Browse All Posts (107)

Eric van Wijk announces a public preview of arm64 macOS build agents for Azure Pipelines, letting teams run CI workloads natively on Apple Silicon with pay-as-you-go, per-minute billing. The post shows how to enable the GitHub-hosted Agents pool, select new macOS/Xcode image labels, and monitor usage in pool analytics and Azure Cost Management.

Abhinav Premsekhar explains why cloud-hosted browsers are becoming a core platform capability for running browser automation and AI agents at scale, with a focus on the operational requirements enterprises hit in production: isolation, governance, observability, reproducibility, and geographic execution.

Anasheh announces a preview update for Microsoft Fabric Eventstreams observability in Workspace Monitoring, adding per-eventstream control so teams can choose which pipelines emit monitoring data. The post explains what telemetry is captured, where it lands, and how to query and dashboard it with KQL.

midesa announces general availability of data source routing for Microsoft Fabric data agents, explaining how a data agent decides which data sources to query when answering questions. The post focuses on improving agent responses by controlling and prioritizing where the agent looks for data across Fabric-managed sources.

Visual Studio Code highlights the Mobile Canvas extension, which lets developers control and interact with Android and iOS apps directly from within VS Code.

NevenaNikolic explains Fabric Data Warehouse Query Acceleration (Preview), a GPU-powered execution capability that automatically offloads eligible parts of SQL query plans to GPUs. The post covers where it helps most (high concurrency), which operators benefit, how fallback to CPU works, and how to monitor impact using SSMS and Query Insights.

Haoran Cheng announces five new Claude capabilities in Microsoft AI Foundry hosted on Azure—structured outputs, web search, web fetch, an MCP connector, and tool search—focused on turning a model endpoint into a production-ready agent platform with clearer governance, cost controls, and operational guidance.

dotnet covers upcoming and recent C# language features, focusing on union types for modeling closed sets of shapes (common in wire protocols), plus a look at extension members and closed classes and how these features aim to make consuming code clearer and safer.

dotnet explains how to add practical AI capabilities to .NET apps using Microsoft.Extensions.AI, starting with features like summarization, classification, and semantic search across cloud and local models, then extending the same foundations into agentic systems with the Microsoft Agent Framework.

Microsoft Developer introduces SQL MCP Server, a Data API Builder-based approach for letting AI tools like GitHub Copilot query SQL Server, Azure SQL, and Fabric SQL Database through a governed, RBAC-enforced interface instead of direct raw SQL access.

Microsoft Developer explains how to implement practical, high-performance vector search in SQL Server using DiskANN, including how to store vectors, build the right indexes, and write queries that combine semantic similarity with relational filters and full-text search for more precise results.

Ayan Gupta explains how GitHub Copilot canvases provide a durable workspace for agentic development, making plans, decisions, progress, and approval points easier to track than chat alone. He shares two concrete canvases—Java Modernization Studio and Site Studio—and discusses the up-front AI credit cost versus long-term workflow efficiency.

John Savill runs through a fast-paced AI-103 study cram focused on building AI apps and agents on Azure, covering Azure AI Foundry concepts, model selection and deployment options, API/SDK usage, evaluations, and agent tooling including Microsoft Agent Framework and Foundry Agent Service.

This week's ML roundup spans practical platform work and model-facing guidance, from Fabric Runtime 2.0 reaching GA for Spark workloads to new Lakehouse targets for dbt jobs and better near real-time capacity monitoring in Real-Time Hub. On the application side, the RAG guidance makes a clear point: vector search is only candidate generation, and rank fusion plus reranking determine what your system actually uses. We also look at production-focused inference improvements on AKS with NVIDIA Dynamo and Blob Storage integrations, and a research update on CARE-X that combines vision-language modeling with calibration, grounding, and tool-augmented measurement for radiology workflows.

This week in .NET centers on staying current and testing early: Microsoft shipped August 2026 servicing updates for .NET 10, 9, 8, and .NET Framework, while .NET 11 Preview 7 continued to advance runtime, SDK, and the major app stacks. On the AI side, Microsoft.Extensions.AI added routing and failover primitives that help teams run multi-model and multi-endpoint setups more safely, and Copilot workflows picked up practical improvements from instruction hygiene guidance to local Ollama-based integrations. Rounding things out, Visual Studio 18.9 improved Git submodule management inside the IDE, and agent governance guidance focused on reducing Teams noise and enforcing runtime allow/deny tool-call policy with auditing.

