AI Driven DevSecOps Part 4: Observing Microservices with OpenTelemetry and Grafana
Source: YouTube · SANS Cloud Security · published Jul 31, 2026 · 55:10
BLUF: This session demonstrates integrating OpenTelemetry with Kong and Grafana to collect and visualize telemetry data, while using AI agents via MCPs to speed up configuration and troubleshooting 2:46.
Key Takeaways:
• Core observability signals: metrics, logs, and traces linking transactions across systems 2:50
• OpenTelemetry is vendor-neutral—swap backends without rewriting instrumentation 7:51
• High metric cardinality (e.g., unique pod names as labels) can overwhelm storage 6:01
• The OTel Collector uses receiver/processor/exporter pipelines to send data to multiple destinations 11:03
• MCP servers let AI agents explore infrastructure read-only, speeding up debugging 16:21
• Grafana's Loki, Tempo, and Mimir share scalable designs: object storage and multi-tenancy 29:14
AI agents spotted missing configuration in minutes that took the presenter hours to find manually 27:02. Combining solid telemetry with AI assistance enables faster incident response and deeper visibility.
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First 800 characters of the transcript
Welcome, I guess the part four in the title. We've got all covered here, so um quick background about me. Uh my name is Ben Allen. I currently work at the Bouillon Group as a security engineer. And I figured since we're talking observability, I'd uh give the brief summary of my uh sort of career history here as a trace. So, um slides will be available tomorrow. You can take a look deeper in there. Um top-level summary, I've been doing infosec stuff for over 20 years and I'm having a blast and still learning more and more and more every day, so um what we've got in store for today. Uh [clears throat] we're going to do a quick series recap. Um we'll look at some core concepts of observability. Um dig into the details with Open Telemetry and Grafana and uh do some conclusions. Hopefully, we'r…