Azure API Management Your Auth Gateway For MCP Servers
The Model Context Protocol (MCP) is quickly becoming the standard for integrating Tools 🛠️ with Agents 🤖 and Azure API Management is at the fore-front, ready to support this open-source protocol 🚀. You may have already encountered discussions about MCP, so let's clarify some key concepts: Model Context Protocol (MCP) is a standardized way, (a protocol), for AI models to interact with external tools, (and either read data or perform actions) and to enrich context for ANY language models. AI Agents/Assistants are autonomous LLM-powered applications with the ability to use tools to connect to external services required to accomplish tasks on behalf of users. Tools are components made available to Agents allowing them to interact with external systems, perform computation, and take actions to achieve specific goals. Azure API Management: As a platform-as-a-service, API Management supports the complete API lifecycle, enabling organizations to create, publish, secure, and analyze APIs with built-in governance, security, analytics, and scalability. New Cool Kid in Town - MCP AI Agents are becoming widely adopted due to enhanced Large Language Model (LLM) capabilities. However, even the most advanced models face limitations due to their isolation from external data. Each new data source requires custom implementations to extract, prepare, and make data accessible for any model(s). - A lot of heavy lifting. Anthropic developed an open-source standard - the Model Context Protocol (MCP), to connect your agents to external data sources such as local data sources (databases or computer files) or remote services (systems available over the internet through e.g. APIs). MCP Hosts: LLM applications such as chat apps or AI assistant in your IDEs (like GitHub Copilot in VS Code) that need to access external capabilities MCP Clients: Protocol clients that maintain 1:1 connections with servers, inside the host application MCP Servers: Lightweight programs that each expose specific capabilities and provide context, tools, and prompts to clients MCP Protocol: Transport layer in the middle At its core, MCP follows a client-server architecture where a host application can connect to multiple servers. Whenever your MCP host or client needs a tool, it is going to connect to the MCP server. The MCP server will then connect to for example a database or an API. MCP hosts and servers will connect with each other through the MCP protocol. You can create your own custom MCP Servers that connect to your or organizational data sources. For a quick start, please visit our GitHub repository to learn how to build a remote MCP server using Azure Functions without authentication: https://aka.ms/mcp-remote Remote vs. Local MCP Servers The MCP standard supports two modes of operation: Remote MCP servers: MCP clients connect to MCP servers over the Internet, establishing a connection using HTTP and Server-Sent Events (SSE), and authorizing the MCP client access to resources on the user's account using OAuth. Local MCP servers: MCP clients connect to MCP servers on the same machine, using stdio as a local transport method. Azure API Management as the AI Auth Gateway Now that we have learned that MCP servers can connect to remote services through an API. The question now rises, how can we expose our remote MCP servers in a secure and scalable way? This is where Azure API Management comes in. A way that we can securely and safely expose tools as MCP servers. Azure API Management provides: Security: AI agents often need to access sensitive data. API Management as a remote MCP proxy safeguards organizational data through authentication and authorization. Scalability: As the number of LLM interactions and external tool integrations grows, API Management ensures the system can handle the load. Security remains to be a critical piece of building MCP servers, as agents will need to securely connect to protected endpoints (tools) to perform certain actions or read protected data. When building remote MCP servers, you need a way to allow users to login (Authenticate) and allow them to grant the MCP client access to resources on their account (Authorization). MCP - Current Authorization Challenges State: 4/10/2025 Recent changes in MCP authorization have sparked significant debate within the community. 🔍 𝗞𝗲𝘆 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 with the Authorization Changes: The MCP server is now treated as both a resource server AND an authorization server. This dual role has fundamental implications for MCP server developers and runtime operations. 💡 𝗢𝘂𝗿 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: To address these challenges, we recommend using 𝗔𝘇𝘂𝗿𝗲 𝗔𝗣𝗜 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 as your authorization gateway for remote MCP servers. 🔗For an enterprise-ready solution, please check out our azd up sample repo to learn how to build a remote MCP server using Azure API Management as your authentication gateway: https://aka.ms/mcp-remote-apim-auth The Authorization Flow The workflow involves three core components: the MCP client, the APIM Gateway, and the MCP server, with Microsoft Entra managing authentication (AuthN) and authorization (AuthZ). Using the OAuth protocol, the client starts by calling the APIM Gateway, which redirects the user to Entra for login and consent. Once authenticated, Entra provides an access token to the Gateway, which then exchanges a code with the client to generate an MCP server token. This token allows the client to communicate securely with the server via the Gateway, ensuring user validation and scope verification. Finally, the MCP server establishes a session key for ongoing communication through a dedicated message endpoint. Diagram source: https://aka.ms/mcp-remote-apim-auth-diagram Conclusion Azure API Management (APIM) is an essential tool for enterprise customers looking to integrate AI models with external tools using the Model Context Protocol (MCP). In this blog, we've emphasized the simplicity of connecting AI agents to various data sources through MCP, streamlining previously complex implementations. Given the critical role of secure access to platforms and services for AI agents, APIM offers robust solutions for managing OAuth tokens and ensuring secure access to protected endpoints, making it an invaluable asset for enterprises, despite the challenges of authentication. API Management: An Enterprise Solution for Securing MCP Servers Azure API Management is an essential tool for enterprise customers looking to integrate AI models with external tools using the Model Context Protocol (MCP). It is designed to help you to securely expose your remote MCP servers. MCP servers are still very new, and as the technology evolves, API Management provides an enterprise-ready solution that will evolve with the latest technology. Stay tuned for further feature announcements soon! Acknowledgments This post and work was made possible thanks to the hard work and dedication of our incredible team. Special thanks to Pranami Jhawar, Julia Kasper, Julia Muiruri, Annaji Sharma Ganti Jack Pa, Chaoyi Yuan and Alex Vieira for their invaluable contributions. Additional Resources MCP Client Server integration with APIM as AI gateway Blog Post: https://aka.ms/remote-mcp-apim-auth-blog Sequence Diagram: https://aka.ms/mcp-remote-apim-auth-diagram APIM lab: https://aka.ms/ai-gateway-lab-mcp-client-auth Python: https://aka.ms/mcp-remote-apim-auth .NET: https://aka.ms/mcp-remote-apim-auth-dotnet On-Behalf-Of Authorization: https://aka.ms/mcp-obo-sample 3rd Party APIs – Backend Auth via Credential Manager: Blog Post: https://aka.ms/remote-mcp-apim-lab-blog APIM lab: https://aka.ms/ai-gateway-lab-mcp YouTube Video: https://aka.ms/ai-gateway-lab-demoLogic Apps Aviators Newsletter - July 25
