Introduction

Completed

Azure Stack portfolio is an extension of Azure that enables customers to build hybrid applications and run them consistently across on-premises, edge locations, and cloud. Azure Stack includes Azure Stack Hyperconverged Infrastructure (HCI), Azure Stack Hub (previously Azure Stack), and Azure Stack Edge (previously Azure Data Box Edge). The last two components (Azure Stack Hub and Azure Stack Edge) are discussed in this module.

Azure Stack Hub and Azure Stack Edge represent key enabling technologies that allow customers to process highly sensitive data using a private or hybrid cloud. These technologies also allow customers to pursue digital transformation using Microsoft's intelligent cloud and intelligent edge approach. For many government customers, enforcing data sovereignty, addressing custom compliance requirements, and applying maximum available protection to highly sensitive data are the primary driving factors behind these efforts. Government customers can use these products to exercise full operational control over their environment and even operate in a fully disconnected mode. As part of a cloud solution, they provide flexibility to support multiple data classifications under various conditions.

Azure Stack Portfolio.

Infographic shows three hardware/device illustrations on the left-hand side of the infographic, each with an accompanying text description on the right. From top to bottom, the descriptions are as follows: 1. “Azure Stack Edge—Cloud-managed appliance”, 2. “Azure Stack HCI—Hyperconverged solution”, 3. “Azure Stack Hub—Cloud-native integrated system”.

Learning objectives

After completing this module, you'll be able to:

  • Explain how Azure Stack Hub helps customers to remain in control of access to their data.
  • Describe and identify key use cases for Azure Stack Edge.
  • Design a conceptual architecture using Azure products and services to support various data classifications.

Prerequisites

  • Familiarity of how data is protected at rest, in transit, and in use.
  • Familiarity with data classifications.