Naïm Achahboun

Building a data-driven application is easy; building one that is secure, performant, and scalable is where most teams struggle. This session provides a definitive field guide to the architectural patterns used by the most successful builders on the Databricks App platform. We will break down the ""how-to"" for the most in-demand app categories: Internal Tools, AI Copilots, Agentic Workflows, and Customer-Facing Products. For each pattern, we will dive into the technical specifics that matter most: - Connectivity & State: Best practices for integrating with Databricks SQL and Lakebase. - Identity & Auth: Implementing On-Behalf-Of (OBO) tokens and service principal delegation to ensure data privacy. - Agentic Design: Orchestrating LLMs and tool-calling within a full-stack environment. - Performance: Strategies for caching and low-latency UI responses. Join us to learn how to avoid common pitfalls and leverage standardized blueprints to ship better apps.

Organizations are moving beyond simple dashboards to interactive, secure Data & AI applications built directly where their data lives. This session provides a technical deep dive into Databricks Apps, exploring how to transform complex AI logic into production-ready business tools. We will cover the essential architectural choices for developers, including a comparison of Pythonic frameworks like Streamlit and Gradio versus full-stack JS/TS implementations. The discussion will focus on the end-to-end development lifecycle, teaching you how to master authentication via Service Principals and On-Behalf-Of (OBO) tokens, and how to implement robust production workflows using Databricks Asset Bundles (DABs). Additionally, we will share best practices for optimizing performance and scalability—such as using async operations—and ensuring enterprise-grade observability through diagnostic logging and audit trails