In this issue: Ace Aviator of the Month News from our product group News from our community Ace Aviator of the Month July’s Ace Aviator: Şahin Özdemir What's your role and title? What are your responsibilities? I currently work for Rubicon Cloud Advisor, a Dutch company specialized in digital transformations, cloud adoption and AI implementation. At Rubicon I fulfil the role of Application and Integration architect, while also being a Professional Scrum Trainer at Scrum.org. Even though this sounds like two completely different roles, in practice both go closely hand in hand. I firmly believe that good architecture, a strong development process, and application of best practices are key pillars for delivering high-quality solutions to my clients. Therefore, both roles come in handy in my day-to-day job (combined with my strong background in software development).\ I work closely with companies and their teams in making their journey to Azure - especially Azure Integration Services - successful. Most of the time this journey starts with a business need or challenge, and I work with my clients to get a deeper understanding of their needs. This results in further analysis, capturing requirements, defining architecture, solution design, setting the stage for development (ALM) and being involved in quality assurance. At the same time, I think it’s important to stay relevant from a technical perspective. That’s why I also like being involved with implementing the solution. This way, I hear the technical struggles teams face and I can help them to find the right solution. Can you give us some insights into your day-to-day activities and what a typical day in your role looks like? Not a single day is the same, although there are some recurring activities. Specific parts of my day (or sprint) are dedicated to Scrum-related activities - whether it's participating in the daily scrum, having sprint reviews with stakeholders, planning the next sprint, or refining the backlog with the team or just aligning with the PO or stakeholders. I’m frequently involved in cross-organizational meetings focused on projects at scale. I contribute from the perspective of architecture, technical expertise, and integration strategy. In my role as a solution architect, I'm engaged in designing and implementing a critical integration platform for my client. This platform connects and exchanges data between many internal departments and external vendors - an effort that requires frequent alignment and collaboration. I’m always looking for opportunities to expand our Hybrid Integration Platform itself. Exploring how Azure resources may add value to our platform and working closely with the team to realize such improvements to the platform’s capabilities is something I enjoy. Outside of the regular meetings, I often focus on designing new integrations. Having working sessions with stakeholders to understand what they want. Based on these discussions, I assess the technical and architectural aspects of the solution. Every integration that lands on the platform is measured against both architectural and development principles and guidelines. I contribute to reviewing the solutions that have been developed. Ensuring that each integration is high-quality, consistent, easy to understand, and maintainable. I support the platform team with, and whenever possible. And if time permits, I develop parts of the solution myself – I see this as a great way to stay relevant from a technological perspective. All the spare time I have, I spend on writing technical articles that may help others. What motivates and inspires you to be an active member of the Aviators/Microsoft community? Because I enjoy helping others. Every day I work with a team of smart professionals on integration solutions and custom code within the Azure platform. Along the way, we regularly encounter challenges, limitations, or issues. In those moments, it's incredibly helpful to find solutions online or to have a community that can think along with you. Over the past few years, there have been many occasions where I just couldn’t find a solution online for a technical problem with Logic Apps. In these cases, we either came up with a creative solution ourselves or received support from Microsoft. When the integration community faces a similar challenge, it’s pretty much wasteful to tackle the same hurdles again. By documenting an approach or solution, others may be saving their invaluable time looking for a solution. Looking back, what advice do you wish you had been given earlier that you'd now share with those looking to get into STEM/technology? It is ok that you don’t know everything. Just start doing, experiment, stay curious, challenge yourself, don’t be afraid to ask questions, fail, learn and keep going! What has helped you grow professionally? I have spent a fair amount of my career at a big consulting firm. I started off as a software engineer all the way up to senior manager and architect. A long journey like that gives great and well-dosed opportunities and learning experiences to focus on your technical (in-depth) skillset first, continued by working on you soft skills like consulting, guiding and leading teams, solutioning and architecture. If I had not followed this path at that company, I would not be the person I am now professionally. Be ok with the fact that growth doesn’t happen overnight -no shortcuts, no magic pills. It's like a good red wine that needs time to mature. So do many challenging projects, become all-round and then choose a specialization, ask for constructive feedback, fail many times and take your time to reflect and learn. And don’t forget to have a strong work ethic and ongoing curiosity to learn new things. In the end I found that - from a technological perspective-, quality attributes (the “-illities”), enterprise application integration and scrum made my heart skip a beat. So my advice is to always pursue what brings you joy! If you had a magic wand that could create a feature in Logic Apps, what would it be and why? Overall, I must say that I’m happy with the current state of Logic Apps. Nevertheless, if I had a magic wand: I would like to see that the service plans for Logic App standard would be in line with Function Apps. The plans for Function apps have way better tiers from both memory, cores and pricing perspective. And being able to scale out and in based on specific metrics is more flexible than Logic App Standard currently offers. Having more CPU/memory available in the plans would also improve the overall performance of Logic Apps in general, even though performance optimizations of many actions would also be more than welcome. What I currently really miss in the HTTP connector (and possibly others) is the ability to have better control over the request timeouts. Even though the setting is there, it is capped to 4 minutes max. In practice, we need to deliver data to external APIs that work synchronously and take more time to complete. Giving better control on these timeouts would make the usability of workflows even better! Even though some nice additions to the initialization of variables have been made recently, I would like to see the ability to initialize variables at any point in the workflow. E.g. the foreach loop can be executed in parallel, and therefore the current global variables are not thread-safe, which leads to unexpected behavior. News from our product group Logic Apps Live June 2025 Missed Logic Apps Live in June? You can watch it here. We focused on the Logic Apps big announcements from Integrate 2025. There are a lot of great things to check! Feedback Opportunity: SRE Agent + Logic Apps Discover the new Applications feature in Azure API Management, enabling OAuth-based access to APIs and products. Streamline secure API access with built-in OAuth 2.0 application-based authorization. Configure SQL Storage for Standard Logic Apps Azure Logic Apps traditionally rely on Azure Storage to manage workflow states and