azure
3246 TopicsAzure customer usage attribution (CUA) - report or validate it is working?
Per this article - https://learn.microsoft.com/en-us/partner-center/marketplace-offers/azure-partner-customer-usage-attribution#example-azure-powershell If we use Azure PowerShell along with the ISV/SDC's Tracking GUID (created earlier in Partner Centre), to provision Azure VM's and other resources in end-customer tenants directly related to our IP as an ISV/SDC - how do we report or validate that this CUA is working?7Views0likes1CommentWhat’s New? Unveiling the Latest Features of the Azure Native Dynatrace Service
Introducing Multi-Subscription Monitoring for Dynatrace on Azure We’re excited to announce the general availability of Multi-Subscription Monitoring (MSM) for the Azure Native Dynatrace Service (ANDS). This powerful new capability allows customers to monitor multiple Azure subscriptions through a single Dynatrace resource—significantly simplifying the setup of observability for multiple Azure subscriptions at scale. Organizations often operate across dozens—or even hundreds—of Azure subscriptions. Until now, when setting up observability with the Azure Native Dynatrace Service, customers had to create one Dynatrace resource per Azure subscription, leading to higher operational overhead and some redundant configurations. With Multi-Subscription Monitoring, customers can now consolidate monitoring of up to 20 Azure subscriptions into a single Dynatrace resource, streamlining their operations and reducing complexity. 🧩 How It Works The feature is available directly in the Azure portal: Navigate to your Dynatrace resource. Go to Environment Configuration > Monitored Subscriptions. Click Add Subscriptions. Select the subscriptions you want to monitor—Dynatrace will automatically detect those where your managed identity has the required permissions. Click Add. Once added, the subscriptions will appear with an “Active” status, and diagnostic settings will be applied automatically based on your tag rules. ⚠️ Note: You can link up to 20 subscriptions per Dynatrace resource. If you reach the 20 subscriptions linked to one Dynatrace resource, you have to create a new Dynatrace resource in the next Azure subscription you want to link. To use MSM, the managed identity associated with your Dynatrace resource must have Owner permissions on the target subscriptions. 📘 Learn More Check out the article here for step-by-step guidance and stay tuned for updates on the Azure Tech Community blog. We look forward to your feedback! Announcing Enhanced Customization for Dynatrace OneAgent Installation on Azure VMs We’re excited to introduce a powerful new capability in the Azure Native Dynatrace Service: The installation of Dynatrace OneAgent on Virtual Machines (VMs) now supports additional parameters. This enhancement adds flexibility and control to your observability workflows—directly from the Azure portal. Previously, customers installing Dynatrace OneAgent via the Azure portal needed to manually configure important options. This included enabling system logs, choosing infrastructure-only monitoring, or setting proxy configurations. These settings were only available through CLI-based setups or post-installation. This manual configuration created friction for certain use cases, including the following: Security-conscious teams wanting to pre-configure log ingestion, proxy settings and custom installation paths. SREs managing multiple subscriptions desiring to predefine host groups and network zones for better organization and routing. With this update, we’re providing advanced configuration and automation. What’s New: Full Parameter Control at Install Time You can now configure the following parameters during agent installation via the Azure portal or CLI: Parameter Description Monitoring Mode Enable full-stack or infra-only monitoring Host Group Assign host to a logical group Network Zone Route traffic through a specific network zone Proxy Define address of proxy server Custom Host Name Custom host name for agent Enable Log Monitoring Enable/disable log monitoring Enable Auto Update Auto-update agent version Access to System Logs Enable/disable system log collection Enable Automatic Ingestion Enable/disable auto-ingestion Extensions ingest port Set custom ingest port StatsD Port Set custom StatsD port These parameters are optional, giving you the freedom to tailor the installation to your environment’s needs. 🔍 Learn More To explore the full list of parameters and their usage, check out the official Dynatrace documentation: Customize OneAgent installation on Linux — Dynatrace Docs We look forward to your feedback!59Views0likes0CommentsAzure MCPP Subscription
Hello When renewing partner benefits, an Azure subscription called MCPP Subscription appeared. We're currently receiving information that this subscription has expired and will be deleted soon. Should we worry about this? What's this subscription for, and should we do something about it?Solved51Views0likes4CommentsUnleashing the Power of Model Context Protocol (MCP): A Game-Changer in AI Integration
