
The SRE Agent for Kubernetes deployments uses a scheduler to monitor cluster health without waking the full agent, collecting state via the Kubernetes Python client and generating structured reports in Slack. It employs a read/write split, with writes requiring human approval, and integrates specialized subagents to prioritize remediations. The architecture balances autonomy with safety, using LangGraph for planning and HITL interrupts for writes, while minimizing costs through efficient resource use. The agent is designed to be simple, cost-effective, and adaptable, with LangSmith aiding in debugging and improving its performance.
Managed Deep Agents gives developers a managed way to build, run, and deploy Deep Agents with built-in runtime, streaming, sandboxes, evals, memory, and auth.

LangSmith Bring Your Own Cloud is now generally available on AWS, giving Enterprise teams managed observability, evaluation, and deployment inside their own VPC.

Learn what AI agents are, how they work in an LLM loop, and where workflows fit so you can build reliable, production-ready autonomous systems.
