Virtual Event Series
Databricks Specialist Sessions
Dive Deeper into Databricks
As an experienced Databricks user, we’d like to invite you to take a deep dive into a range of topics to help maximise the value and performance of the Databricks platform.
Each Databricks Specialist Session will take an in-depth look at the key challenges you may encounter day-to-day, and how to solve them. Each month, we will cover a different technical subject in depth, including best practices for governance, geospatial data processing, data warehousing and streaming, as well as a detailed look at the platform architecture.
Upcoming Sessions
- Meet Lakebase: the next evolution of Postgres for AI and Data Apps | 16 March
- From Prototype to Production with MLflow for GenAI | 15 April
Coming Up Next
Meet Lakebase: the next evolution of Postgres for AI and Data Apps
Duration: 1 hour 30 mins
This session is an in-depth look at Lakebase — the first fully managed, serverless Postgres database built for data apps and AI agents. Built on Postgres 17 and natively integrated with the Databricks Data Intelligence Platform, Lakebase brings together transactional and analytical workloads in a single, unified platform — eliminating the complex ETL pipelines that have traditionally kept operational and analytical data apart.
You’ll explore real-world use cases, architecture, security, and monitoring, and see live demos that showcase how Lakebase transforms traditional PostgreSQL into a modern, decoupled, and high-performance platform. See firsthand why modern data teams are switching to Lakebase, the intelligent database built for the future.
Key Takeaways:
- - Learn how Lakebase extends PostgreSQL to power both modern data apps and AI-driven workloads
- - See how decoupled storage and compute deliver elastic, serverless performance — with autoscaling, scale-to-zero, and usage-based pricing in DBUs
- - Explore instant database branching using copy-on-write technology, point-in-time recovery, read replicas, and enterprise-grade security via Unity Catalog
- - Experience seamless Lakehouse integration through Synced Tables and Lakehouse Federation — unifying transactional and analytical data without custom pipelines
16 March 2026
10:00 AM GMT | 11:00 AM CET
From Prototype to Production with MLflow for GenAI
Duration: 2 hours
This session introduces MLflow as the open platform for building, evaluating, and deploying production-ready GenAI agents at speed, with core capabilities such as tracing, evaluation, versioning, and the AI Gateway, which provides deep visibility into agent behaviour while simplifying debugging and improving reliability at scale.
We’ll also cover MLflow’s newest features brought to life through a live demo showcasing end-to-end tracing, evaluation, and monitoring in action. Whether you’re just starting with GenAI or scaling existing agents, you’ll leave with a clear phased adoption strategy—from initial tracing through full production monitoring—to deliver high-quality, cost-efficient, and accountable GenAI applications.
Key takeaways:
- - Use MLflow to support the full GenAI agent lifecycle, from experimentation to production monitoring.
- - Apply tracing, evaluation, and LLM judges to understand and improve complex agent behaviour
- - Leverage the newest MLflow features, including prompt optimisation and the Prompt Registry API for governed, reusable prompt management
- - Follow a phased adoption strategy for robust monitoring, evaluation, and governance of GenAI systems on Databricks
Ideal for: ML engineers, data scientists, and platform teams building or operating GenAI systems on Databricks
15 April 2026
10:00 AM BST | 11:00 AM CEST
