I built an open-source tool for running ARG governance checks on a schedule and tracking findings
Most of the Azure governance work I have done over the last ten years ended the same way. Someone writes a sharp Resource Graph query, it finds something real, it gets pasted into a chat, and then it lives in that person's terminal history until they move on. The failure that costs more is quieter. A check that stops running does not turn red. It stays green, and the estate keeps drifting behind a number that nobody has any reason to distrust. Disclosure before I name anything: I built the tool below and I maintain it. RuleBeat runs the governance checks your team writes for Azure on a schedule, tracks every finding over time, and never holds write access. A check is a rule you author against Azure Resource Graph or Microsoft Graph, in a visual builder or as raw KQL. It ships 158 checks out of the box, 15 built-in rules plus the 143-rule APRL pack. Findings keep their lifecycle across scans, so they move through new, active and fixed and reopen on their own, and a suppression needs a reason and can carry an expiry date. The trade-offs, so nobody has to discover them after installing: - Read-only, permanently. It never holds write credentials and never creates its own service principal. You create the credential, so you can see in Azure RBAC exactly what it was granted. The cost is real: there is no one-click fix. Remediation stays your action under your own identity. - Self-hosted, one container, SQLite inside. Nothing about your tenant leaves your deployment and there is no telemetry. The cost is that you run it. Demo mode runs the real UI over a generated database with no Azure credential, if you would rather look before wiring anything up. - Honest numbers. A rule that has never run, or whose last run failed, is reported as unknown rather than passing. The posture number is uglier for it, and that is the point. On where this does and does not belong next to the native stack: Azure Policy is for enforcing a standard, and it does that better than anything I would write. Defender for Cloud covers its own scope well. If your assignments are enforcing, your Workbook answers the question you actually ask, and one person owns the whole loop, you do not need this. Where I kept running out of road was the organization-specific check that no built-in standard covers, and the question of who owns a flagged row once more than one person has to care about it. It is open source under Apache-2.0 and free, and it is v0.2, early on purpose. I build it with AI assistance from Claude, which the public commit history shows in the co-author trailers, and every change is human-reviewed and gated by the test suite in CI before it ships. Repo: https://github.com/rulebeat/rulebeat Docs: https://docs.rulebeat.com The question I would rather ask than answer: for those of you running recurring governance checks today, what do you do with a finding that is accepted on purpose? Every version of this I have seen was a tag, a wiki page, or a spreadsheet, and all three drift away from the query that produced them. I would like to know what has actually held up for you.Path to production for agents: a Microsoft Azure AI Tech Accelerator
Move AI agents from experimentation to production with trusted architecture, governance, and operations. Many organizations have made progress with AI prototypes, but struggle to turn early success into systems that are secure, reliable, and ready for real-world use. If you want to bridge that gap with practical, engineering-focused guidance across the full AI lifecycle—from foundational governance and architecture to deployment, security, and ongoing operation—don't miss this event. Learn how to establish trust in AI systems, design architectures that scale with control, and operate agentic solutions with confidence over time. Explore proven patterns for building production-ready foundations, managing risk and cost, and maintaining performance in dynamic, non-deterministic environments. Walk away with a clear path forward, offering actionable strategies and playbooks you can use to deliver secure, compliant, and high-performing AI solutions in your organization. Organizational policies preventing you from watching and participating here on the Tech Community? Sign in with a personal account or tune in on LinkedIn. (You'll find LinkedIn event links on each session page.) Day 1: Now on demand Build an AI Center of Excellence for agent governance Design Azure AI Landing Zones for production at scale A Microsoft blueprint for scalable agentic AI systems Day 2 - Now on demand Monitor and govern AI agents in production with AgentOps What it looks like: Trusted, compliant AI systems at scale How to keep agentic workloads orchestrated, fast, and affordableA Microsoft blueprint for scalable agentic AI systems
Explore a governance-first, multi-agent architecture that embeds consistent controls and quality checks across every layer. Many AI pilots don't fail because of technology; they fail because the architecture isn't designed for trust. Agentic AI architecture enables trusted, scalable AI systems with built-in governance and control from user interactions and agent orchestration to integrations, data, and models. See how aligning these layers under a unified security and governance framework creates a resilient, enterprise-wide AI fabric. You'll leave with a clear blueprint for building interoperable, trustworthy AI systems that are designed to scale without compromising control. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Just announced! Live Q&A will also be available July 28 from 10:00-11:00 AM SGT (UTC+8) to support attendees in Asia and western Australia. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. Organizational policies preventing you from signing in to the Tech Community? Use a personal account or tune in on LinkedIn. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.What it looks like: Trusted, compliant AI systems at scale
As AI systems move into production, the risk landscape expands beyond traditional app security. Examine emerging threats like prompt injection, data leakage, and autonomous tool misuse—and hear ways to mitigate threats using a defense-in-depth strategy. Find out how to apply layered controls across identity, data protection, orchestration, and runtime environments to keep AI systems secure and controllable. AI security and observability are essential for building trusted, compliant AI systems at scale. That's why we'll also cover how traceability, safety monitoring, and auditability help you maintain trust, prove compliance, and operate with confidence in real-world conditions. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Just announced! Live Q&A will also be available July 29 from 9:00-10:00 AM SGT (UTC+8) to support attendees in Asia and western Australia. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. Organizational policies preventing you from signing in to the Tech Community? Use a personal account or tune in on LinkedIn. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.Monitor and govern AI agents in production with AgentOps
