesh (and what actually works)
04:30 – Why enriched logs matter for faster root cause analysis
05:15 – Full-context searchability and eliminating data silos

Additional resources:

Learn more about Elastic Observability: https://www.elastic.co/observability

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About Elastic
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.

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