Browse All Posts (151)

Anna Hoffman explains how Microsoft SQL spans on-premises, Azure, and Microsoft Fabric, highlighting what’s new in the engine, developer tooling, and migration options. She also demonstrates AI-assisted performance troubleshooting and scalable vector search, and shows how Azure Arc/Azure Local and Foundry-based experiences can support modern data-driven apps.

Sukhwant Kaur demonstrates how SQL database in Microsoft Fabric can support app development, analytics, and AI in one place—covering database creation, workload migration, and automatic mirroring into OneLake, plus Git-based workflows with VS Code and a T-SQL RAG example for product search.

David Pless explains how Azure SQL Database Hyperscale’s cloud-native architecture lets teams scale compute, storage, and read capacity independently, and how features like serverless compute, elastic pools, named replicas, and snapshot-based backups map to different workload and availability needs.

Patrick LeBlanc demonstrates Fabric Database Hub’s database agent for observing SQL Server databases, surfacing performance signals, and guiding investigation from detection through hands-on troubleshooting, including a blocking scenario in SSMS and follow-up analysis workflows in VS Code with GitHub Copilot support.

Borko Novakovic explains how Azure SQL Managed Instance (SQL MI) aims to make it easier to move SQL Server workloads to Azure while modernizing over time, with demos around replication and minimal-downtime migration plus a look at new performance configuration options and update-policy trade-offs.

Bob Ward explains what “AI-ready” means in SQL Server 2025, focusing on native vector capabilities, embedding generation, and RAG patterns you can implement directly with T-SQL across local and cloud AI model deployments.

Pam Lahoud explains how to migrate SQL Server workloads to Azure Virtual Machines while keeping OS and database control, with practical guidance on VM sizing, storage selection, and cost considerations like constrained cores for licensing. She also outlines what to build next using Azure services and related Microsoft data/AI capabilities.

Amit Khandelwal demonstrates an end-to-end migration of a working app from SQL Server to Azure SQL Database Hyperscale, using SSMS assessments and VS Code tooling to evaluate readiness, address blockers, and execute a BACPAC-based move. He also shows GitHub Copilot helping resolve a Service Broker issue and validating the cutover.

Alicia Li summarizes Q3 2026 updates to Microsoft Fabric Eventstreams, focusing on new managed and custom connectors, CDC ingestion from operational databases, schema registry and schema-aware processing for mixed event types, in-flight enrichment with Delta tables, improved monitoring and diagnostics, and stronger deployment and networking controls.

Visual Studio Code introduces Canvases (Preview), a shared workspace concept in VS Code designed to help teams plan releases, prioritize backlog work, and collaborate with a coding agent using contextual cards that can be turned into actionable plans.

Allison announces a GitHub repository governance update that lets you convert all classic branch protection rules into repository rulesets in one action, making it easier to standardize and manage branch policies at scale across branches and organizations.

Allison summarizes recent improvements and bug fixes in GitHub secret scanning, including an upcoming audit log field change that may affect integrations, plus updates to token revocation support, webhook payloads, and several API and push-protection edge cases.

tushar-msft summarizes January–August 2026 Graph Query Language (GQL) updates in Microsoft Fabric Graph, covering new path-finding and traversal controls, path inspection functions, multi-stage query composition, richer aggregation options, and added value/text functions (casting, ranges, Unicode normalization, and regex helpers).

Allison announces an update to the Dependabot alerts REST API that adds a new version_requirement field, making it easier to retrieve the dependency version (or constraint) recorded for an alert without parsing lockfiles or issuing separate GraphQL queries.

jovanpop-msft announces four preview T-SQL enhancements in Microsoft Fabric Data Warehouse—GROUP BY ALL, ORDER BY ALL, QUALIFY, and the FROM ... SELECT query format—aimed at reducing repetitive SQL, simplifying maintenance when projections change, and making analytical query logic easier to read.

Allison announces GitHub package firewall in public preview for GitHub Enterprise Cloud, a supply-chain security feature that inspects package metadata and downloads to block malicious dependencies before they reach CI/CD hosts or developer workstations.

Julien Dubois shares practical stories from three Java Champions using GitHub Copilot in real projects, focusing on agentic workflows, verification gates, and staying accountable for what ships—from large content migrations to debugging tricky concurrency issues on Raspberry Pi.

jovanpop-msft announces a preview update for Microsoft Fabric Data Warehouse and the SQL analytics endpoint: new and enhanced T-SQL analytical functions for distribution analysis, including exact and approximate median/quantile calculations and expanded percentile aggregate syntax.

Microsoft Developer presents SQL Modernization Day, a set of sessions from the Microsoft SQL team focused on moving SQL Server workloads to Azure without rewriting applications, and then preparing those workloads for building AI-ready apps using modern Azure and Fabric SQL options.

GitHub shows how to fix repository issues from inside JetBrains IntelliJ by installing the GitHub Copilot plugin, browsing open GitHub issues, and using Copilot to generate an implementation plan and apply the changes with its coding agent.

Waldek Mastykarz tests whether swapping a real GitHub repo for a local bare git remote changes AI coding agent behavior during evals, focusing on a rebase scenario where the agent must decide whether to push without being asked.