AgentOps brings discipline and reliability to deploying, monitoring, and scaling agentic AI in production. Getting an AI agent to work once is easy. Keeping it reliable over time is not. Dive into the full lifecycle of running agentic AI in production, from evaluation and CI/CD quality gates to observability, continuous monitoring, and incident response. Learn how to apply DevOps practices to AI’s unique challenges, including non-deterministic behavior, prompt regression, model drift, and tool-calling risks. If you are looking for a practical AgentOps operating model that can increase release confidence, catch issues earlier, and connect agent performance insights back into Microsoft Foundry and Azure Monitor, this is the session for you. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Just announced! Live Q&A will also be available July 29 from 8:00-9:00 AM SGT (UTC+8) to support attendees in Asia and western Australia. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. Organizational policies preventing you from signing in to the Tech Community? Use a personal account or tune in on LinkedIn. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.How to keep agentic workloads orchestrated, fast, and affordable
Getting AI to production is only half the battle. Once agentic workloads are live, organizations face compounding challenges: token costs that grow non-linearly, latency that degrades user trust, Retrieval-Augmented Generation (RAG) pipelines that return noise instead of signal, and orchestration overhead that multiplies with every agent added to the mesh. This is where the real engineering begins. Wrap up your Path to production Tech Accelerator experience with a practical optimization playbook for agentic AI, from model selection and inference routing to prompt compression, RAG tuning, and caching strategies. Learn how to manage orchestration complexity across multi-agent systems while improving signal quality and response times. Explore FinOps practices for AI, including capacity planning, batch processing, and intelligent model routing. Walk away with actionable techniques to reduce inference costs, cut latency, and scale reliably across regions. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Just announced! Live Q&A will also be available July 29 from 10:00-11:00 AM SGT (UTC+8) to support attendees in Asia and western Australia. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. Organizational policies preventing you from signing in to the Tech Community? Use a personal account or tune in on LinkedIn. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.Build an AI Center of Excellence for agent governance
AI governance and Center of Excellence (CoE) strategies are key to scaling trusted AI. Too many AI initiatives stall in the proof-of-concept graveyard—not because of lack of innovation, but because trust, consistency, and accountability are missing. Learn how to establish an AI Center of Excellence and governance framework that acts as a consistent "quality gate" across every layer of your AI applications. See how this approach helps you deliver a single, organization-wide view of secure, responsible, and trustworthy AI so you can confidently move from experimentation to production and scale with control. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Just announced! Live Q&A will also be available July 28 from 8:00-9:00 AM SGT (UTC+8) to support attendees in Asia and western Australia. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. Organizational policies preventing you from signing in to the Tech Community? Use a personal account or tune in on LinkedIn. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.Design Azure AI Landing Zones for production at scale
If you’re moving beyond AI experiments, you need more than great models; you need a foundation you can trust. Azure AI Landing Zones enable secure, scalable AI deployment with proven architectures and governance. Learn how to use Landing Zones as your production-ready blueprint for deploying AI applications and agents with built-in guardrails for networking, identity, security, and cost control. Get insights to help you apply the Cloud Adoption Framework and the Azure Well-Architected Framework to design platforms that support innovation without sacrificing compliance. Walk away knowing how to accelerate time-to-production using validated architectures, infrastructure as code (IaC), and seamless integration with your enterprise environment. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Just announced! Live Q&A will also be available July 28 from 9:00-10:00 AM SGT (UTC+8) to support attendees in Asia and western Australia. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. Organizational policies preventing you from signing in to the Tech Community? Use a personal account or tune in on LinkedIn. This session is part of Path to production for agents: a Microsoft Azure AI Tech Accelerator. View the full agenda for more actionable strategies to help you deliver secure, compliant, and high-performing AI solutions across your organization.Proactively design, deploy & monitor resilient Azure workloads
Do you want to know how to get resilient and stay resilient? Explore the architectural features needed to uphold stringent uptime requirements for critical deployments. Learn how to design resiliency into workloads and environments by implementing Azure landing zones and infrastructure-as-code modules. We will demo native bicep and Azure Verified Modules while explaining the scenarios in which you need those. We'll also show how to use the Azure Proactive Resiliency Library, Azure Advisor and Azure Monitor baseline alerts to minimize outage impacts and increase productivity. This session is part of Tech Accelerator: Mastering Azure and AI adoption. View the full agenda for more great sessions and insights.Microsoft Data and Analytics Forum
Join the Microsoft Data and Analytics Forum on October 30, 2024, at 8:00 AM Pacific Time to ensure your data is organized, secure, and ready for AI innovation. This one-day, digital event will give attendees the insight they need to unify data and analytics on an open and governed foundation and streamline data transformation, business intelligence, and generative AI using Microsoft solutions. By joining the Microsoft Data and Analytics Forum, you’ll: Hear real-world success stories and industry best practices from other organizations using Microsoft analytics tools to drive business growth and efficiency. Future-proof your skills and stay ahead of the curve with future trends and developments in data analytics and cloud computing. Gain insight to the latest advancements and innovations across the Microsoft Intelligent Data Platform. Learn about product updates, best practices, and cost-saving programs straight from Microsoft leaders, experts, and partners. See the products in action through breakout sessions and live demos. This helps you understand how to apply these tools to your own business scenarios. Register now to make sure you’re a part of the Microsoft Data and Analytics Forum. Microsoft Data and Analytics Forum Wednesday, October 30, 2024 8:00 AM-10:00 AM Pacific Time (UTC-7)
