logic apps
389 TopicsMoving the Logic Apps Designer Forward
Today, we're excited to announce a major redesign of the Azure Logic Apps designer experience, now entering Public Preview for Standard workflows. While these improvements are currently Standard-only, our vision is to quickly extend them across all Logic Apps surfaces and SKUs. ⚠️ Important: As this is a Public Preview release, we recommend using these features for development and testing workflows rather than production workloads. We're actively stabilizing the experience based on your feedback. This Is Just the Beginning This is not us declaring victory and moving on. This is Phase I of a multi-phase journey, and I'm committed to sharing our progress through regular blog posts as we continue iterating. More importantly, we want to hear from you. Your feedback drives these improvements, and it will continue to shape what comes next. This redesign comes from listening to you—our customers—watching how you actually work, and adapting the designer to better fit your workflows. We've seen the pain points, heard the frustrations, and we're addressing them systematically. Our Roadmap: Three Phases Phase I: Perfecting the Development Loop (What we're releasing today) We're focused on making it cleaner and faster to edit your workflow, test it, and see the results. The development loop should feel effortless, not cumbersome. Phase II: Reimagining the Canvas Next, we'll rethink how the canvas works—introducing new shortcuts and workflows that make modifications easier and more intuitive. Phase III: Unified Experiences Across All Surfaces We'll ensure VS Code, Consumption, and Standard all deliver similarly powerful flows, regardless of where you're working. Beyond these phases, we have several standalone improvements planned: a better search experience, streamlined connection creation and management, and removing unnecessary overhead when creating new workflows. We're also tackling fundamental questions that shouldn't be barriers: What do stateful and stateless mean? Why can't you switch between them? Why do you have to decide upfront if something is an agent? You shouldn't. We're working toward making these decisions dynamic—something you can change directly in the designer as you build, not rigid choices you're locked into at creation time. We want to make it easier to add agentic capabilities to any workflow, whenever you need them. What's New in Phase I Let me walk you through what we're shipping at Ignite. Faster Onboarding: Get to Building Sooner We're removing friction from the very beginning. When you create a new workflow, you'll get to the designer before having to choose stateful, stateless, or agentic. Eventually, we want to eliminate that upfront choice entirely—making it a decision you can defer until after your workflow is created. This one still needs a bit more work, but it's coming soon. One View to Rule Them All We've removed the side panel. Workflows now exist in a single, unified view with all the tooling you need. No more context switching. You can easily hop between run history, code view, or visual editor, and change your settings inline—all without leaving your workflow. Draft Mode: Auto-Save Without the Risk Here's one of our biggest changes: draft mode with auto-save. We know the best practice is to edit locally in VS Code, store workflows in GitHub, and deploy properly to keep editing separate from production. But we also know that's not always possible or practical for everyone. It sucks to get your workflow into the perfect state, then lose everything if something goes wrong before you hit save. Now your workflow auto-saves every 10 seconds in draft mode. If you refresh the window, you're right back where you were—but your changes aren't live in production. There's now a separate Publish action that promotes your draft to production. This means you can work, test your workflow against the draft using the designer tools, verify everything works, and then publish to production—even when editing directly on the resource. Another benefit: draft saves won't restart your app. Your app keeps running. Restarts only happen when you publish. Smarter, Faster Search We've reorganized how browsing works—no more getting dropped into an endless list of connectors. You now get proper guidance as you explore and can search directly for what you need. Even better, we're moving search to the backend in the coming weeks, which will eliminate the need to download information about thousands of connectors upfront and deliver instant results. Our goal: no search should ever feel slow. Document Your Workflows with Notes You can now add sticky notes anywhere in your workflow. Drop a post-it note, add markdown (yes, even YouTube videos), and document your logic right on the canvas. We have plans to improve this with node anchoring and