- 👓 View today's article
- 🍿 Tune into the AI Show
- 🗞️ AiMonthly Newsletter
- 🌤️ Continue the Azure AI Cloud Skills Challenge
- 🏫 Bookmark the Azure AI Technical Community
- 🌏 Join the Global AI Community
- 💡 Suggest a topic for a future post
Please share
🗓️ Day 18 of #30DaysOfAzureAI
Azure ML Managed Online Endpoints - A Quickstart
Yesterday we learned how to streamline ML Development with Azure ML. Today, we'll learn how to deploy ML models using Azure ML managed online endpoints.
🎯 What we'll cover
- What are Azure ML managed online endpoints.
- The three main components of an online endpoint.
- How to deploy one or more models under the same endpoint.
📚 References
🚌 Get started with Azure ML's managed online endpoints
Today's article discusses the benefits of using Azure Machine Learning's managed online endpoints and compares them to Azure Container Instances. The author outlines three main reasons why they prefer managed online endpoints: built-in security, native blue/green deployments, and auto-scaling with Azure Monitor.
Step-by-step instructions are provided for for deploying an online endpoint that translates API inputs to something a machine learning model can handle, invokes the model, and returns formatted results.
👓 View today's article
Today's article.
🙋🏾♂️ Questions?
You can ask questions about this post on GitHub Discussions
📍 30 days roadmap
What's next? View the #30DaysOfAzureAI Roadmap
Subscribe to the AiMonthly RSS XML feed