# Deploying a model serving endpoint

DevFeed: [Deploying a model serving endpoint](<https://devfeed.tech/articles/deploying-a-model-serving-endpoint-28605.md>)

Original publisher: [Read original article](<https://www.marvelousmlops.io/p/lecture-6-deploying-model-serving>)

Author: Başak Tuğçe Eskili

Published: 2025-08-02T11:00:01Z

Content type: tutorial

Language: en

Sources: [MarvelousMLOps](<https://devfeed.tech/sources/marvelousmlops.md>)

Topics: [databricks](<https://devfeed.tech/topics/databricks.md>), [MLOps](<https://devfeed.tech/topics/mlops.md>), [model-serving](<https://devfeed.tech/topics/model-serving.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>), [autoscaling](<https://devfeed.tech/topics/autoscaling.md>), [API](<https://devfeed.tech/topics/api.md>), [A/B Testing](<https://devfeed.tech/topics/a-b-testing.md>)

Tags: [a-b-testing](<https://devfeed.tech/tags/a-b-testing.md>), [api](<https://devfeed.tech/tags/api.md>), [article](<https://devfeed.tech/tags/article.md>), [autoscaling](<https://devfeed.tech/tags/autoscaling.md>), [databricks](<https://devfeed.tech/tags/databricks.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [latency](<https://devfeed.tech/tags/latency.md>), [mlops](<https://devfeed.tech/tags/mlops.md>), [model-serving](<https://devfeed.tech/tags/model-serving.md>)

## AI overview

Lecture 6 in an MLOps with Databricks course explains how to deploy registered MLflow models as Databricks Model Serving REST APIs. It covers serverless deployment, automatic scaling, monitoring, Unity Catalog integration, workload sizing, and limitations such as restricted runtime and cluster control.

## Source excerpt

Lecture 6 of MLOps with Databricks course