runtime data. However, with the introduction of SQL as a storage provider (currently in preview), developers now have a compelling alternative that offers greater control, flexibility, and integration with existing SQL infrastructure. This post explores the benefits, configuration steps, and considerations for using SQL storage with Standard Logic Apps. Announcing General Availability: Azure Logic Apps Standard Automated Test Framework We’re excited to announce the General Availability (GA) of the Azure Logic Apps Standard Automated Test Framework—a major step forward in enabling developers to build, test, and maintain enterprise-grade workflows with confidence and agility. Announcing General Availability: Azure Logic Apps Standard Custom Code with .NET 8 We’re excited to announce the General Availability (GA) of Custom Code support in Azure Logic Apps Standard with .NET 8. This release marks a significant step forward in enabling developers to build more powerful, flexible, and maintainable integration workflows using familiar .NET tools and practices. With this capability, developers can now embed custom .NET 8 code directly within their Logic Apps Standard workflows. This unlocks advanced logic scenarios, promotes code reuse, and allows seamless integration with existing .NET libraries and services—making it easier than ever to build enterprise-grade solutions on Azure. Business Process Tracking Reaches General Availability Business Process Tracking provides key insights to business stakeholders from your Logic Apps (Standard) implementation in an efficient and timely manner. Today, we are pleased to announce the General Availability of this capability, allowing customers to leverage in their production workloads. Announcement: General Availability of Logic Apps Hybrid Deployment Model We’re excited to announce the Public Preview of two major integrations that bring the power of Azure Logic Apps to AI Agents in Foundry – Logic Apps as Tools and AI Agent Service Connector. Learn more on our announcement post! Announcing Public Preview: Organizational Templates in Azure Logic Apps We’re excited to announce the Public Preview of Organizational Templates in Azure Logic Apps— empowering teams to author, share, and reuse automation patterns across their organization. With this release, we’re also rolling out a brand-new UI experience to easily create templates directly from your workflows—no manual packaging required! OpenTelemetry in Azure Logic Apps (Standard and Hybrid) OpenTelemetry provides a unified, vendor-agnostic framework for collecting telemetry data—logs, metrics, and traces—across different services and infrastructure layers. It simplifies monitoring and makes it easier to integrate with a variety of observability backends such as Azure Monitor, Grafana Tempo, Jaeger, and others. For Logic Apps—especially when deployed in hybrid or on-premises scenarios—OpenTelemetry is a powerful addition that elevates diagnostic capabilities beyond the default Application Insights telemetry. Logic App Standard - When High Memory / CPU usage strikes and what to do Monitoring your applications is essential, as it ensures that you know what's happening and you are not caught by surprise when something happens. One possible event is the performance of your application starting to decrease and processing becomes slower than usual. This may happen due to various reasons, and in this blog post, we will be discussing the High Memory and CPU usage and why it affects your Logic App. We will also observe some possibilities that we've seen that have been deemed as the root cause for some customers. Introducing Agent in a Day Agent in a Day represents a fantastic opportunity for customers to participate in hackathon-style contests where attendees learn how to build agents and then can apply them to their unique business use cases. For Partners, Agent in a Day represents a great way to engage your customers by building agents with them and uncovering new use cases. Introducing Confluent Kafka Connector (Public Preview) We are pleased to announce the introduction of the Confluent Kafka Connector in Logic Apps (Standard) which allows you to both send and receive messages between Logic Apps and Confluent Kafka. Confluent Kafka is a distributed streaming platform for building real-time data pipelines and streaming applications. It is used across many industries including financial services, Omnichannel retail, autonomous cars, fraud detection services, microservices and IoT deployments. Our current connector offering supports both triggers (receive) and sending (publish) within Logic Apps. News from our community Logic App Standard: Throw exceptions like a pro! Post by Şahin Özdemir Learn how to throw exceptions in Logic App Standard using a simple Compose action—no code needed, just clever workflow design. Azure Logic Apps: are you handling large blobs? Keep memory usage under control. Post by Stefano Demiliani Struggling with large blob files in Logic Apps? Learn how to keep memory usage under control and avoid out-of-memory errors with smart workflow design and a few performance-boosting tricks De SOAPing Services SOAP to REST using Azure API Management Video by Stephen W Thomas Struggling with legacy SOAP integrations from BizTalk to Azure? Check out this video on simplifying SOAP-to-REST conversions using Azure API Management and learn how easily you can manage SOAP envelopes and streamline your Logic Apps integrations! Integrating Entra ID and AI Agent workflows in Azure Logic Apps Post by Brian Veldman Discover how to build AI-powered workflows in Azure Logic Apps that interact with Entra ID, automate tasks, and adapt dynamically using agentic tools and OpenAI models. Advanced KQL Queries for Logic Apps in Application Insights: A Practical Guide Post by Dieter Gobeyn Boost Logic App performance with advanced KQL queries in Application Insights—spot bottlenecks, analyze slow actions, and optimize workflows without upgrading your hosting plan. How to Build an AI Agent with Azure Logic Apps Post by Cameron McKay Learn how to build your first AI Agent in Azure Logic Apps using Agent Loop—connect to OpenAI, design smart prompts, and automate tasks like weather reporting with low-code workflows. You Can Now Initialize All Your Variables In One Single Action Post by Luis Rigueira You can now initialize multiple variables in Logic Apps with a single action—making your workflows cleaner, faster, and easier to manage. It is a Friday Fact, brought to you by Luis Rigueira! Integration Insights Podcast: The Future of Integration Video by Sagar Sharma and Jochen Toelen In this two-part episode of the Integration Insights podcast, Sagar, Joechen and Kent dive into how integration is evolving in a cloud-first world. From BizTalk migrations to hybrid deployments with Azure Arc, they share practical insights and best practices to future-proof your integration strategy. A must-listen! You can watch part 2 here. Event Grid vs Service Bus vs Event Hubs vs Storage Queues: Choosing the Right Messaging Backbone in Azure Post by Prashant Singh Confused by Azure’s messaging options? This guide breaks down Event Grid, Service Bus, Event Hubs, and Storage Queues—helping you choose the right tool for real-time events, telemetry, enterprise workflows, or lightweight tasks. IntelliSense in Logic Apps Just Got Smarter – Matching Brackets in the Expression Editor! Post by Sandro Pereira Logic Apps just got a lot friendlier—bracket matching in the expression editor now highlights pairs as you type, making it easier to write and debug complex expressions.A Friday Fact from Sandro Pereira. How to Build Resilient Integrations for Mission-Critical Systems Post by Lilan Sameera Learn how to build resilient integrations for mission-critical systems using Logic Apps, Service Bus, and Event Hub—ensuring reliable data delivery, smart retries, and clean outputs even under pressure.