better stability features, but for now, you can visualize and explain your workflows more clearly than ever. Unified Monitoring and Run History Making the development loop smoother means keeping everything in one place. Your run history now lives on the same page as your designer. Switch between runs without waiting for full blade reloads. We've also added the ability to view both draft and published runs—a powerful feature that lets you test and validate your changes before they go live. We know there's a balance between developer and operator personas. Developers need quick iteration and testing capabilities, while operators need reliable monitoring and production visibility. This unified view serves both: developers can test draft runs and iterate quickly, while the clear separation between draft and published runs ensures operators maintain full visibility into what's actually running in production. New Timeline View for Better Debugging We experimented with a timeline concept in Agentic Apps to explain handoff—Logic Apps' first foray into cyclic graphs. But it was confusing and didn't work well with other Logic App types. We've refined it. On the left-hand side, you'll now see a hierarchical view of every action your Logic App ran, in execution order. This makes navigation and debugging dramatically easier when you're trying to understand exactly what happened during a run. What's Next This is Phase I. We're shipping these improvements, but we're not stopping here. As we move into Phase II and beyond, I'll continue sharing updates through blog posts like this one. How to Share Your Feedback We're actively listening and want to hear from you: Use the feedback button in the Azure Portal designer Join the discussion in GitHub/Community Forum – https://github.com/Azure/LogicAppsUX Comment below with your thoughts and suggestions Your input directly shapes our roadmap and priorities. Keep the feedback coming. It's what drives these changes, and it's what will shape the future of Azure Logic Apps. Let's build something great together.2.1KViews5likes4CommentsWrite Logic Apps in C#: introducing the Logic Apps Standard SDK
The workflow you always wished you could write in code If you build on Logic Apps Standard, you already know the deal: the runtime is excellent at the unglamorous parts of integration - connecting to systems, retrying, scaling, keeping run history you can actually debug. What you sometimes wanted was a different front door. You're a .NET developer. You live in C#, source control, and pull requests. And for a long time, authoring a workflow meant leaving all of that behind for a visual designer and a JSON file. That's the gap the new Logic Apps Standard SDK closes. It lets you define Logic Apps Standard workflows in code - strongly typed, IntelliSense-guided C# - without giving up a single thing the runtime already does for you. What is the Logic Apps Standard SDK? The Logic Apps Standard SDK (Microsoft.Azure.Workflows.Sdk) is a NuGet package that gives you a fluent, code-first way to build workflow definitions in C#. Instead of dragging actions onto a canvas, you compose a workflow with method chaining: a trigger, then the actions that follow it, all the way to a response. Worth saying clearly, because people ask: this is a new way to define workflows - not a new runtime. The workflows you write with the SDK compile down to the same definitions and run on the same Logic Apps Standard runtime you use today. Same connectors. Same hosting. Same rich run history and monitoring. You're changing the authoring experience, not the engine underneath it. Why this matters for developers When your workflow lives in C#, it behaves like the rest of your code. A few things fall out of that almost for free: Type safety and IntelliSense - connector operations, triggers, and outputs are discoverable as you type, and the compiler catches mistakes before you run anything. Real source control and reviews - workflows diff like code, get reviewed in pull requests, and version alongside the services they orchestrate. Familiar tooling - refactor, debug with F5, and lean on the .NET ecosystem you already know. Extensibility on your terms — Compose your workflow declaratively with the fluent builder, then drop into plain imperative C# wherever a step needs logic that might be too complex to implement declaratively - loops, branching, a call into your own library, all encapsulated in a step of your workflow - without leaving the file or the language. And it isn't limited to one style of work. The SDK covers both enterprise integration workflows - the connect-systems-and-move-data scenarios Logic Apps is known for - and agentic workflows, where a conversational or autonomous AI agent drives the steps. Both are first-class in the same SDK, built from the same building blocks. There's one more angle worth