agent-mlops

What problem does it solve?

Produces robust, observable deployment and lifecycle management for AI agents on Databricks, enabling reliable production usage with traceability, evaluation, and governance.

Core Features & Use Cases

• Production deployment and monitoring of AI agents on Databricks using MLflow.
• Enable tracing and logging of agent decisions, tool usage, and interactions for debugging and auditability.
• Implement agent evaluation frameworks, version management, and CI/CD pipelines.
• Monitor latency, cost, and performance across development, staging, and production environments.
• Production readiness: model serving configuration, monitoring dashboards, and incident response.

Quick Start

Configure Databricks MLflow integration and deploy your first agent to a production serving endpoint.