Expose REST APIs as MCP servers with Azure API Management and API Center (now in preview)
As AI-powered agents and large language models (LLMs) become central to modern application experiences, developers and enterprises need seamless, secure ways to connect these models to real-world data and capabilities. Today, we’re excited to introduce two powerful preview capabilities in the Azure API Management Platform: Expose REST APIs in Azure API Management as remote Model Context Protocol (MCP) servers Discover and manage MCP servers using API Center as a centralized enterprise registry Together, these updates help customers securely operationalize APIs for AI workloads and improve how APIs are managed and shared across organizations. Unlocking the value of AI through secure API integration While LLMs are incredibly capable, they are stateless and isolated unless connected to external tools and systems. Model Context Protocol (MCP) is an open standard designed to bridge this gap by allowing agents to invoke tools—such as APIs—via a standardized, JSON-RPC-based interface. With this release, Azure empowers you to operationalize your APIs for AI integration—securely, observably, and at scale. 1. Expose REST APIs as MCP servers with Azure API Management An MCP server exposes selected API operations to AI clients over JSON-RPC via HTTP or Server-Sent Events (SSE). These operations, referred to as “tools,” can be invoked by AI agents through natural language prompts. With this new capability, you can expose your existing REST APIs in Azure API Management as MCP servers—without rebuilding or rehosting them. Addressing common challenges Before this capability, customers faced several challenges when implementing MCP support: Duplicating development efforts: Building MCP servers from scratch often led to unnecessary work when existing REST APIs already provided much of the needed functionality. Security concerns: Server trust: Malicious servers could impersonate trusted ones. Credential management: Self-hosted MCP implementations often had to manage sensitive credentials like OAuth tokens. Registry and discovery: Without a centralized registry, discovering and managing MCP tools was manual and fragmented, making it hard to scale securely across teams. API Management now addresses these concerns by serving as a managed, policy-enforced hosting surface for MCP tools—offering centralized control, observability, and security. Benefits of using Azure API Management with MCP By exposing MCP servers through Azure API Management, customers gain: Centralized governance for API access, authentication, and usage policies Secure connectivity using OAuth 2.0 and subscription keys Granular control over which API operations are exposed to AI agents as tools Built-in observability through APIM’s monitoring and diagnostics features How it works MCP servers: In your API Management instance navigate to MCP servers Choose an API: + Create a new MCP Server and select the REST API you wish to expose. Configure the MCP Server: Select the API operations you want to expose as tools. These can be all or a subset of your API’s methods. Test and Integrate: Use tools like MCP Inspector or Visual Studio Code (in agent mode) to connect, test, and invoke the tools from your AI host. Getting started and availability This feature is now in public preview and being gradually rolled out to early access customers. To use the MCP server capability in Azure API Management: Prerequisites Your APIM instance must be on a SKUv1 tier: Premium, Standard, or Basic Your service must be enrolled in the AI Gateway early update group (activation may take up to 2 hours) Use the Azure Portal with feature flag: ➤ Append ?Microsoft_Azure_ApiManagement=mcp to your portal URL to access the MCP server configuration experience Note: Support for SKUv2 and broader availability will follow in upcoming updates. Full setup instructions and test guidance can be found via aka.ms/apimdocs/exportmcp. 2. Centralized MCP registry and discovery with Azure API Center As enterprises adopt MCP servers at scale, the need for a centralized, governed registry becomes critical. Azure API Center now provides this capability—serving as a single, enterprise-grade system of record for managing MCP endpoints. With API Center, teams can: Maintain a comprehensive inventory of MCP servers. Track version history, ownership, and metadata. Enforce governance policies across environments. Simplify compliance and reduce operational overhead. API Center also addresses enterprise-grade security by allowing administrators to define who can discover, access, and consume specific MCP servers—ensuring only authorized users can interact with sensitive tools. To support developer adoption, API Center includes: Semantic search and a modern discovery UI. Easy filtering based on capabilities, metadata, and usage context. Tight integration with Copilot Studio and GitHub Copilot, enabling developers to use MCP tools directly within their coding workflows. These capabilities reduce duplication, streamline workflows, and help teams securely scale MCP usage across the organization. Getting started This feature is now in preview and accessible to customers: https://aka.ms/apicenter/docs/mcp AI Gateway Lab | MCP Registry 3. What’s next These new previews are just the beginning. We're already working on: Azure API Management (APIM) Passthrough MCP server support We’re enabling APIM to act as a transparent proxy between your APIs and AI agents—no custom server logic needed. This will simplify onboarding and reduce operational overhead. Azure API Center (APIC) Deeper integration with Copilot Studio and VS Code Today, developers must perform manual steps to surface API Center data in Copilot workflows. We’re working to make this experience more visual and seamless, allowing developers to discover and consume MCP servers directly from familiar tools like VS Code and Copilot Studio. For questions or feedback, reach out to your Microsoft account team or visit: Azure API Management documentation Azure API Center documentation — The Azure API Management & API Center TeamsAnnouncement: Azure Logic Apps (Standard) Automated Testing Public Preview
We are excited to announce the public preview of the Azure Logic Apps (Standard) Automated Testing Framework! This new framework is designed to simplify and enhance the testing process for your Logic Apps workflows, ensuring that your integrations are robust, reliable, and ready for production. Starting with version 5.58.8, the Azure Logic Apps (Standard) extension for Visual Studio Code provides the capability to create unit test from a workflow run or a workflow saved definition, that can be edited and executed locally. Learn more about this feature in the April session for Logic App Live: Learn more Create unit tests from Standard workflow definitions in Azure Logic Apps with Visual Studio Code (Preview) Create unit tests from Standard workflow runs in Azure Logic Apps with Visual Studio Code (Preview) Sample Unit Tests (GitHub)
Using Logic Apps (Consumption)? Tell us what’s keeping you there