calling out, because it's becoming hard to ignore: coding agents are simply better at writing imperative code than declarative JSON. And the reason is the same set of guardrails that helps you. Strong typing and a compilation step mean the code an agent produces is syntactically correct out of the gate — the type system and the compiler do the checking, so you don't have to. Layer unit tests on top and you've covered north of 90% of what matters; what's left is integration testing. Getting an LLM to the same level of accuracy against declarative JSON means building dedicated tooling to stand in for everything the compiler gives you for free. With code-first workflows, those guardrails are just there — which makes this a natural fit for an agent-assisted way of building. Getting started Everything here lives in the Logic Apps extension for VS Code. You'll want the Logic Apps Standard VS Code extension version 5.961.10 or later, which includes all the components you need to create code first workflows. Beyond that, the prerequisites are the ones you'd expect - VS Code with the Logic Apps extension, an Azure subscription you can create resources in, and a working comfort with C# and .NET. From a clean start, you're a handful of steps from a running workflow: Create the workspace — launch the Logic Apps extension and choose Create new Logic Apps workspace. Pick a folder, name the workspace and project, and when prompted for the workflow type, choose Logic Apps codeful - that's the code-first option that uses the SDK. Pick a workflow kind - name your first workflow and choose how it runs: Stateful, Autonomous agents (Preview), or Conversational agents (Preview). The agent options are where the agentic scenarios live. Enable connectors - when prompted, select Use connectors from Azure, choose your subscription and resource group, and pick Connection Keys for authentication. Managed identity is still in development, so connection keys are the way in for now. Find your way around - the project opens with Program.cs, which builds and starts the host, plus a workflow file (like workflow1.cs) where your trigger and actions are defined. The SDK compiles those definitions and runs them on the Logic Apps runtime. Run it - press F5 (or right-click Program.cs and pick Overview). The runtime starts locally and an overview page opens where you can fire triggers, watch run history, and inspect inputs and outputs. That last part is worth dwelling on: run history for SDK workflows uses the same rich visual view as designer-built ones. You author in code, but you monitor and troubleshoot exactly as you always have. A look at the capabilities Connectors and triggers Every workflow starts with a trigger and runs a series of actions. The SDK exposes both through two entry points - WorkflowTriggers and WorkflowActions - each split into BuiltIn and Managed. Built-in triggers and actions run directly in the runtime: HTTP request, recurrence, and the conversational agent trigger; actions like Compose, HTTP, Response, and custom code. Managed connectors give you the full Logic Apps connector catalog - Service Bus, SharePoint, SQL, and hundreds more - typed and ready to call. The managed surface is generated from the same connector definitions the designer uses, so the operations you know are right there: // Built-in trigger var trigger = WorkflowTriggers.BuiltIn.CreateHttpTrigger(); // Managed connector action — full catalog, strongly typed var getItems = WorkflowActions.Managed .Sharepointonline("sharepoint") .GetItems( dataset: () => "https://contoso.sharepoint.com", table: () => "orders-list-id") .WithName("GetOrders"); The fluent API streamlines the definition This is where it comes together. You compose a workflow by chaining operations with .Then(...). The shape of your code mirrors the shape of your workflow - read it top to bottom and you read the execution path. trigger .Then(validateOrder) .Then(getOrders) .Then(sendResponse); Control flow is part of the same fluent model. Built-in structures like Condition (if/else) and ForEach - along with Switch, Until, Scope, and Terminate - are just actions you chain in, each taking a small factory for the branch or loop body: var checkTotal = WorkflowActions.BuiltIn.Control.Condition( expression: () => order.Total > 1000, trueBranch: () => requireApproval, falseBranch: () => autoApprove ).WithName("CheckOrderValue"); And ForEach takes the collection to iterate and a factory that builds the body for each item: var processLines = WorkflowActions.BuiltIn.Control.ForEach( items: () => order.LineItems, actions: (item) => new WorkflowBuiltInActions() .Compose(inputs: () => $"Line: {item}").WithName("HandleLine") ).WithName("ProcessLineItems"); Need parallel branches that fan back in? The same Then pattern handles branching and join - no JSON wiring, no run-after blocks to