What happened
Observe by Snowflake, the observability platform, says its AI SRE (AI that helps engineers find and fix system problems) can help customers troubleshoot incidents up to 10x faster, with an average of over 4x faster, based on an analysis of 3,163 AI SRE conversation spans from October to November 2025.
Why it matters
The company's baseline data shows a complex incident currently takes 10 minutes to detect, 120 minutes to investigate, and 370 minutes for root cause analysis, with only 30% completion. The company argues most AI SRE tools fail because they are not built on a unified telemetry storage layer and a context graph that models relationships between systems.
What to watch
Observe attributes the gains to its architecture, which combines a data lakehouse storing logs, metrics, and traces with a context graph. One automotive SaaS customer cut investigation time from over three hours to minutes, and productivity gains generally clustered in the 3x-10x range.
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The article argues that the reason most AI for observability fails to speed up incident investigation is that it is bolted onto architectures not designed to support it. The authors state that data teams have more telemetry data than ever, but investigation has not gotten faster, and they identify structural reasons for this, such as data volume outpacing legacy platforms and root cause expertise being concentrated in a few engineers.
Observe by Snowflake presents its own architecture—combining a lakehouse for logs, metrics, and traces with a context graph that models semantic relationships—as the solution. The company’s analysis, using Anthropic’s methodology, found productivity gains clustered in the 3x-10x range, with 30% of interactions showing more than a 5x improvement. The company positions this as a direct result of giving the AI layer complete telemetry and context, suggesting that without this foundation, an AI SRE is only a chat interface for data.
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