Best practices

Through integration with Cognitive Services APIs, Azure Search has long had the ability to extract text and structure from images and unstructured content.

The action rules feature for Azure Monitor, available in preview, allows you to define actions for your alerts at scale, and allows you to suppress alerts for scenarios such as maintenance windows.

This year at Microsoft Build 2019, we announced a slew of new releases as part of Azure Machine Learning service which focused on MLOps. These capabilities help you automate and manage the end-to-end machine learning lifecycle.

Data is rarely simple. Not every piece of data we have can fit nicely into a single Excel worksheet of rows and columns.

Today, many organizations are leveraging digital transformation to deliver their applications and services in the cloud. At the recent Build 2019 conference, Microsoft Azure Quickstart Center was generally available and received positive feedback from customers.

The Microsoft Worldwide Learning Innovation lab is an idea incubation lab within Microsoft that focuses on developing personalized learning and career experiences. One of the recent experiences that the lab developed focused on offering skills-based personalized job recommendations.

Customers such as Allscripts, Chevron, J.B. Hunt, and thousands of others are migrating their important workloads to Azure where they find unmatched security.

Preparing for the unexpected is part of every IT professional’s and developer’s job. Although rare, service issues like outages and planned maintenance do occur.

Learn how to monitor performance and resource utilization on Azure HDInsight by keeping tabs on metrics, such as CPU, memory, and network usage, to better understand how your cluster is handling your workloads and whether you have enough resources to complete the task at hand.

When data scientists work on building a machine learning model, their experimentation often produces lots of metadata: metrics of models you tested, actual model files, as well as artifacts such as plots or log files.

Customers have been using Azure Stack in a number of different ways. We continue to see Azure Stack used in connected and disconnected scenarios as a platform for building applications to deploy both on-premises as well as in Azure.

Data scientists have a dynamic role. They need environments that are fast and flexible while upholding their organization’s security and compliance policies. Notebook Virtual Machine (VM), announced in May 2019, resolves these conflicting requirements while simplifying the overall experience for data scientists.