hand-edit. Extending workflows with custom code Some logic doesn't belong in a connector or an expression - it's just code. The CustomCode action lets you drop a real C# method into the middle of a workflow. It receives a WorkflowContext, so you can read the trigger payload or any earlier action's results and return a strongly typed value the next step can use: var enrich = WorkflowActions.BuiltIn.CustomCode<string>(async (context) => { var trigger = await context.GetTriggerResults(); var order = await context.GetActionResults("GetOrders"); // your logic, your libraries, your types return "enriched"; }).WithName("EnrichOrder"); That's the escape hatch that keeps you in flow: when a step needs custom transformation, validation, or a call into your own libraries, you write a method instead of bending an expression to do something it was never meant to. Handling failures: try/catch with run-after Real workflows have to deal with things going wrong, and the SDK gives you the same try/catch shape Logic Apps has always had - expressed in code. The .Then(...) overload takes a FlowStatus[] run-after condition, so a handler runs only when the step before it ends in a status you name. Wrap the risky work in a Scope (your try), then chain a handler that runs after it Failed or TimedOut (your catch): var tryProcess = WorkflowActions.BuiltIn.Control.Scope(() => callPaymentApi.Then(saveOrder) ).WithName("ProcessPayment"); var handleFailure = WorkflowActions.BuiltIn .Compose(inputs: () => "Payment failed — compensating") .WithName("HandleFailure"); trigger .Then(tryProcess) .Then(handleFailure, runAfter: new[] { FlowStatus.Failed, FlowStatus.TimedOut }); The status set is the whole vocabulary: Succeeded, Failed, Skipped, and TimedOut. Combine them however a step needs - a cleanup action that should run no matter what can list every status; a finally is just the union. The same idea scales to fan-in. When several parallel branches converge, the per-predecessor RunAfter overload lets the join wait on each branch independently - so you can require some to succeed and tolerate others failing: leftChain .Join(rightChain) .Then(merge, runAfter: new[] { new RunAfter(leftChain, FlowStatus.Succeeded), new RunAfter(rightChain, FlowStatus.Succeeded), }); Putting it together Here's a small but complete shape - an HTTP-triggered order workflow that validates input, branches on order value, loops over line items, runs custom code, and replies. The core steps live in a Scope so a single failure handler can catch anything that goes wrong, and a clean reply only runs when the work succeeds. Notice it's all one readable chain: namespace LogicApps { using Microsoft.Azure.Workflows.Sdk; using Microsoft.Azure.Workflows.Sdk.Connectors.Msnweather; using System.Net; public class OrderWorkflow : IWorkflowProvider { /// <summary> /// Gets the HTTP request/response workflow definition. /// </summary> public FlowDefinition[] GetWorkflows() { // --- Trigger ---------------------------------------------------- var trigger = WorkflowTriggers.BuiltIn.CreateHttpTrigger(); // --- Managed connector action (full catalog, strongly typed) ---- // Reused verbatim from the confirmed stateful1.cs pattern. var getWeather = WorkflowActions.Managed.Msnweather("msnweather").CurrentWeather( location: () => "98058", units: () => unitsInput.Imperial).WithName("GetWeather"); // --- Custom code: real C# in the middle of the workflow --------- var enrich = WorkflowActions.BuiltIn.CustomCode<string>(async (context) => { var triggerResults = await context.GetTriggerResults(); var weather = await context.GetActionResults("GetWeather"); // your logic, your libraries, your types return "enriched"; }).WithName("EnrichOrder"); // --- ForEach over a collection (control flow via .Control) ------- var processLines = WorkflowActions.BuiltIn.Control.ForEach( items: () => trigger.TriggerOutput.Body["lineItems"], actions: (item) => WorkflowActions.BuiltIn .Compose(inputs: () => $"Line: {item}").WithName("HandleLine") ).WithName("ProcessLineItems"); // --- Condition (if/else) (control flow via .Control) ------------ var checkTotal = WorkflowActions.BuiltIn.Control.Condition( expression: () => true, trueBranch: () => processLines, falseBranch: () => WorkflowActions.BuiltIn .Compose(inputs: () => "Auto-approved").WithName("AutoApprove") ).WithName("CheckOrderValue"); // --- Scope groups the core steps so one handler catches failures - var processOrder = WorkflowActions.BuiltIn.Control.Scope(() => checkTotal .Then(getWeather) .Then(enrich) ).WithName("ProcessOrder"); // --- Responses -------------------------------------------------- var ok = WorkflowActions.BuiltIn.Response( responseBody: () => "Order processed").WithName("Reply"); var failed = WorkflowActions.BuiltIn.Response( statusCode: () => HttpStatusCode.InternalServerError, responseBody: () => "Order failed").WithName("ReplyFailed"); // --- Assemble --------------------------------------------------- // Happy path runs after the Scope Succeeded; the handler runs after // Failed or TimedOut. trigger .Then(processOrder) .Then(ok, runAfter: new[] { FlowStatus.Succeeded }) .Then(failed, runAfter: new[] { FlowStatus.Failed, FlowStatus.TimedOut }); return new[] { WorkflowFactory.CreateStatefulWorkflow("OrderWorkflow", trigger) }; } } } That last stretch is the best-practice shape in miniature: the happy-path Reply runs only after the Scope Succeeded, while a separate handler catches Failed or TimedOut and returns a 500 - no exception plumbing, just run-after conditions. You implement IWorkflowProvider, hand your trigger graph to WorkflowFactory as a stateful, stateless, or agent workflow, and the host registers it. Run it with F5 and the Logic Apps runtime starts locally - same as any Standard project. Before you build: preview realities I'd rather you go in clear-eyed. While the SDK is in public preview, keep these in mind: Service Provider connectors aren't supported yet - that connector type is coming in a future release. Dynamic schemas aren't supported - support is planned. Custom code supports callback methods only - inline lambdas aren't available in this version. Define and name actions before referencing them - name an action before using it as a dependency elsewhere. Managed identity authentication is in development - use connection keys for connectors in the meantime. Try it, and tell us what you think If you've ever wanted your workflows to live where the rest of your code lives - in C#, in source control, in your pull requests - this is for you. Install the Logic Apps extension for VS Code, create a Logic Apps codeful project, and build your first workflow in code. This is a preview, which means your feedback genuinely shapes where it goes - which capabilities come next, where the rough edges are. Bring issues, feature requests and feedback to our GitHub page. I read it. Let's make code-first workflows something you actually want to use.400Views2likes0CommentsWhat's new in Azure API Management at Microsoft Build 2026
For more than a decade, Azure API Management has helped organizations secure, govern, and operate APIs at enterprise scale. As organizations build more AI-powered applications, APIs are increasingly part of a broader architecture that includes AI models, agents, MCP tools, and agent-to-agent interactions. These new patterns increase the need for consistent governance, discovery, security, and observability across the full application ecosystem. Azure API Management already provides AI gateway capabilities that help organizations govern and observe AI workloads. At Build 2026, we're continuing to expand those capabilities and introducing new updates that help organizations manage the growing ecosystem of APIs, models, agents, MCP tools, and AI-powered interactions. General Availability: Azure API Center expands discovery and governance for APIs and AI assets As organizations build more AI-powered applications, APIs are no longer the only reusable enterprise asset. Agents, MCP tools, prompts, skills, and AI services are rapidly becoming building blocks that developers need to discover, evaluate, and reuse. To support this shift, Azure API Center now Azure API Center now supports agent registration, agent assessment, and Git-based synchronization | Microsoft Community Hub, helping organizations create a centralized catalog for APIs and AI assets. Developers can register agents directly into API Center, making them discoverable alongside APIs and other enterprise assets. Agent definitions can be synchronized automatically from Git repositories, ensuring catalog entries remain aligned with source-controlled implementations and evolving codebases. To help organizations establish trust and quality standards, API Center now also provides automated agent assessment using an LLM-as-a-Judge framework. Agents can be evaluated for safety, reliability, and behavioral completeness before being published to the enterprise catalog. We're also announcing the general availability of the Azure API Center data plane MCP server. As organizations adopt MCP-based tooling and AI agents at scale, developers need a simpler way to discover and connect to the growing ecosystem of enterprise MCP servers, tools, APIs, agents, and AI assets. The Azure API Center data plane MCP server acts as a unified enterprise discovery endpoint, enabling agents and developer tools to access registered MCP servers, tools, APIs, agents, and AI assets through a single MCP connection. This allows organizations to provide centralized access to enterprise capabilities, simplify discovery across growing catalogs, and automatically make newly registered MCP servers and tools available without requiring individual client reconfiguration. Together