We’re inviting Logic Apps Consumption customers to share feedback on what’s influencing their decision to stay on Consumption and what might be holding them back from exploring Logic Apps Standard. Your input will help shape future improvements.Announcing General Availability: Azure Logic Apps Standard Automated Test Framework
We’re excited to announce the General Availability (GA) of the Azure Logic Apps Standard Automated Test Framework - a major step forward in enabling developers to build, test, and maintain enterprise-grade workflows with confidence and agility. Automated testing has become a cornerstone of modern development practices, and Logic Apps Standard now offers a robust framework to help you create unit tests for both workflow definitions and workflow runs directly within Visual Studio Code. This framework empowers teams to validate logic, simulate external dependencies, and ensure workflows behave as expected—before they’re deployed to production. Since the public preview, we’ve listened to your feedback and continued to enhance the framework. With GA, we’re introducing several key improvements that make testing even more powerful and flexible. What’s New in GA Support for More Mocked Actions You can now mock a broader range of built-in and managed connector actions, making it easier to isolate your workflow logic from external systems. With this release we unlocked support to mock actions for the following actions, unavailable during public preview: Call workflow in this logic app Execute inline code (JavaScript, C#, PowerShell Call Functions (Azure functions, local functions) XML Operations (transform, parse with schema) Liquid Operations (JSON to JSON, JSON to text, XML to JSON, XML to text) Data Mapper operations This enhancement allows for more comprehensive and reliable unit tests, providing more control to your workflow tests, especially in complex integration scenarios. Access to Workflow Settings for Assertions The framework now allows you to access and assert against workflow settings, such as parameters and app setting values. This means you can validate not just the behavior of your workflow, but also the environment in which it runs—ensuring logic consistency across different environments. Inline Script Actions Support Inline Code actions are now fully supported in test scenarios. JavaScript actions are now executed as part of the test workflow execution, since they are part of workflow logic. This improvement allows you to validate the logic of those scripts at part of your workflow scenarios. We are working on bringing similar support for C# and PowerShell scripts. Learn More To get started with the Azure Logic Apps Standard Automated Test Framework, check out the following Microsoft Learn articles: Create unit tests for workflow definitions in Visual Studio Code Create unit tests for workflow runs in Visual Studio Code Logic Apps Standard Automated Test SDK. Let us know what you think and stay tuned for more enhancements coming soon!Announcing General Availability: Azure Logic Apps Standard Custom Code with .NET 8
We’re excited to announce the General Availability (GA) of Custom Code support in Azure Logic Apps Standard with .NET 8. This release marks a significant step forward in enabling developers to build more powerful, flexible, and maintainable integration workflows using familiar .NET tools and practices. With this capability, developers can now embed custom .NET 8 code directly within their Logic Apps Standard workflows. This unlocks advanced logic scenarios, promotes code reuse, and allows seamless integration with existing .NET libraries and services—making it easier than ever to build enterprise-grade solutions on Azure. What’s New in GA This GA release introduces several key enhancements that improve the development experience and expand the capabilities of custom code in Logic Apps: Bring Your Own Packages Developers can now include and manage their own NuGet packages within custom code projects without having to resolve conflicts with the dependencies used by the language worker host. The update includes the ability to load the assembly dependencies of the custom code project into a separate Assembly context allowing you to bring any NET8 compatible dependent assembly versions that your project need. There are only three exceptions to this rule: Microsoft.Extensions.Logging.Abstractions Microsoft.Extensions.DependencyInjection.Abstractions Microsoft.Azure.Functions.Extensions.Workflows.Abstractions Dependency Injection Native Support Custom code now supports native Dependency Injection (DI), enabling better separation of concerns and more testable, maintainable code. This aligns with modern .NET development patterns and simplifies service management within your custom logic. To enable Dependency Injection, developers will need to provide a StartupConfiguration class, defining the list of dependencies: public class StartupConfiguration : IConfigureStartup { /// <summary> /// Configures services for the Azure Functions application. /// </summary> /// <param name="services">The service collection to configure.</param> public void Configure(IServiceCollection services) { // Register the routing service with dependency injection services.AddSingleton<IRoutingService, OrderRoutingService>(); services.AddSingleton<IDiscountService, DiscountService>(); } } You will also need to initialize those register those services during your custom code class constructor: public class MySampleFunction { private readonly ILogger<MySampleFunction> logger; private readonly IRoutingService routingService; private readonly IDiscountService discountService; public MySampleFunction(ILoggerFactory loggerFactory, IRoutingService routingService, IDiscountService discountService) { this.logger = loggerFactory.CreateLogger<MySampleFunction>(); this.routingService = routingService; this.discountService = discountService; } // your function logic here } Improved Authoring Experience The development experience has been significantly enhanced with improved tooling and templates. Whether you're using Visual Studio or Visual Studio Code, you’ll benefit from streamlined scaffolding, local debugging, and deployment workflows that make building and managing custom code faster and more intuitive. The following user experience improvements were added: Local functions metadata are kept between VS Code sessions, so you don't receive validation errors when editing workflows that depend on the local functions. Projects are also built when designer starts, so you don't have to manually update references. New context menu gestures, allowing you to create new local functions or build your functions project directly from the explorer area Unified debugging experience, making it easer for you to debug. We have now a single task for debugging custom code and logic apps, which makes starting a new debug session as easy as pressing F5. Learn More To get started with custom code in Azure Logic Apps Standard, visit the official Microsoft Learn documentation: Create and run custom code in Azure Logic Apps Standard You can also find example code for Dependency injection wsilveiranz/CustomCode-Dependency-InjectionLogic Apps Aviators Newsletter - June 25
