Browse All Posts (134)

Chu Lahlou compares Azure Document Intelligence (ADI) and Azure Content Understanding (ACU) for real-world document processing, focusing on when to use purpose-trained document models versus generative, schema-driven extraction. The guide covers OCR/layout overlap, custom extraction trade-offs, RAG-ready output, multimodal analysis, and a practical evaluation checklist.

GitHub explains an upcoming GitHub Copilot feature that intelligently routes some requests to local, on-device models (including Ollama and Microsoft Foundry Local) to reduce cloud usage, enable offline workflows, and keep sensitive data on the machine.

Erin Havens shares GitHub data showing secret leaks are scaling with the volume of code being pushed, then explains how GitHub Secret Protection is using a fast ModernBERT-based classifier to improve push protection for unstructured secrets and reduce the human cost of remediation.

Allison announces a new fine-tuned GitHub model for context-aware leaked secret detection across secret scanning alerts, push protection, and GitHub Copilot /security-review. The post explains what’s changing, where it’s available (including GHES 3.23), and how AI Credits and budgets apply to the new opt-in checks.

Taesoo Kim shares what Microsoft Security’s FORGE Lab learned while scaling AI-assisted vulnerability research across Windows and major open-source projects, including how to turn agent-discovered bugs into reproducible evidence, validated fixes, and shipped security updates.

Allison announces general availability of local sandboxing for GitHub Copilot, adding a secure execution boundary for agent-run tools and commands on developer machines across Copilot CLI, the Copilot app, and VS Code Agent Host sessions.

Allison announces an update to GitHub Copilot CLI that lets you discover and select supported local models from a running Ollama instance using the new /model picker, without restarting your session. The post also clarifies how adding local models relates to offline mode, telemetry, and remote providers.

Apoorv Gupta explains how GitHub Spec Kit can be extended for enterprise use with presets, extensions, bundles, workflows, and governed catalogs, so teams can standardize spec-driven development without forking the core toolkit.

Visual Studio Code introduces “Blobby” as the new VS Code Pet and shows how to enable it from GitHub Copilot Chat using the /vscode-pet command.

jalenmcg announces a public preview for onboarding Amazon EKS and Google GKE clusters into Azure Arc using the Azure Arc Multicloud Connector, focusing on automatic discovery, agent installation, and ongoing sync so multicloud Kubernetes can be governed and monitored from Azure.

Gareth Bland explains TokenOps: a practical way to control AI agent spend by focusing token budget where it creates real value. He breaks down why multi-turn agents get expensive fast, how cached input changes the cost curve, and which efficiency ratios help teams measure whether they’re getting leverage or just burning tokens.

The Visual Studio Code Team shares the release notes landing page for VS Code 1.142 (Insiders), with links to the commit log and closed issues so developers can track what’s changing as features land in the Insiders build.

Sreekanth Thirthala explains an upcoming Azure API Management networking change: new control-plane IPs are being added to the ApiManagement service tag, and customers using VNet internal/external on classic (v1) tiers need to update NSGs, UDRs, and firewall rules by November 30, 2026 to avoid losing management access.

hqaffesha explains how to use Azure Storage Actions in the Azure portal to change Azure Blob Storage access tiers in bulk without writing scripts. The post walks through creating a Storage Task, defining tier-based conditions, assigning it to a storage account with the right RBAC role, and reviewing execution reports, with a practical cost warning before running at scale.

John Savill gives a quick, practical overview of MCP (Model Context Protocol), explaining why it matters for integrating AI with external tools and services. He frames MCP as a standard way for models to discover capabilities and interact with “target services” through local or remote MCP servers.

Allison explains why GitHub Copilot usage metrics may undercount agent activity after some IDEs moved agent sessions to the Copilot SDK, and what to do to restore accurate reporting. The post lists the fixed IDE versions, what report gaps to expect, and why missing data can’t be backfilled.

sbaynes outlines how “physical AI” shifts factory automation from pre-programmed instructions to systems that perceive, reason, and act in the real world. The article focuses on agent-assisted operations, scaling patterns across plants and fleets, and the governance and security controls needed when AI decisions have physical consequences.

Brian Celenza explains how GitHub is redesigning its Git storage architecture to handle “agentic” development at extreme scale, where pushes, merges, and CI fan-out happen concurrently and continuously. The post outlines the bottlenecks in today’s replica-based design and the principles behind a new storage/compute split.

Rory Preddy demonstrates an end-to-end workflow in VS Code using GitHub Copilot to build and debug a Java Spring Boot app, then expose app capabilities as MCP tools and validate behavior with Playwright tests.

Allison announces general availability of GitHub stacked pull requests, a workflow for breaking large changes into smaller PRs that can be reviewed independently and merged together. The update includes improvements to rebasing, merge queue behavior, approvals preservation, commit signing, webhooks, and GitHub CLI support.

