Weekly Azure Roundup: Resilience Playbooks and AI Load Testing
Azure news this week focuses on new resources for disaster recovery, data migration, cloud backup, and automated test creation. Step-by-step guides support business continuity, resilience, and innovation in Azure environments.
Guides for Resilience, Migration, and Data Protection on Azure
Developers have three new guides for improving business continuity, streamlining analytics migrations, and automating data backup in Azure. The disaster recovery tutorial covers Azure Databricks and Microsoft Fabric, with instructions for using Terraform and CI/CD to replicate critical data services like ADLS, Key Vault, and SQL. Those working with Databricks get a Python solution for automating Databricks failover, while Power BI and Fabric users benefit from geo-redundancy and cross-region features aligned with SLAs. Expanding on last week’s Azure Databricks best practices around security and data management, these guides extend to backup and restoration workflows and support compliance standards. Power BI and Fabric’s redundancy features build on earlier themes of reliability, automation, and ease of recovery. For teams modernizing analytics, there is a recipe for migrating from Tableau to Power BI on Microsoft Fabric. The step-by-step migration focuses on a “semantic layer first” design—meaning that business logic is centralized for less duplication and easier governance. The guide covers everything from asset mapping and workspace setup to AI integration with Power BI Copilot and ML notebooks, and includes best practices on security, naming, and model design to help ensure long-term analytics maintainability. An additional resource describes automating backup and restore for Azure Cosmos DB and Databricks, with support for self-service restores using Apache Spark. This supports scenarios like point-in-time recovery, test environment deployment, or compliance reporting. Restores can be executed before deployment or to quickly roll back production, and pipelined with CI/CD for easy workflows. Documentation and example cases make these features accessible for different organizations. All three guides expand last week’s focus on cloud data security and automation, now addressing everything from scheduled failover to migration playbooks and one-click database recovery.
- Disaster Recovery Strategies for Azure Databricks and Microsoft Fabric
- Tableau to Power BI Migration: A Semantic Layer-First Architecture for Microsoft Fabric
- How to Ensure Seamless Data Recovery and Deployment in Microsoft Azure
AI-Assisted Load Testing and Performance Workflows
A new set of AI-enabled tools for Azure App Testing allows teams to create load tests automatically. By using an Edge or Chrome browser extension, user sessions are captured and converted into JMeter scripts with the help of AI, including labeling, parameterization, and dynamic correlation. Scripts are fully editable for custom needs and can be used directly with Azure Load Testing for realistic test runs at scale. Version 4.0 focuses on minimizing manual work and supporting realistic performance engineering through feedback-driven improvement. This extends recent updates introducing AI-powered load generators in Azure. The new tools further support automated performance scenarios and make integration into existing DevOps workflows easier.
Other Azure News
The Azure SRE Agent Community Hub is now live, providing SREs and cloud app developers with a central place to trade strategies, problem-solving tips, and updates. It includes forums, a dedicated blog, and the latest product information, all designed to foster knowledge sharing for those developing reliability automation on Azure. This resource addresses recent requests for spaces to exchange practical knowledge and build collective experience with Azure reliability tools. It reflects two recent weeks of emphasis on site reliability engineering and agent-based automation.