Artificial Intelligence is evolving rapidly, and one of the most pressing challenges is enabling AI models to interact effectively with external tools, data sources, and APIs. The Model Context Protocol (MCP) solves this problem by acting as a bridge between AI models and external services, creating a standardized communication framework that enhances tool integration, accessibility, and AI reasoning capabilities. What is Model Context Protocol (MCP)? MCP is a protocol designed to enable AI models, such as Azure OpenAI models, to interact seamlessly with external tools and services. Think of MCP as a universal USB-C connector for AI, allowing language models to fetch information, interact with APIs, and execute tasks beyond their built-in knowledge. Key Features of MCP Standardized Communication – MCP provides a structured way for AI models to interact with various tools. Tool Access & Expansion – AI assistants can now utilize external tools for real-time insights. Secure & Scalable – Enables safe and scalable integration with enterprise applications. Multi-Modal Integration – Supports STDIO, SSE (Server-Sent Events), and WebSocket communication methods. MCP Architecture & How It Works MCP follows a client-server architecture that allows AI models to interact with external tools efficiently. Here’s how it works: Components of MCP MCP Host – The AI model (e.g., Azure OpenAI GPT) requesting data or actions. MCP Client – An intermediary service that forwards the AI model's requests to MCP servers. MCP Server – Lightweight applications that expose specific capabilities (APIs, databases, files, etc.). Data Sources – Various backend systems, including local storage, cloud databases, and external APIs. Data Flow in MCP The AI model sends a request (e.g., "fetch user profile data"). The MCP client forwards the request to the appropriate MCP server. The MCP server retrieves the required data from a database or API. The response is sent back to the AI model via the MCP client. Integrating MCP with Azure OpenAI Services Microsoft has integrated MCP with Azure OpenAI Services, allowing GPT models to interact with external services and fetch live data. This means AI models are no longer limited to static knowledge but can access real-time information. Benefits of Azure OpenAI Services + MCP Integration ✔ Real-time Data Fetching – AI assistants can retrieve fresh information from APIs, databases, and internal systems. ✔ Contextual AI Responses – Enhances AI responses by providing accurate, up-to-date information. ✔ Enterprise-Ready – Secure and scalable for business applications, including finance, healthcare, and retail. Hands-On Tools for MCP Implementation To implement MCP effectively, Microsoft provides two powerful tools: Semantic Workbench and AI Gateway. Microsoft Semantic Workbench A development environment for prototyping AI-powered assistants and integrating MCP-based functionalities. Features: Build and test multi-agent AI assistants. Configure settings and interactions between AI models and external tools. Supports GitHub Codespaces for cloud-based development. Explore Semantic Workbench Workbench interface examples Microsoft AI Gateway A plug-and-play interface that allows developers to experiment with MCP using Azure API Management. Features: Credential Manager – Securely handle API credentials. Live Experimentation – Test AI model interactions with external tools. Pre-built Labs – Hands-on learning for developers. Explore AI Gateway Setting Up MCP with Azure OpenAI Services Step 1: Create a Virtual Environment First, create a virtual environment using Python: python -m venv .venv Activate the environment: # Windows venv\Scripts\activate # MacOS/Linux source .venv/bin/activate Step 2: Install Required Libraries Create a requirements.txt file and add the following dependencies: langchain-mcp-adapters langgraph langchain-openai Then, install the required libraries: pip install -r requirements.txt Step 3: Set Up OpenAI API Key Ensure you have your OpenAI API key set up: # Windows setx OPENAI_API_KEY "<your_api_key> # MacOS/Linux export OPENAI_API_KEY=<your_api_key> Building an MCP Server This server performs basic mathematical operations like addition and multiplication. Create the Server File First, create a new Python file: touch math_server.py Then, implement the server: from mcp.server.fastmcp import FastMCP # Initialize the server mcp = FastMCP("Math") MCP.tool() def add(a: int, b: int) -> int: return a + b MCP.tool() def multiply(a: int, b: int) -> int: return a * b if __name__ == "__main__": mcp.run(transport="stdio") Your MCP server is now ready to run. Building an MCP Client This client connects to the MCP server and interacts with it. Create the Client File First, create a new file: touch client.py Then, implement the client: import asyncio from mcp import ClientSession, StdioServerParameters from langchain_openai import ChatOpenAI from mcp.client.stdio import stdio_client # Define server parameters server_params = StdioServerParameters( command="python", args=["math_server.py"], ) # Define the model model = ChatOpenAI(model="gpt-4o") async def run_agent(): async with stdio_client(server_params) as (read, write): async with ClientSession(read, write) as session: await session.initialize() tools = await load_mcp_tools(session) agent = create_react_agent(model, tools) agent_response = await agent.ainvoke({"messages": "what's (4 + 6) x 14?"