In this issue: Ace Aviator of the Month News from our product group News from our community Ace Aviator of the Month April’s Ace Aviator: Andrew Wilson What's your role and title? What are your responsibilities? I am the Chief Consultancy Officer at Black Marble, a multi-award-winning software company with a big focus on the Microsoft stack. I work with a talented team of consultants to help our customers get the most out of Azure. My role is all about enabling organisations to modernise, integrate, and optimise their systems, always with an eye on DevOps best practices. I’m involved across most of the software development lifecycle, but my focus tends to lean toward consultations, gathering requirements, and architecting solutions that solve real-world problems. I work across a range of areas including application modernisation, BizTalk to Azure Integration Services (AIS) migrations, system integrations, and cloud optimisation. Over time, I've developed a strong focus on Azure, especially around AIS. In short, I help bridge the gap between technical possibilities and business needs, making sure the solutions we design are both practical and future-ready. Can you give us some insights into your day-to-day activities and what a typical day in your role looks like? No two days are quite the same which keeps things interesting! I usually kick things off with a quick plan for the day (and a bit of reshuffling for the week ahead) to make sure we’re focused on what matters most for both customers and the team. My time is a mix of customer-facing work, sales conversations with new prospects, and supporting existing clients, whether that’s through solution design, quick fixes, or hands-on consultancy. I’m often reviewing or writing proposals and architectures, and jumping in to support the team on delivery when needed. There’s always some active learning in the mix too, reading, experimenting, or spinning up quick ideas to explore better ways of doing things. We don’t work in silos at Black Marble, so I’ll often jump in where I can add value, whether or not I’m directly on the project. It’s a real team effort, and that collaboration is a big part of what makes the role so rewarding. What motivates and inspires you to be an active member of the Aviators/Microsoft community? I’ve always enjoyed the challenge of bringing systems and applications together, there’s something really satisfying about seeing everything click into place and knowing it’s driving real business value What makes the Aviators and wider Microsoft community special is that everyone shares that same excitement. It’s a group of people who genuinely care about solving problems, pushing technology forward, and learning from one another. Being part of that kind of community is motivating in itself, we’re all collaborating, sharing ideas, and helping shape a better, more connected future. It’s hard not to be inspired when you’re surrounded by people who are just as passionate about the work as you are. Looking back, what advice do you wish you had been given earlier that you'd now share with those looking to get into STEM/technology? Stay curious, always ask “why,” and don’t be afraid to get things wrong, because you will, and that’s how you learn. Some of the best breakthroughs come after a few missteps (and maybe a bit of head-scratching). It’s easy to look around and feel like others have it all figured out, don’t let that discourage you. Everyone’s journey is different, and what looks effortless on the outside often has a lot of trial and error behind it. One of the best things about STEM is its diversity, there are so many different roles, paths, and people in this space. Whether you’re hands-on with code, designing systems, or solving data challenges, there’s a place for you. It’s not a one-size-fits-all, and that’s what makes it exciting. Most importantly, share what you learn. Even if something’s been “done,” your take on it might be exactly what someone else needs to see to help them get started. And yes, imposter syndrome is real, but don’t let it silence you. You belong here just as much as anyone else. What has helped you grow professionally? A big part of my growth has come from simply committing to continuous learning, whether that’s diving into new tech, attending conferences like Integrate, or being part of user groups where ideas (and challenges) get shared openly. I’ve also learned to say yes to opportunities, even when they’ve felt a bit daunting at first. Pushing through the unknown, especially with the support of a great team and community, has led to some of my most rewarding experiences. And finally, I try to approach everything with the mindset that I’m someone others can count on. That sense of responsibility has helped me stay focused, accountable, and constantly improving. If you had a magic wand that could create a feature in Logic Apps, what would it be and why? Wow, what an exciting question! If I had a magic wand, the first thing I’d add is having the option to throw exceptions that can be caught by try-catch scope blocks, this would bring much-needed clarity and flexibility to error handling. It’s a feature that would really help build more resilient and maintainable solutions. Then, the ability to break or continue loops, sometimes you need that fine-tuned control to keep your workflows running smoothly without extra workarounds. And lastly, full GA support for unit and integration testing, because testing is the backbone of reliable software, and having that baked in would save so much time and stress down the line. News from our product group Logic Apps Live May 2025 Missed Logic Apps Live in May? You can watch it here. We focused on the Logic Apps big announcements from Microsoft Build 2025. There are a lot of great things to check! Announcing agent loop: Build AI Agents in Azure Logic Apps The era of intelligent business processes has arrived! Today, we are excited to announce agent loop, a groundbreaking new capability in Azure Logic Apps to build AI agents into your enterprise workflows. With agent loop, you can embed advanced AI decision-making directly into your processes – enabling your apps and automation to not just follow predefined steps, but to reason, adapt, and act autonomously towards goals. Agent Loop Demos We announced the public preview of agent loop at Build 2025. Agent Loop is a new feature in Logic Apps to build AI Agents for use cases that span across industry domains and patterns. In this article, share with you use cases implemented in Logic Apps using agent loop and other features. Announcement: Azure Logic Apps Document Indexer in Azure Cosmos DB We’re excited to announce the public preview of Azure Logic Apps as a document indexer for Azure Cosmos DB!00 With this release, you can now use Logic Apps connectors and templates to ingest documents directly into Cosmos DB’s vector store—powering AI workloads like Retrieval-Augmented Generation (RAG) with ease. Announcement: Logic Apps connectors in Azure AI Search for Integrated Vectorization We’re excited to announce that Azure Logic Apps connectors are now supported within AI Search as data sources for ingestion into Azure AI Search vector stores. This unlocks the ability to ingest unstructured documents from a variety of systems—including SharePoint, Amazon S3, Dropbox and many more —into your vector index using a low-code experience. Announcement: