Pastries with SREs: Enriched logs and filled donuts

In this episode of Pastries and SREs, we take a sweet dive into one of the most exciting evolutions in observability: enriched logs, also known as wide events.
Gone are the days of toggling between tools and stitching together logs, metrics, and traces. Enriched logs consolidate the context, providing everything you need to understand and resolve issues in a single log entry.

We explore:

⦁What enriched logs (wide events) are and why they’re transforming observability
⦁How enriched logs simplify root cause analysis and reduce toil
⦁Why enriched logs are a game-changer for AI observability tools and LLM readiness
⦁How they work alongside metrics and traces (not replace them)
⦁Real-world use cases for accelerating incident response with context-rich data
⦁Why this approach sets the stage for automated troubleshooting and remediation
⦁So next time you're debugging an issue, imagine having everything you need in one bite, just like that cream-filled donut. It's time to rethink your observability stack.

00:00 – What are enriched logs in observability?

00:30 – How logs evolved: From basic events to wide context logs

01:01 – Metrics vs. traces vs. enriched logs

02:01 – How wide events improve correlation, joins, and analytics

02:26 – Why enriched logs are critical for AI and LLM observability

03:24 – Addressing cost concerns: Are big logs worth it?

03:58 – How enriched logs reduce tooling toil and incident time

04:32 – Make money, save money, reduce risk

04:51 – Why enriched logs win on all three factors

05:49 – Querying by User/Merchant ID with full context in one log

Additional resources:

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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.