What your AI SRE can't see (and what you can do about it)

AI SRE tools can reduce alert fatigue and speed incident triage, but the article argues that they remain primarily reactive because they engage after failures begin and cannot prevent sudden events such as certificate expirations, configuration errors, or dependency failures with no warning signals. It contends that telemetry-based root cause analysis is inferential and potentially inaccurate, while automated remediation may restore service without proving that underlying weaknesses have been fixed. The piece advocates proactive resilience testing as a complement to AI SRE, using controlled tests to identify anticipated failure modes such as zone outages, broken failovers, dependency failures, and resource exhaustion before they affect users. It presents Gremlin’s Foresight AI as a product that draws on resilience-testing data to recommend tests, explain observed failures, suggest fixes, and verify remediations by safely reproducing failure conditions. The proposed approach assigns proactive testing to known and testable risks, while reserving AI-assisted incident response for novel failures and edge cases that remain.

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