Power your Agents in Azure AI Foundry Agent Service with Azure Logic Apps We’re excited to announce the Public Preview of two major integrations that bring the power of Azure Logic Apps to AI Agents in Foundry – Logic Apps as Tools and AI Agent Service Connector. Learn more on our announcement post! Codeful Workflows: A New Authoring Model for Logic Apps Standard Codeful Workflows expand the authoring and execution models of a Logic Apps Standard, offering developers the ability to implement, test and run workflows using an imperative programming model both locally and in the cloud. Announcing the General Availability of the Azure Logic Apps Rules Engine we are announcing the General Availability of our Azure Logic Apps Rules Engine. A deterministic rules engine runtime based on the RETE algorithm that allows in-memory execution, prioritization, and reevaluation of business rules in Azure Logic Apps. Integration Environment Update – Unified experience to create and manage alerts We’re excited to announce the next milestone in our journey to simplify monitoring across Azure Integration Services. As a follow-up to our earlier preview release on unified monitoring and dashboards, we’re now making it easier than ever to configure alerts for your integration applications. Automate Invoice data extraction with Logic Apps and Document Intelligence This blog post demonstrates how you can use Azure Logic Apps, the new Analyze Document Details action, and Azure OpenAI to automatically convert invoice images into structured data and store them in Azure Cosmos DB. Log Ingestion to Azure Log Analytics Workspace with Logic App Standard Discover how to send logs to Azure Log Analytics Workspace using Logic App Standard for VNet integration. Learn about shared key authentication and HTTP action configuration for seamless log ingestion. Generating Webhook Action Callback URL with Primary or secondary Access Key Learn how to manage Webhook action callback URLs in Azure Logic Apps when regenerating access keys. Discover how to use the accessKeyType property to ensure seamless workflow execution and maintain security. Announcing the Public Preview of the Applications feature in Azure API management Discover the new Applications feature in Azure API Management, enabling OAuth-based access to APIs and products. Streamline secure API access with built-in OAuth 2.0 application-based authorization. GA: Inbound private endpoint for Standard v2 tier of Azure API Management Today, we are excited to announce the general availability of inbound private endpoint for Azure API management Standard v2 tier. Securely connect clients in your private network to the API Management gateway using Azure Private Link. Announcing the open Public Preview of the Premium v2 tier of Azure API Management Announcing the public preview of Azure API Management Premium v2 tier. Experience superior capacity, highest entity limits, and unlimited calls with enhanced security and networking flexibility. Announcing Federated Logging in Azure API Management Announcing federated logging in Azure API Management. Gain centralized monitoring for platform teams and autonomy for API teams, streamlining API management with robust security and operational visibility. Introducing Workspace Gateway Metrics and Autoscale in Azure API Management Introducing workspace gateway metrics and autoscale in Azure API Management. Efficiently monitor and scale your gateway infrastructure with real-time insights and automated scaling for enhanced reliability and cost efficiency. Introducing Model Logging, Import from AI Foundry, and extended model support in AI Gateway Introducing workspace gateway metrics and autoscale in Azure API Management. Efficiently monitor and scale your gateway infrastructure with real-time insights and automated scaling for enhanced reliability and cost efficiency. Expose REST APIs as MCP servers with Azure API Management and API Center (now in preview) Discover how to expose REST APIs as MCP servers with Azure API Management and API Center, now in preview. Enhance AI integration with secure, observable, and scalable API operations. Now in Public Preview: System events for data-plane in API Management gateway Announcing the public preview of new data-plane system events in Azure Event Grid for the Azure API Management managed gateway. Gain near-real-time visibility into critical operations, automate responses, and prevent disruptions. News from our community Agentic AI – A Potential Black Swan Moment in System Integration Video by Ahmed Bayoumy Discover how Agentic Logic Apps are revolutionizing system integration with AI-driven workflows. Learn how this innovative approach transforms business processes by understanding goals, deciding actions, and using predefined tools for smart orchestration. Microsoft Build: Behind the Scenes with Agent Loop Workflow A New Phase in AI Evolution Video by Ahmed Bayoumy Explore how Agent Loop brings “human in the loop” control to enterprise workflows, on this video by Ahmed, sharing insights directly from Microsoft Build 2025, in a chat with Kent Weare and Divya Swarnkar. Microsoft Build 2025: Azure Logic Apps is Now Your AI Agent Superpower! Post by Sagar Sharma Discover how Azure Logic Apps is transforming AI agent development with new capabilities unveiled at Microsoft Build 2025. Learn about Agent Loop, AI Foundry integration, Document Indexer, and more for intelligent, adaptive workflows. Everyone is talking about AI Agents — Here’s how to actually build one that works Post by Mateusz Partyka Learn how to build effective AI agents with practical strategies and insights. Discover tips on choosing the right tech stack, prototyping fast, managing model costs, and prompt engineering for optimal results. Agent Loop | Azure Logic Apps Just Got Smarter Post by Andrew Wilson Discover Agent Loop in Azure Logic Apps – now in preview - a revolutionary AI-powered integration feature. Enhance workflows with advanced decision-making, context retention, and adaptive actions for smarter automation. Step-by-Step Guide to Azure Logic Apps Agent Loop Post by Stephen W. Thomas Dive into the step-by-step guide for creating AI Agents with Azure Logic Apps Agent Loop – now in preview. Learn to leverage 1300+ connectors, set up OpenAI models, and build intelligent workflows with no-code integration. You can also follow Stephen’s video tutorial Confessions of a Control Freak: How I Learned to Love Low Code (with Logic Apps) Post by Peter Mugisha Discover how a self-confessed control freak learned to embrace low-code development with Azure Logic Apps. From skepticism to advocacy, explore the journey of efficient integration and streamlined workflows. Logic Apps Standard vs. Large Files: Common Hurdles and How to Beat Them Post by Şahin Özdemir Learn how to overcome common hurdles when handling large files in Logic Apps Standard. Discover strategies for scaling, offloading memory-intensive operations, and optimizing performance for efficient integration. There is a new-new Data Mapper for Logic App Standard Post by Sandro Pereira Discover the new Data Mapper for Logic App Standard, now in public preview. Enjoy a modern BizTalk-style mapper with code-first, schema-aware experience, supporting XSLT 3.0, XSD, and JSON schemas for efficient data mapping! A Friday Fact from Sandro Pereira. The name of When a HTTP request is received trigger affects the workflow URL Post by Sandro Pereira Discover how the name of the "When a HTTP request is received" trigger affects the workflow URL in Azure Logic Apps. Learn best practices to avoid integration issues and ensure consistent endpoint paths. Changing APIM Operations Doesn’t Update their PathTemplate Post by Luis Rigueira Learn how to handle PathTemplate issues in Azure Logic Apps Standard when switching APIM operations. Ensure correct endpoint paths to avoid misleading results and streamline your workflow. It is a Friday Fact, brought to you by Luis Rigueira!Codeful Workflows: A New Authoring Model for Logic Apps Standard
