Scaling GitOps for large-scale deployments can be challenging with a single repository or controller. This talk explores sharding as a strategy to optimize performance, improve reliability, and manage complexity in GitOps workflows for multi-environment or multi-tenant setups.

In this hands-on workshop, participants will learn how to develop powerful AI agents that can revolutionize IT infrastructure management through natural language interactions. As infrastructure complexity grows, the ability to leverage AI to simplify operations becomes increasingly valuable. This workshop will guide attendees through the complete process of building a Python-based AI assistant that can interpret natural language requests and execute complex infrastructure tasks.
Participants will learn how to:

Architect an AI agent that connects large language models (LLMs) with backend systems
Implement secure API integrations between AI models and infrastructure components
Design conversation flows that translate natural language into precise technical operations
Build a web interface for seamless interaction with the AI assistant
Implement error handling and security best practices for production-ready agents

This workshop combines practical coding sessions with architectural insights, enabling participants to create their own customizable AI infrastructure assistants. By the end, attendees will have a working prototype they can extend to manage various aspects of their IT ecosystem.

Suitable for DevOps engineers, system administrators, and developers with basic Python knowledge, this workshop provides the foundation for building the next generation of intelligent infrastructure management tools that dramatically enhance team productivity and system reliability.RetryClaude can make mistakes. Please double-check responses.

Requirements: Basics of Python