Simplifying Lakehouse Observability: Databricks Key Design Goals and Strategies
OVERVIEW
EXPERIENCE | In Person |
---|---|
TYPE | Breakout |
TRACK | Data Lakehouse Architecture |
TECHNOLOGIES | Databricks Experience (DBX), Developer Experience, Governance |
SKILL LEVEL | Intermediate |
DURATION | 40 min |
In this session, we will explore Databricks’ Lakehouse Observability, which is a crucial aspect of any successful data, analytics, and AI initiatives. Databricks aims to provide users with the necessary tools and insights to run a successful business on top of lakehouse architecture by directly integrating observability solutions within the Databricks Data Intelligence Platform.
Our approach is designed to leverage existing expertise and streamline the process of monitoring and optimizing data and AI workflows, enabling teams to deliver sustainable and scalable data and AI applications.
Join us to learn more about our key design goals and how Databricks is making Lakehouse Observability more accessible to support the next generation of data-driven applications.
SESSION SPEAKERS
Greg Kroleski
/Product Manager, Billing
Databricks