📝 This blog introduce early concepts of a pre-release functionality and is subject to change. Azure Logic Apps Standard offers you a powerful cloud orchestration engine, enabling you to build and run automated workflows that effortlessly integrate resources from various services, systems, apps, and data sources. Whether you're looking to streamline processes across a complex enterprise or simply reduce the need for extensive coding, this platform provides a solution that's both efficient and flexible. For those of you who require more control over workflow designs or want to leverage your expertise in frameworks like .NET and the Durable Tasks framework, Logic Apps Standard now introduces an exciting new feature: Codeful Workflows. With Codeful Workflows, you can define workflows using an imperative programming style, blending the flexibility of coding with the simplicity and operational strengths of Logic Apps. This means you can structure your workflows the way that makes sense to you while still tapping into the rich ecosystem of connectors and tools built into Logic Apps. What Are Codeful Workflows? Codeful Workflows expand the authoring and execution models of a Logic Apps Standard, offering developers the ability to implement, test and run workflows using an imperative programming model both locally and in the cloud. Built on frameworks like .NET and the Durable Tasks framework, Codeful Workflows allow you to structure workflows in code while seamlessly integrating with Logic Apps Standard rich connector ecosystem, and leverage its operational capabilities. The core elements of a Logic App workflow—triggers, actions and connections —are translated into durable task concepts within this codeful model: Triggers are implemented as Client Functions that invoke durable orchestrations, which contain the body of the workflow, blending logic implemented by the language primitives, with connections actions for external connectivity. Connector actions are presented as Activity Functions. The Logic Apps Connector ecosystem is exposed to you via an SDK, bringing discoverability and rich support for intelisense when creating action inputs, invoking actions or reusing action outputs in later steps. The SDK vastly simplifies the execution of those connectors, by wrapping them internally on a Activity Function, so you don’t need to create new activities for each connector action you want to invoke. Connections, which manages the connectivitiy between actions and end systems, remains unchanged, allowing you to setup once and share connections between multiple orchestrations and logic apps declarative workflows. Connector actions uses a reference to a connection, providing flexibility between local and cloud configurations. Using those building blocks, you can create workflows using familiar programming paradigms, while still benefiting from the easy configuration and operational feature of Logic Apps Standard. If you are an existing Logic Apps Standard customer, your codeful and visual workflows can coexist within the same application, bridging the gap between pro-code and low-code approaches. With those two execution models working hand in hand on the same application, Logic Apps Standard becomes a comprehensive orchestration tool that caters to all developer personas, from integration specialists to enterprise teams, with no cliffs on their experience. Creating Codeful Workflows Designing codeful workflows begins with creating a new Logic Apps project within Visual Studio Code, configured for .NET and the Durable Tasks framework. From triggers to actions, developers gain full flexibility to define their workflows programmatically. Implementing Triggers Triggers are the entry points of workflows, and in Codeful Workflows, they are defined as Client Functions. For example, an HTTP trigger can start a workflow when a request is received: [FunctionName("HelloTrigger")] public static async Task<HttpResponseMessage> HttpStart( [HttpTrigger(AuthorizationLevel.Anonymous, "get", "post")] HttpRequestMessage req, [DurableClient] IDurableOrchestrationClient starter, ILogger log) { var requestContent = await req.Content.ReadAsStringAsync(); var workflowInput = new HTTPHelloInput { Greeting = $"Hello from Codeful workflows. You said '{requestContent}'" }; log.LogInformation("Workflow Input = '{workflowInput}'.", JsonSerializer.Serialize(workflowInput)); string instanceId = await starter.StartNewAsync("HelloOrchestrator", workflowInput); log.LogInformation("Started orchestration with ID = '{instanceId}'.", instanceId); return await starter.WaitForCompletionOrCreateCheckStatusResponseAsync(req, instanceId); } Using Connector Actions Both Managed and Service Provider Actions are available to be used within your orchestrations. They are organized in the SDK by type making it easy to find the right connector to use. Once you identify the action to use, you can use the rich intelisense interface to generate inputs and call the action directly in your orchestration code. Deployment and Operations Deploying Logic Apps Standard that uses both codeful and codeless workflows follows the same practices already available in Logic Apps Standard. Operational insights, such as endpoint visibility and execution monitoring, are provided within the Azure Portal, ensuring parity with the functionality available for codeless workflows. This cohesive deployment model allows organizations to maximize their resources and cater to diverse development needs, whether they require quick prototyping via low-code tools or robust, scalable solutions through pro-code implementations. Codeful Workflows and Intelligent Agents You can take advantage of codeful workflows and Logic Apps Standard Agent Loop to create new intelligent applications that embed advanced AI decision-making directly into your processes – enabling your apps and automation to not just follow predefined steps, but to reason, adapt, and act autonomously towards goals. See this demo where we share two approaches to implement agent loops – combining codeful and codeless workflows, where you can reuse existing workflows as tools, and writing agent loop actions directly with code: Looking for feedback on Codeful Workflows We are looking for early feedback on this feature. If you are interested in participating on a private preview, please use the form below to register your interest and we will contact you to share the instructions. https://aka.ms/lacodeful/privatepreview/form
