Model Serving with Databricks
What you’ll learn
Databricks Model Serving makes it easy to deploy AI models without dealing with complex infrastructure.
It turns your MLflow machine learning models into scalable REST API endpoints, offering a reliable and fast service for deployment. The system adjusts automatically to changes in demand, cutting infrastructure costs and improving latency performance.
In simple words, you can deploy different types of models, whether they're for language, vision, audio, tabular data, or custom models. It doesn't matter how the model was created—whether from scratch, using open source software, or fine-tuned with private data.
Try Databricks free
Test-drive the full Databricks platform free for 14 days
Simplify data ingestion and automate ETL
Ingest data from hundreds of sources. Use a simple declarative approach to build data pipelines.
Collaborate in your preferred language
Code in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations and RBAC.
12x better price/performance than cloud data warehouses
See why over 9,000 customers worldwide rely on Databricks for all their workloads from BI to AI.