kars is a secure, Kubernetes-native runtime for AI agents on Azure: one hardened sandbox per agent, zero credentials in the agent process, an in-pod inference router that brokers every external call, and an end-to-end encrypted inter-agent mesh. Governance is consumed from the Microsoft Agent Governance Toolkit (AGT). Source: https://github.com/Azure/kars (MIT). Docs are mdBook Markdown under docs/.
A reference implementation, built from open-source components (Kubernetes, Kata Containers, QEMU/OVMF, NVIDIA GPU Operator, Node Feature Discovery, and Trustee for attestation), that extends CPU + GPU confidential computing to Kubernetes workloads. It protects data-in-use and model IP for regulated/enterprise AI by running GPU workloads inside hardware-based Trusted Execution Environments (TEEs: AMD SEV-SNP or Intel TDX) with GPU passthrough. Scope notes for agents and readers: - This is a REFERENCE IMPLEMENTATION with example component choices, not a locked spec or turnkey…
Declarative workflow descriptor (YAML) with swappable backends. Describe a workflow once — tasks, dependencies, resources, and launch methods — and run it on Slurm or locally (Docker and Kubernetes planned). sflow ships AI agent skills for writing and debugging sflow YAML, installable with sflow skill.
A reference architecture for AWS networking best practices, covering enterprise network design across five pillars: Foundation, Connectivity, Application Networking, Security, and Observability. This guide provides opinionated, production-ready networking guidance for AWS environments. It assumes multi-account AWS Organizations deployments, treats IPv6 as a core element, and includes cost implications in every architectural decision. Essential building blocks that everything else depends on. How AWS resources communicate with the internet, with each other, and with networks outside AWS. Traffic distribution, service discovery, and…
Microsoft Foundry cookbook of runnable Jupyter notebook recipes, hands-on AI guides, and examples for building agents, model inference, and multimodal apps. Forgebook recipes are authored as Jupyter notebooks and rendered as public recipe pages. For LLM context, prefer the Markdown recipe links below: they contain the notebook narrative and code in a compact text format without site navigation or client-side UI. Publishing is explicit. Notebook source files live in notebooks/, public metadata lives in registry.yaml, author profiles live in authors.yaml,…
A daily, deterministic aggregation of factual changes to public Microsoft Copilot documentation (Microsoft Learn), the public Microsoft 365 Roadmap, and the public Microsoft 365 Message Center archive. Each entry records what changed and when, classified by product and smart-tagged for retrieval. Independent, community-run aggregation. NOT an official Microsoft notification service. Message Center content varies by tenant; roadmap items change. Always confirm against the linked source before acting. A daily, deterministic aggregation of factual changes to public Microsoft Copilot guidance: Microsoft…
Eleven open-source Power BI templates, PowerShell exporters, and add-ons from Microsoft's Copilot ROI Advisory Team that turn your tenant's audit logs and Viva Insights data into a complete picture of Microsoft Copilot adoption, impact, sentiment, and readiness. The canonical source is https://microsoft.github.io/Analytics-Hub/ and https://github.com/microsoft/Analytics-Hub. A daily, machine-readable aggregation of factual changes to public Microsoft Copilot guidance (Microsoft Learn docs, the public Microsoft 365 Roadmap, and the public Message Center archive), classified by product and smart-tagged. Independent community aggregation, not an…
Eval Recipes is a an evaluation framework that makes it easy to evaluate LLM chat assistants, and does so at a high degree of quality. We use recipes to develop specialized evaluation workflows that score conversations on dimensions such as how well the assistant adhered to user preferences or if they did not generate any hallucinations. The built-in claim_verification evaluation is based on these two papers: Claimify and VeriTrail. This is not an official implementation of either. Whenever you use…
Hexana is a WebAssembly and binary analysis toolkit by JetBrains, available as an IntelliJ Platform plugin (org.jetbrains.hexana) and a VS Code extension (JetBrains.hexana-wasm). It parses .wasm binaries, renders WAT and…
The Azure SQL Database engine, running locally for development and CI. Build and test against the same engine, defaults, and T-SQL you run in the Microsoft Azure cloud, with AI-native capabilities built in. Free for local development; no Azure subscription required. Lift and shift to Azure SQL Database in the cloud is a connection-string change, not a code change. Status: Private Preview. Last updated: August 2026. Layered knowledge: each skill bundles its instructions and version-pinned config shapes, and can optionally…
This file is the auto-generated concatenation of all agent-facing docs for the PolyStella package. Regenerate with pnpm build:llms. Constituent files (in order): - AGENTS.md - PACKAGE_ARCHITECTURE.md - ARCHITECTURE.md - skills/polystella-consumer/SKILL.md - skills/polystella-contributor/SKILL.md PolyStella — an Astro integration that translates content into additional locales at build time using AI, caches translations in Cloudflare R2, and injects locale-prefixed routes. This file is the entry point for coding agents working on the PolyStella package itself. Four companion docs: - PACKAGE_ARCHITECTURE.md — post-migration package…
AI-driven content localization for Astro: build-time translation of Markdown/MDX/TOML/JSON/YAML into additional locales, cached in Cloudflare R2, with locale-prefixed routing. PolyStella is an Astro integration plus four published packages (core, EmDash, Astro, and a compatibility shim). Translations happen at build time, are content-addressed (source bytes + glossary + model), cached in R2, and rendered as static bytes — no runtime AI calls. The Astro package includes the integration and a polystella CLI with verb-style subcommands (translate, check-ui, sync-ui, translate-ui). Direct flow:…
Python package for analyzing and visualizing Microsoft Viva Insights data. Use these established workflows instead of reimplementing Viva Insights aggregation, segmentation, or visualization logic. Conventions: - Import as import vivainsights…
This file is regenerated on every build by docshooks/llmstxt.py with the full concatenated docs corpus for deep ingestion by AI agents. If you are reading this placeholder, the build hook did not run.
This file is regenerated on every build by docshooks/llmstxt.py with a curated, grouped index of every page. If you are reading this placeholder, the build hook did not run. See https://llmstxt.org/ for the spec.
Release capsules for Microsoft Foundry model announcements — each pairs a model release with a runnable notebook. A capsule is a folder holding a README and a Jupyter notebook you can run against your own Foundry project. Announcements are tracked in CHANGELOG.md, newest first, grouped by month. Capsules are indexed in CAPSULE-TOC.md, grouped by provider. catalog.json holds this same index in structured form.
Microsoft Korea 공식 솔루션 허브. Azure, AI, 보안, 데이터, Microsoft 365, 앱 현대화 분야의 솔루션 설명 자료와 실습 워크샵, 최신 기능 업데이트를 한곳에서 제공합니다. (Official Microsoft Korea hub for solution guides, hands-on workshops, and product update feeds.) 주요 콘텐츠는 한국어로 제공되며, 방문자 이용 패턴 분석을 위해 Google Analytics와 Microsoft Clarity를 사용합니다. 개인 식별 정보는 의도적으로 수집하지 않습니다.
A Hydrogen storefront (React Router) pre-wired to mock.shop, Shopify's auth-free Storefront API with 100+ fictional stores. Clone it, run npm install and npm run dev, and you are browsing a store. Switch stores with one environment variable; switch to a real Shopify store when you are ready.