Georgia State's TReNDS cuts root-cause investigation from 30 minutes to under 60 seconds with a Strands agent on Bedrock
AWS Machine Learning Blogmedium signalAWS published a build writeup of TReNDS, a Georgia State University research center, wiring an agentic incident-response pipeline: CloudWatch subscription filters match ERROR/Exception/FATAL/CRITICAL patterns, trigger a Lambda, and hand off to a Strands Agents SDK agent running Claude Sonnet that pulls surrounding log context and the relevant GitHub source before publishing a structured root-cause analysis to SNS for email and Slack. Investigation time drops from 15–30 minutes to under 60 seconds at what the team calls negligible Bedrock inference cost, with deduplication preventing repeat analyses of the same error. They benchmarked Claude Haiku, Claude Opus, Amazon Nova Pro and Nova Lite before choosing Sonnet for multi-file code reasoning — a concrete, copyable pattern for anyone running production services.
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