Microsoft Developer explains why an AI agent’s output quality depends on the context you can retrieve at runtime, and shows how Foundry IQ-style capabilities connect agents to enterprise data, ground responses, and enable actions across business workflows.

Mahmoud A. Atallah shows how he uses GitHub Copilot agents in VS Code to turn meeting transcripts and other customer inputs into structured requirements and execution-ready delivery artifacts, then enriches them with Azure guidance via MCP servers and the Well-Architected Framework.

Alex Weininger introduces the Canvas authoring plugin, which guides GitHub Copilot through the native create-canvas workflow to generate an Azure canvas app based on Microsoft Canvas Toolkit, including a read-only starter and patterns for safe, explicitly scoped Azure operations.

Poornima99 announces the general availability of the GitOps with Argo CD extension for Azure Kubernetes Service (AKS), highlighting Microsoft-managed lifecycle, Entra ID SSO, workload identity federation for ACR/Azure DevOps, hardened Azure Linux images, and Azure Managed Prometheus metrics for observability.

Drew Noakes explains how C# Dev Kit 11.0 (aligned with .NET 11) was rearchitected to dramatically reduce solution load times and memory usage in VS Code, while also speeding up incremental builds and improving MSBuild file editing with richer language features.

shyambasnet shows how to set up proactive monitoring for Azure VPN Gateway Site-to-Site tunnels by using diagnostic logs and an Azure Monitor alert. The post includes the exact KQL query and alert rule settings needed to notify admins as soon as a tunnel enters a Disconnected state.

Freddy Dezeure and Sesha Mani explain how frontier AI models are changing vulnerability management, and what CISOs can do to keep patching both fast and correct. The post highlights Microsoft’s use of AI “harnesses” for scanning and triage, and points to Baseline Security Mode and secure-by-default controls to reduce blast radius when patches can’t land in time.

Ayush Shekhar introduces ScreenMind, an open source project that runs a single local AI model to understand what’s on your screen, transcribe audio (like meetings), and answer questions about what it has seen—aimed at running on a GPU with as little as 4GB of VRAM.

Emanuele Bartolesi shares a practical fix for high CPU/disk usage on Windows 11 when running Claude, Codex, and GitHub Copilot tooling: adding targeted Microsoft Defender Antivirus folder exclusions. The post also calls out the security tradeoff and walks through the exact Windows Security steps to apply exclusions safely.

GitHub explains how PR limits can reduce low-quality pull requests and automated spam (“AI slop”) by letting maintainers cap the number of open PRs from external contributors, with upcoming options like counting draft PRs and allowing trusted users to bypass limits.

Victoria Hall introduces Azure Functions Agent bindings (preview) for Python, showing how to add bounded agentic reasoning via Microsoft Agent Framework while keeping deterministic function code in control. The post walks through project structure, package setup, local settings, and examples for both direct HTTP calls and Durable Functions orchestrations.

Visual Studio Code shows how to use the Thunder Client extension to send API requests and view responses directly inside VS Code, keeping API testing alongside your code while you build and debug your app.

James Rempt explains how Azure credits included with eligible Visual Studio Subscriptions can be used as a personal Azure sandbox for learning and experimentation, including how the monthly credit works, what happens when you hit the spending limit, and key constraints around non-production use and service eligibility.

Allison announces an update to GitHub code scanning that adds visibility into AI Scan for pull requests enablement in the Security Overview coverage view, including enabled/not-enabled counts, per-repo effective status, filter queries, and a new CSV export column for tracking adoption across orgs and enterprises.

Andrew Lock shows how to shrink a .NET NativeAOT binary by using ILLink.Substitutions.xml to replace a runtime-only property with a compile-time constant, letting the linker remove an otherwise “reachable” dependency chain (including Azure.Identity and MSAL) and cutting output size by roughly 22–25%.

Waldek Mastykarz introduces Agent Experience (AX): how AI agents discover, choose, and correctly use your SDKs, APIs, and CLIs. He breaks AX down into propensity and efficacy, shows why you must measure both quality and task cost, and shares practical examples from GitHub Copilot Chat evaluations.

Samu Niemelä shares practical takeaways from FabCon 2026 on how Microsoft Fabric is maturing, from Fabric IQ grounding Copilot and agents in governed business semantics to new on-demand compute and stronger monitoring and governance features for running Fabric at scale.

Maria Jose Fernandez and Kyle Ikeda explain how Azure’s savings plan for databases helps teams reduce database spend with flexible, spend-based discounts that can follow workloads across services and regions, and how it compares to (and complements) Azure Reservations.

Rob Bos shares a short pointer to his Azure Heroes session on how he works with GitHub Copilot, with a link to download the slides.

Allison announces new GitHub Secret Scanning detectors and a new partner integration, expanding the set of credentials GitHub can identify and help remediate when they’re committed to repositories.