AI

Building AI for Observability with AWS Bedrock In my previous post, I wrote about closing the last mile of observability with AI . The core idea was simple: we already have plenty of metrics, logs, and traces, but the real challenge is turning them into insights and answers that engineers can act on. In that post, I highlighted two main gaps: Connector layer – bridging multiple observability tools like Prometheus, Thanos, Elastic, etc. Insight layer – going beyond raw queries to provide real context and recommendations. Now, I’ve been experimenting with AWS Bedrock , and it feels like a natural way to solve both layers. ...

Over the years, observability has grown in ways I couldn’t have imagined when I first started working in this space. Thanks to OpenTelemetry, we now have a standard way to collect traces, metrics, and logs. Tools like Grafana, Prometheus, Jaeger and Elasticsearch make it easy to store and visualize that data. But here’s the truth I keep coming back to: Even with all the dashboards and alerts, something is still missing. ...