Azure Weekly

Issue 576

23rd August 2026

Highlights this week include:

  • The August 17 outage, and the work ahead by Vlad Fedorov - GitHub's recent outages underscored the necessity for faster reliability enhancements such as scaling infrastructure, optimizing Azure use, and improving operations to manage increased commits, pull requests, and Actions runs.
  • Announcing General Availability of Managed Instance on Azure App Service by Gaurav Seth - Managed Instance on Azure App Service now provides a 99.95% production SLA, expanded regional availability in eight locations, and enhanced integration with Premium v4 features, simplifying enterprise migration of legacy .NET Framework applications with minimal code modifications.
  • AKS Hyperscale Control Plane Now in Preview by Richard Hooper - Azure Kubernetes Service now offers a hyperscale control plane preview enabling users to specify tiered capacity guarantees during cluster creation for enhanced performance and reliability.
  • Azure Quick Review (azqr) v4.0.0: What You Need to Know by Carlos Mendible - Azure Quick Review v4.0.0 adds VM sizing, Service Health analysis, SQL Server lifecycle management, and region selection capabilities with breaking changes requiring script reviews for upgrade.

And four AI related posts from my colleagues:

  • How to trust your AI-assisted data analysis by James Broome - Trust in AI-assisted data analysis hinges on maintaining a clear audit trail of how results are derived, emphasizing the need for reproducible code over polished but unverifiable outputs.
  • How to Implement Retrieval in RAG a 3-part series by Carmel Eve - Implementing effective retrieval in RAG is crucial because it ensures only relevant information is used, improving LLM response quality while enabling document citation and continuous knowledge updates. How to Implement Augmentation in RAG: Augmentation in Retrieval-Augmented Generation structures prompts with system instructions, retrieved context, and the user's question to guide LLMs toward accurate, context-aware responses while managing token limits and document formatting. How to Implement Generation in RAG: Generation in RAG depends critically on effective retrieval and augmentation for producing high-quality model responses.

🤖 AI

🔎 Analytics

🖥️ Compute

🚢 Containers

🗄️ Databases

🛠️ Developer tools

🔩 DevOps

🧬 Hybrid + multicloud

🎭 Identity

🔌 Integration

🎓 Learning and Certifications

⚖️ Management and Governance

🚌 Migration

🌐 Networking

🔐 Security

📦 Storage

🔗 Web