This module covers tools that you can use to monitor your Azure environment.

Compare Azure, and on-premises tools for monitoring and measuring performance. Determine critical metrics. Understand the purpose of a baseline for comparative analysis. Configure extended event sessions for tracing activities.

This module describes parallel jobs and how to estimate their usage. Also, it presents Azure Pipelines for open-source projects, explores Visual Designer and YAML pipelines.

This module introduces you to the benefits cloud computing can offer you or your organization.

Learn about the components of Microsoft Power Platform, the business value for customers, and how the technology works with other Microsoft products.

Learn how you can use Power BI to easily build reports and dashboards with interactive visualizations and AI-driven insights. See how other organizations have used this solution to drive business results with actionable insights.

This module explains the basic infrastructure components of Microsoft Azure. You'll learn about the physical infrastructure, how resources are managed, and have a chance to create an Azure resource.

Source control is a critical tool used by developers and devops professionals to manage and maintain code. Describe the purpose and use of source control is an introduction to source control. It starts out explaining source control as a concept, then delves into one of the most popular source control platforms around, and finishes with guiding you through creating your first source controlled file and handling updates.

Select the most appropriate Windows Server administration tool for a given situation and learn how to use that tool.

This module helps you plan a container build strategy, explains containers and their structure, introduces Docker, microservices, Azure Container Registry, and related services.

Learn how to design a data ingestion solution for training data used in machine learning projects.

Identify strategies for managing relationships between data entities, such as customers and sales data. Improve data-model performance and scaling by pre-aggregating and denormalizing your data. Use change-feed to maintain your data's referential integrity.