This week's DevOps roundup centers on two pressures colliding in real workflows: supply chain attacks that arrive through everyday repo automation, and a push to run AI agents with controls you can actually audit. We cover the ChainDrop (Shai-Hulud) npm worm and what it means for repository configs, tokens, and automated dependency updates, then dig into GitHub's tightening governance layer with OAuth hardening, ruleset migration, and new org-level Rule insights. We also look at agent-ready platform patterns (hardware-isolated sandboxes, APIM as a policy gateway, and OpenTelemetry-based run traces) plus practical reliability tooling that turns telemetry into SLI/SLO signals and ITSM-synced incidents.

This week's AI roundup centers on shipping agents safely and paying for them predictably, from GitHub Copilot's expanding model lineup (and upcoming deprecations) to richer per-model token reporting for chargeback. MCP continued its shift into everyday tooling with faster VS Code setup, clearer enterprise guidance on auth and governance, and more concrete patterns for packaging and distributing tool access via Agent Plugins. On Azure and Foundry, the focus stayed operational: hosted agents as containers with tracing, sandboxed execution for risky workloads, and routing model and tool traffic through an AI gateway for consistent policy and telemetry. We also saw practical improvements in content extraction (Azure Content Understanding), RAG relevance discipline (reranking plus better vector indexing), and reliability and cost controls that treat agents like any other production service.

This week's GitHub Copilot roundup is about operational reality: more models in the picker, more places Copilot runs, and better tools to understand what it costs. New options like Gemini 3.7 Flash, Grok 4.6, Kimi K3, and MAI-Code-1.1-Flash push model selection into normal platform governance, while improved token visibility and per-model usage reporting make spend easier to attribute. On the agent side, Agent Plugins 1.0 GA and smoother MCP setup make portable, tool-driven workflows more practical, with clearer patterns for guardrails like allowlists, least privilege, and PR-based review. Across IDEs and enterprise environments (including GHES 3.22 RC), the message is consistent: treat Copilot like part of your toolchain, with policies, instructions, and review paths that keep outputs safe and repeatable.

This week in Azure, the story is how teams turn agent prototypes into production systems with repeatable runtimes, safer execution, and enforceable tool governance. Updates across Foundry Agent Service, Azure Functions Serverless Agents, and Container Apps Sandboxes show practical patterns for observability, isolation, and policy-driven control over tool calls and MCP-based integrations. On the operations side, Azure Monitor expands lower-cost logging options, Application Insights improves tracing in API Management policies, and the Reliability Starter Kit provides a runnable path from SLIs/SLOs to automated response. Rounding things out are workflow improvements in azd and App Service deployment, plus concrete guidance on cost control, retrieval quality (vector indexing and reranking), and the infrastructure work that supports faster, cheaper AI serving.

This week in Security focuses on how real-world attacks and platform changes are reshaping day-to-day defensive work. The ChainDrop (Shai-Hulud) npm worm is a reminder that supply chain incidents can spread through repo automation and developer tooling, so playbooks need to cover hooks, configs, and token scope - not just dependency diffs. On the platform side, GitHub shipped OAuth improvements (multiple redirect URIs and refresh tokens), GHES 3.22 RC tightened repository controls, and license detection updates will change some SBOM and compliance outputs. We also cover time-sensitive patch and version deadlines across Windows, .NET, and Defender for Endpoint on Android, plus practical guardrails for agentic workflows (sandboxes, gateways, MCP safety, and runtime tool-call policy).

Authorised Territory demonstrates integrating the GitHub Copilot SDK with the .NET Microsoft Agent Framework, using Ollama to run models locally as part of an agent-style workflow.

John Edward explains Microsoft’s required Microsoft Defender for Endpoint update on Android ahead of infrastructure changes, including the minimum supported app version and the rollout timeline. The post focuses on what IT admins should do to avoid disruptions to mobile threat protection across managed and user-updated devices.

Harel Broitman explains how to connect Azure Monitor issues with ServiceNow ITOM so incidents and alerts stay linked and status changes sync both ways during an active response, reducing manual copy/paste and keeping technical investigation context aligned with ITSM workflows.