Julia Muiruri demonstrates an end-to-end workflow for building and shipping an AI agent directly from Visual Studio Code, using GitHub Copilot and the Foundry Toolkit extension to pick a model, test the agent against a real product catalog, deploy to Microsoft Foundry, and connect it to a website via a secure proxy.

Allison announces expanded Dependabot support for newer package manager versions (npm 12, pnpm 11/12, and Bun 1.4), so teams can upgrade and continue receiving automated dependency update PRs across GitHub.com and GitHub Enterprise Server.

Andrew Lock introduces CBOR as a compact binary alternative to JSON and explains where it fits compared to formats like Protobuf and MessagePack. He then demonstrates how to read and write CBOR in .NET using the low-level System.Formats.Cbor APIs, including conformance modes and practical decoding patterns.

John Edward explains how to monitor Copilot Studio agents in production by combining conversation analytics with application telemetry, security controls, and outcome-based metrics. The guide focuses on catching failures early (tool-call errors, latency, unsafe access), setting baselines and alerts, and tying cost and performance back to successful task completion.

Takuto Higuchi interviews Sindhura Bandhakavi on why AI agents get expensive at scale, and how to think about “tokenomics” beyond simply cutting tokens. The episode shows how Azure AI Foundry features like Model Router and Agent Optimizer can help balance quality, performance, and cost while keeping agent usage measurable and controlled.

Khalid Abuhakmeh shows how ASP.NET Core 11 can localize Minimal API validation errors using Microsoft.Extensions.Validation and standard resx resources, without FluentValidation or custom endpoint filters. The post includes a working Program.cs setup, resource key conventions, and an integration test harness that verifies responses across multiple cultures.

Allison announces generally available REST API endpoints for retrieving and updating GitHub Copilot model policies across enterprises, organizations, teams, and enterprise apps, making it easier to centrally control which Copilot models are available at each scope.

Allison announces that several AI models have been deprecated across GitHub Copilot experiences as of October 19, 2026, and lists the supported replacement models. The post also calls out what Copilot Enterprise admins may need to change in model policies so alternatives show up in Copilot Chat.

Krishnaprasad Hande explains a reference architecture for running sensitive AI inference on shared Azure GPU capacity using Azure Confidential Computing, NVIDIA H100 confidential GPUs, and Protopia’s Stained Glass Transform, with attestation and key-release controls to reduce data exposure across the inference path.

Satya Nadella shares Microsoft’s view that AI models and agents should be treated as insider risks, with security controls enforced outside the model. He highlights expanded Project Perception capabilities aimed at continuously assessing agent risk, adapting permissions, and containing threats across enterprise security layers.

Kayla Cinnamon explains how to move an existing GitHub Copilot app agent session into VS Code so you can review the diff, keep the full conversation context, make manual edits, run tests locally, and push updates back to the same pull request.

GitHub demonstrates an end-to-end workflow for taking an open GitHub issue to a pull request using GitHub Copilot inside JetBrains IntelliJ IDEA, including installing the plugin, planning the work, implementing a fix, reviewing changes, and validating accessibility.

ayeshakhan announces general availability of Metrics usage insights for Azure Monitor workspace, a set of dashboards that help teams understand what’s driving metrics ingestion (time series and events), spot unused metrics, and investigate ingestion volume changes over time to optimize workspace usage and cost.

brethompson explains how Azure Container Registry now exposes a Data Transfer metric in Azure Monitor that attributes registry egress by operation, including previously “invisible” GetBlob downloads redirected to Azure Storage. The post also outlines the Storage Activity Platform built to ingest storage activity quickly enough for near-real-time metrics.

EldertGrootenboer explains how to bridge an on-premises JMS broker (using IBM MQ as the example) to Azure Service Bus Premium with a standalone Apache Artemis JMS bridge, including connection factory setup, Entra ID authentication, and practical guidance for handling duplicates safely.

Amir Jafari announces the deprecation of the Fabric data agent “custom tool” integration in Microsoft Foundry and explains how to migrate to the Fabric IQ (OneLake Catalog) tool, including portal steps and an SDK/REST approach using MCP endpoints and Entra-based authentication.

Gerald Versluis explains why existing .NET MAUI apps can crash right after the splash screen when built with Xcode 27, and walks through migrating to UIKit’s scene lifecycle—either manually or by using the .NET MAUI CLI “maui-xcode27-migration” agent skill with GitHub Copilot CLI.

Bruno Capuano shows how to use Bring Your Own Model (BYOK) with the GitHub Copilot SDK in a small .NET 10 console app, routing inference to Microsoft Foundry or Azure OpenAI while keeping the Copilot runtime. The walkthrough covers ProviderConfig, endpoint normalization, and Entra ID vs API-key authentication.

midesa announces general availability of advanced NL2SQL and advanced DAX generation for Microsoft Fabric data agents, focused on improving query correctness for enterprise schemas. The post explains the agent’s explore-then-generate approach, new creator configurations (schema descriptions and topics), and internal benchmark results showing higher accuracy and lower latency.