}) return agent_response["messages"][3].content if __name__ == "__main__": result = asyncio.run(run_agent()) print(result) Your client is now set up and ready to interact with the MCP server. Running the MCP Server and Client Step 1: Start the MCP Server Open a terminal and run: python math_server.py This starts the MCP server, making it available for client connections. Step 2: Run the MCP Client In another terminal, run: python client.py Expected Output 140 This means the AI agent correctly computed (4 + 6) x 14 using both the MCP server and GPT-4o. Conclusion Integrating MCP with Azure OpenAI Services enables AI applications to securely interact with external tools, enhancing functionality beyond text-based responses. With standardized communication and improved AI capabilities, developers can build smarter and more interactive AI-powered solutions. By following this guide, you can set up an MCP server and client, unlocking the full potential of AI with structured external interactions. Next Steps: Explore more MCP tools and integrations. Extend your MCP setup to work with additional APIs. Deploy your solution in a cloud environment for broader accessibility. For further details, visit the GitHub repository for MCP integration examples and best practices. MCP GitHub Repository MCP Documentation Semantic Workbench AI Gateway MCP Video Walkthrough MCP Blog MCP Github End to End Demo55KViews9likes5CommentsEntra External ID - password reset flow
Hello, We have started to implement Entra External ID and have reached a dead-end when it comes to password reset initiated by an external admin. The process we are trying to support: The use signs up in our client (website) The user should then automatically be generated in Entra External ID At the end of the registration, the user receives an email from Entra External ID, with a password reset link The user resets the password and is redirected back to our client -> fully logged in The only flow we are able to get to work now, is that the user sets their own password by pressing the "Forgotten password" button in the login screen in Entra External ID, but this is not going to work for us. The user should not know that they are in a different site, and for the login to be as seamless as possible, the user should just receive a password reset link in an email. It looks like this might work in Azure B2C, but we have already starting implementing Entra External ID, so we would hope and expect it to work here as well. Any help on how to solve this for Entra External ID would be highly appreciated.33Views0likes1CommentAI Innovation With Azure: From Concept to Creation
The session will explore the transformative power of Azure AI and its services, demonstrating how they can drive innovation and propel individuals and organisations to new heights. Attendees will gain insights into cloud computing concepts through real-world examples and learn how to leverage Azure AI, GitHub Codespaces, and GitHub Copilot to develop cutting-edge applications. The focus will be on building applications that redefine the future with enhanced accuracy and efficiency, while also addressing security concerns and streamlining the development process. We have the amazing https://www.linkedin.com/in/harshavardhan-bajoria here to speak to us about AI Innovation!77Views0likes2CommentsMicrosoft Learning Rooms Weekly Round up on 10/16
Below is a summary of what is happening within our Learning Rooms (Groups) so that you can stay in the loop and discover something new. To get frequent updates of their content you must follow/join the group that interests you. Make sure to join one of our Learning Rooms (Groups) today! Learning Room (Group) Details Date/Time Link to discussion/event/blog Azure Cloud Commanders Event: AI Innovation With Azure: From Concept to Creation Friday, Oct 17, 2025, 7:30 AM GMT+13 AI Innovation With Azure: From Concept to Creation | Microsoft Community Hub Modern Development with Azure Integration and AI Event: Azure Live Voice API and Avatar Creation Friday, Oct 17, 2025, 10:00 AM PDT techcommunity.microsoft.com/event/43624d95-1cb4-43ab-8b6e-e67b78fe8b98/azure-live-voice-api-and-avatar-creation/4458942 Microsoft Fabric Café Event: Securing AI in Fabric: Defending ML Workloads from Advanced Cyber Threats Friday, Oct 17, 2025, 09:00 PM PDT Securing AI in Fabric: Defending ML Workloads from Advanced Cyber Threats | Microsoft Community Hub Microsoft Hero Community