Browse All Posts (125)

Patrick Nikoletich explains how GitHub Copilot agent sessions can move between devices using GitHub’s shared agent runtime, the Copilot SDK, and the Agent Host Protocol, including a live demo that hosts an agent on a home Linux machine and connects to it from the Copilot CLI.

Microsoft Security Research explains why post-quantum readiness needs to cover authentication as well as encryption, and why organizations should start testing their certificate ecosystems now. The article outlines common PKI dependencies, operational risks from larger certificates and chains, and how Microsoft’s PQC TLS Pilot Program supports controlled interoperability testing.

Gareth Bland explains why AI agent costs can scale much faster than the work being done, and how context caching helps control token spend as agents take more turns.

Tsuyoshi Ushio introduces Dynamic Workflows for Azure Functions Hosted Skills, a preview feature that lets an LLM generate a typed DAG plan once and then run it durably via Durable Functions. The post explains the runtime model, safety checks, and when this approach reduces token usage and latency for event-driven apps.

Microsoft Developer explains how to debug an AI agent that’s slow or confidently wrong by turning on server-side tracing for an Azure AI Foundry project and inspecting each run step-by-step in Application Insights, including model calls, tool calls, tokens, and latency, then querying patterns with KQL.

Allison announces a GitHub change that lets users with the triage role (and higher) archive and unarchive pull requests, reducing friction for maintainers who delegate routine moderation work.

torreyt explains how noise reduction in Azure Deployment Stacks What-If makes change previews more trustworthy by filtering out false diffs caused by provider defaults and read-only/write-only properties, and shows how to run Stacks What-If via Azure CLI and Azure PowerShell.

Allison announces an accessibility improvement to GitHub timelines: screen readers can now navigate issue and pull request timelines as lists, with clearer announcements for structure, position, and newly loaded events across github.com and GitHub Enterprise Server.

Anna Hoffman recaps the key Microsoft SQL announcements shared at SQLCon/FabCon Barcelona 2026, covering hybrid and migration updates, Database Hub changes, Hyperscale improvements, SQL DB in Fabric updates, and developer-focused tooling and agent-related updates.

sbaynes explains how GitHub Copilot is rolling out local, on-device AI coding on new Windows PCs, including automatic routing between local and cloud models, a new MAI Code 1.1 Flash local model build, and sandboxed tool execution using Microsoft Execution Containers (MXC).

Allison announces a GitHub change that lets maintainers include draft pull requests when enforcing pull request limits, closing a loophole where users could open unlimited drafts. The update helps reduce repository clutter, notifications, and unnecessary CI runs caused by low-quality or spammy contributions.

tejabhutada explains practical ways to sync Jira Product Discovery ideas with Azure DevOps Epics, so approved roadmap items flow to engineering without manual re-entry and delivery status flows back to product. It breaks down what the Jira API can and can’t sync, plus the field, user, and state-mapping work that usually trips teams up.

Dan Hellem announces a new Azure DevOps Wiki editing experience built on Monaco Editor (the editor behind VS Code), highlighting Markdown-focused improvements like syntax highlighting, find/replace, better undo/redo, and autocomplete for work items, pull requests, people mentions, and wiki links.

Wiliam_Rosa explains Azure Databricks Lakeflow Jobs “Multiple Triggers” (beta), showing how to run a single job from several conditions (schedule, file arrival, table/model updates) and how to configure, monitor, and reason about concurrency and idempotency when triggers overlap.

gurjsing explains a common BYOK pitfall with Azure Key Vault and Azure Storage customer-managed keys: re-importing the same key material creates a new key version and won’t restore the original version identifier that dependent services may still require. The post lays out practical recovery, rotation, monitoring, and backup/restore guidance.

DivSwa announces public preview pricing and monthly free grants for Azure Logic Apps Automation, including what’s covered (managed environment, workflow runtime, retention, connectors, AI usage, knowledge storage, and isolated code execution) and how to track and keep eligibility for the free environment.

Allison announces that Claude Haiku 5.5 is now generally available in GitHub Copilot, positioned as a lightweight model for fast, high-volume coding tasks like subagents, quick edits, and terminal workflows, with access controlled via Copilot plan entitlements and enterprise model policies.

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.

bobmital announces the general availability of Anyscale on Azure, a managed Ray runtime that runs on Azure Kubernetes Service in the customer’s subscription. The post explains the control-plane/data-plane split, Azure-native identity and governance integration, private connectivity options, and the kinds of AI/ML workloads teams can run end-to-end.

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.

wise-r reports a production Azure Container Apps outage in the Austria East region where revisions stall at AssigningReplica and never reach image pull or container start events. The thread documents the observed event timeline, troubleshooting steps (new environment, minReplicas, network checks, ACR/managed identity), and the Kusto diagnostics error seen in the Azure Portal.

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.

Rani Borkar explains how Microsoft applies agentic AI across Azure’s hardware and infrastructure lifecycle—from demand planning and supply chain through datacenter fleet operations—to shorten decision cycles, improve reliability, and build a closed-loop learning system that keeps human judgment in control.

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.