Kubernetes environments generate massive volumes of operational data. Metrics, logs, events, and configuration changes create complexity that's difficult to navigate quickly in production.

WHAT YOU'LL BUILD

Experiment with AI agents that operate directly on Kubernetes infrastructure, interpreting cluster signals and taking action across debugging, scaling, and workload optimization.

Through three hands-on scenarios, you'll explore agents that:

Diagnose cluster issues through Kubernetes API access
Identify and resolve resource constraints and workload failures
Adjust scaling policies based on workload behavior
Apply production optimizations and sync fixes back to infrastructure-as-code

No hype. Just practical AI-powered infrastructure operations.

KEY TOPICS

AI agents for infrastructure operations
Cluster debugging automation
Workload autoscaling optimization
End-to-end infrastructure optimization
Infrastructure-as-code synchronization

AGENDA

2:00 PM - Intro: AI for Kubernetes Operations
2:10 PM - Scenario 1: Cluster debugging with AI
2:35 PM - Scenario 2: Workload autoscaling
3:00 PM - Scenario 3: End-to-end workload optimization
3:25 PM - Closing discussion

WHO SHOULD ATTEND

Platform engineers, DevOps engineers, SREs managing Kubernetes clusters, infrastructure engineers, and developers building internal platform tooling.

Prerequisites: Familiarity with Kubernetes concepts (pods, deployments, resource limits). Prior AI agent experience not required.

What to Bring: Laptop, terminal access, Claude account (free tier).

WORKSHOP ACCESS

This workshop is exclusively available to summit attendees. First come, first served with limited capacity.

CONDUCTED BY

[Hands-on Workshop] Autonomous Kubernetes: Building AI-Powered Operations with AI Agents