Event: D365 Field Service 101 October 19, 2025 09:00 AM CET 📢 https://www.linkedin.com/in/jeevarajankumar/ 🖇️ https://streamyard.com/watch/RtDkftSxhn7P?wt.mc_id=MVP_350258 Azure Cloud Commanders Event: Security Best Practices for Azure Kubernetes Services (AKS) Monday, Oct 20, 2025, 12:00 PM PDT Security Best Practices for Azure Kubernetes Services (AKS) | Microsoft Community Hub Microsoft Hero Community Event: FSI and Gen AI: Wealth management advisor with Azure Foundry Agents and MCP October 21, 2025 19:00 PM AEST October 21, 2025 10:00 AM CET 📢 https://www.linkedin.com/in/priyankashah/ 🖇️ https://streamyard.com/watch/Vb5rUWMBN9YN?wt.mc_id=MVP_350258 Azure Cloud Commanders Event: ASO(cial) Superpowers: Streamlined App Deployments with Azure Service Operator Thursday, Oct 23, 2025, 11:00 AM PDT ASO(cial) Superpowers: Streamlined App Deployments with Azure Service Operator | Microsoft Community Hub Microsoft Hero Community Event: The Role of Sentence Syntax in Security Copilot: Structured Storytelling for Effective Defence October 25, 2025 06:00 PM CET 📢 https://www.linkedin.com/in/monaghadiri/ 🖇️ https://streamyard.com/watch/EtPkn2EZkauD?wt.mc_id=MVP_350258 Azure Cloud Commanders Event: Mastering Full Stack with Azure: Effortless Infrastructure and Well-Architected Framework Sunday, Nov 02, 2025, 08:00 PM PST Mastering Full Stack with Azure: Effortless Infrastructure and Well-Architected Framework | Microsoft Community Hub Azure Cloud Commanders Discussion: [Share] AZD-for-beginners [Share] AZD-for-beginners | Microsoft Community Hub Global Cloud & AI Community Discussion: Why should one learn AI? Why should One learn AI ? | Microsoft Community Hub Microsoft Hero Community Blog: 🚀✨ Get ready for a power-packed November with the Microsoft Zero to Hero Community! ✨🚀 🚀✨ Get ready for a power-packed November with the Microsoft Zero to Hero Community! ✨🚀 | Microsoft Community Hub38Views0likes0CommentsPartner Blog | Microsoft & Oracle: The future of enterprise cloud data for partners
In today’s fast-changing cloud and AI landscape, our partnership with Oracle represents the power of collaboration to drive customer transformation at scale. Microsoft and Oracle share a common goal: to enable organizations to modernize their data estates, accelerate AI innovation, and deliver measurable business outcomes. Oracle Database@Azure brings this vision to life by combining the best of both platforms and putting our partners at the center of that transformation. Announcements from Oracle AI World At Oracle AI World, we introduced a new set of advancements that expand what’s possible for our customers and partners. Azure Accelerate, within the Microsoft AI Cloud Partner Program, support now includes Oracle Database@Azure workloads, offering partners funding, credits, and the Cloud Accelerate Factory for zero-cost deployment assistance. This allows partners to move customers to Azure faster, reduce migration risks, and increase delivery speed. Partners will also be able to resell Oracle Database@Azure directly through Microsoft Marketplace, making it easier to package, license, and deploy solutions globally while building new revenue streams. The platform itself also continues to evolve quickly. Oracle Database@Azure now supports Oracle Base Database Service, Exadata Exascale 19c, and Oracle Database 23ai across more than 28+ regions worldwide, enabling a broad multicloud hyperscaler reach. Native Oracle GoldenGate integration with Oracle Database@Azure now connects directly to Microsoft Fabric, making it easier to unify data across systems, reduce latency, and activate AI and analytics at scale. Partners can also use Copilot Studio and Azure AI Foundry to create and deploy custom agents and low-code AI solutions powered by more than 1,900 models. Security and operations are integrated across Microsoft Defender, Sentinel, and Entra ID, giving customers AI-driven threat detection, real-time monitoring, and unified identity management. Azure Arc integration adds full visibility, policy management, and automation across hybrid and multicloud environments, allowing partners to deliver consistent governance from a single control plane. The partnership between Microsoft and Oracle builds on years of co-engineering, centered on helping customers modernize mission-critical workloads without compromise. Together, we’ve brought Oracle Exadata infrastructure directly into Azure datacenters, unifying Microsoft and Oracle ecosystems through shared networking, identity, and governance. The result is a seamless cloud experience that combines Azure’s scalability and security with Oracle’s trusted database performance. Continue reading here!52Views1like0CommentsCustomer review: Hive CPQ simplifies quoting, boosting sales and avoiding mistakes
In this customer review, Frank ter Steege, Business Development Manager, Zolare (formerly Pirisol), shares his thoughts about Hive CPQ's Hive CPQ product configurator for Microsoft Dynamics 365.78Views3likes0Comments