AzureFeeds

An overview of Microsoft Azure Kubernetes Service (AKS) guidance offerings ranging from “just starting out”, to production, and through sustained operations.

Use these recommendations to avoid having single points of failure, by building redundancy into your application.

Learn to design resilient applications that can recover from failures without manual intervention through self-healing.

Use an example to guide the migration of your application from Azure Service Fabric to Azure Kubernetes Service.

Learn about the Team Data Science Process and Azure Machine Learning objectives that you can use to implement comprehensive data science solutions with Azure technologies.

Learn how the Team Data Science Process provides a data science methodology to deliver predictive analytics solutions and intelligent applications.

Choose a natural language processing service for sentiment analysis, topic and language detection, key phrase extraction, and document categorization.

Learn about Azure cognitive services that you can use in AI applications and data flows. Choose the appropriate service for your use case.

The goals, tasks, and deliverables for the business understanding stage of your data science projects in the Team Data Science Process.

Learn about the tasks that a group manager performs on a Team Data Science Process team, including how they can incorporate language models and copilots.

This article describes approaches to support multitenancy for the storage and data components of your solution.