How TReNDS automates root-cause analysis with Amazon Bedrock
TReNDS built a production AI system using Amazon Bedrock to automate incident root-cause analysis
“knowing that something failed and understanding why it failed are different things”
Georgia State's TReNDS neuroimaging center deployed a production agentic pipeline combining CloudWatch, Lambda, the Strands Agents SDK, and Amazon Bedrock to automatically investigate application errors — pulling log context and source code from GitHub to deliver structured root-cause analysis. The system targets the 15–30 minute manual investigation window engineers previously spent reading stack traces. Notable as a real production deployment of agentic AI for DevOps, though the use case is narrowly vertical and the source is a promotional AWS guest post.