Building a Stateful IT Service Desk Agent with LangGraph on Amazon EKS

This article demonstrates building a stateful IT Service Desk agent using LangGraph on Amazon EKS that autonomously resolves routine support requests and escalates complex issues to human engineers with full context preservation.

• LangGraph's interrupt() and checkpointing primitives enable tiered support escalation with state persistence across pod restarts
• Hybrid confidence routing uses retrieval score thresholds and LLM self-assessment to detect knowledge gaps and ambiguous situations
• Agent retrieves context from Amazon OpenSearch Serverless, generates answers via Claude on Amazon Bedrock, and escalates low-confidence issues
• Amazon DynamoDB checkpointing persists conversation state, enabling engineers to resolve escalated tickets hours later on any pod replica
• OpenTelemetry tracing provides complete audit trails of escalation decisions, documentation searches, and resolutions for SLA tracking
• Kubernetes HPA scales 2-10 replicas based on CPU; Karpenter provisions Spot Instances for cost optimization
• Deployment uses IRSA for secure credential-free access to Bedrock, DynamoDB, and OpenSearch Serverless

The pattern is portable across Kubernetes platforms and demonstrates how LangGraph's graph-based workflows naturally map to support team escalation processes.