DevClass reports on ChainDrop, a new Shai-Hulud npm worm variant that compromises packages via tarballs and can persist through repository configuration files, enabling credential theft and further propagation. The article explains how the attack spreads through npm, GitHub, and developer tools like VS Code, and outlines practical checks and mitigations.

Peter Steinberger shares how teams can scale developer output through compounding workflow automation, where small experiments turn into practical tools and an ecosystem that helps developers move quickly without sacrificing safety.

Allison announces updates to GitHub OAuth Apps and GitHub Apps that tighten authentication security: optional short-lived access tokens with refresh tokens, support for up to 10 redirect URIs per OAuth app, and configurable wildcard matching for redirect URIs, including guidance on when wildcard redirects can be risky.

Cameron Tomisser shares a short weekly developer-news roundup covering Kimi K3’s availability in GitHub Copilot, new Microsoft guidance for building multi-agent systems with Microsoft Agent Framework, and Azure AI Foundry’s continued push toward a multi-model ecosystem.

Microsoft Developer hosts a half-day event on the Model Context Protocol (MCP), explaining how the open standard connects AI models to tools and data, and walking through hands-on sessions for building MCP servers. It also covers enterprise readiness topics like authentication, governance, and security.

Francesco Bonacci joins GitHub’s Open Source Friday to discuss Cua’s approach to computer-use agents, including the Lum and Cua Driver projects, how they benchmark and evaluate agent behavior, and what changes when you move from screenshot-driven automation to more policy-driven, capable agents.

Allison announces that Grok 4.6 (xAI’s reasoning model) is rolling out in GitHub Copilot, with notes on where it can be selected, which Copilot SKUs get access, how admins enable it for Business/Enterprise, and how it’s billed under usage-based pricing.

Sam Zhang explains how GitHub Agent Apps extend GitHub Copilot’s agent workflow so teams can scope work, review dependency risk, roll out feature flags, and assess deployment risk directly from issues and pull requests using Marketplace integrations like Amplitude, Endor Labs, LaunchDarkly, and PagerDuty.

John Savill shares a short Azure update for 14th August 2026, covering a channel milestone plus a set of platform changes across App Service, AKS, networking, security, storage, Fabric, PostgreSQL, and AI—including a note about Gemini 3.7 Flash appearing in GitHub Copilot.

Rory Preddy demonstrates how to expose Spring Boot Java methods as MCP tools, connect them to Visual Studio Code, and enable GitHub Copilot to call those tools to update a working application.

Visual Studio Code shows how to get GitHub Copilot in VS Code using the GitHub MCP server without installing an extension or manually editing mcp.json configuration files.

Lee Stott explains how to take agents from development to production in Microsoft Foundry Agent Service, covering Hosted Agents (container + manifest deployment), the Agent Optimizer, deterministic Routines, Memory, Toolboxes, and end-to-end tracing with OpenTelemetry and Application Insights.

davidwright, Arnaud Lheureux, and Suzanne Daniels describe Git-APE “SaaS skills” as a playbook-style approach to turning an Azure-hosted app into a marketplace-ready SaaS offering, focusing on making key architecture and operational decisions explicit early (tenancy, identity, fulfilment, metering, and production readiness).

Allison summarizes the August 10 weekly GitHub Copilot updates, including new model rollouts, Agent Plugins 1.0 for portable plugins across Copilot tools, and workflow improvements in the Copilot app, Copilot CLI, JetBrains IDEs, and VS Code.

Arturo Quiroga explains how real-world usage reshaped the open-source Azure Architecture Diagram Builder into a guided workflow (Create → Refine → Validate & Improve → Share or Build), with concrete changes around preserving human edits, improving diagram integrity, iterating Well-Architected validation, and generating export/IaC artifacts with clear limitations.

sukkaur announces a preview of SQL database skills for Skills for Fabric, aimed at giving AI coding agents workload-specific guidance to create, connect to, query, and manage SQL databases as part of end-to-end Microsoft Fabric solutions.

Bob Ward and Anna Hoffman walk through recent improvements to vector indexing in Microsoft SQL, including new query and indexing capabilities and what to know when using vector search features in Azure SQL Database and SQL Server.