with agent registration, assessment, and Git synchronization, the Azure API Center data plane MCP server helps organizations create a centralized source of truth for APIs, agents, MCP tools, and AI assets improving discoverability, governance, and reuse across the enterprise General Availability: Agent-to-Agent APIs and content safety controls Agentic systems introduce new governance challenges. As agents begin coordinating work on behalf of applications and users, agent-to-agent communication is becoming an increasingly important architectural pattern. Historically, these interactions have often existed outside traditional API governance boundaries, creating operational blind spots and fragmented governance models. Azure API Management now supports JSON-RPC-based Agent-to-Agent (A2A) APIs, enabling organizations to manage agent interactions alongside REST APIs, GraphQL APIs, MCP tools, and AI model APIs using the same API management platform they already rely on today. We're also extending content safety capabilities to MCP tools and A2A interactions. Organizations can now centrally apply safety controls across model invocations, tool execution, and agent communication patterns through a unified governance layer. Rather than introducing separate governance platforms for agents, Azure API Management enables organizations to extend familiar API governance principles to emerging agent ecosystems. Public Preview: Unified Model API for multi-model AI applications Most organizations are quickly discovering that AI is becoming a multi-model world. Applications increasingly combine models from Microsoft, OpenAI, Anthropic, Google, and other providers based on performance, cost, latency, regional requirements, or workload-specific needs. This creates complexity for developers and platform teams alike. Different providers expose different APIs. SDKs vary. Governance becomes fragmented. Switching providers often requires application changes. To simplify multi-model architectures, we're introducing the Unified Model API in public preview. The Unified Model API allows organizations to standardize on a single client-facing API format while Azure API Management transparently handles provider-specific transformations behind the scenes. Developers can continue using familiar APIs and SDKs while platform teams gain the flexibility to route traffic across multiple providers, implement failover strategies, and evolve model choices over time. By abstracting provider-specific differences behind a unified API layer, organizations can build more portable, resilient, and governable AI applications. General Availability: Expanded AI Gateway support for Anthropic and Vertex AI Azure API Management AI gateway capabilities already helps organizations govern and observe AI traffic across model providers. As multi-model architectures become increasingly common, organizations need consistent governance regardless of where those models are hosted. API Management now extends AI Gateway capabilities to Anthropic and Google Vertex AI models. Organizations can apply runtime governance, security controls, content safety policies, semantic caching, token controls, logging, tracing, and observability across a broader range of AI providers. This enables platform teams to apply consistent governance practices across multi-model environments without introducing separate management tools or operational processes for each provider. General Availability: Expanded token observability for AI workloads Understanding AI usage is becoming increasingly important as model providers introduce new token types beyond traditional prompt and completion tokens. Azure API Management now supports token metrics for all token types, including cached, reasoning, and thinking tokens, with metrics available through Application Insights. Organizations can collect token usage data across multiple providers and API formats, build more accurate cost dashboards, improve budget monitoring, and gain deeper visibility into evolving model behaviors. As AI workloads continue to grow, expanded token observability helps organizations better manage costs, optimize usage, and strengthen governance across AI applications. General Availability: Enterprise platform enhancements Alongside our AI-focused investments, we're continuing to expand the core platform capabilities organizations rely on to operate API programs at scale. Azure API Management Premium v2 now supports multiple custom domains, allowing organizations to expose APIs, developer portals, and management endpoints under multiple branded experiences while maintaining centralized governance. Azure API Management Premium v2 and Standard v2 now support wildcard custom hostnames, significantly reducing certificate and hostname management overhead for growing API estates. We're also expanding workspace support to the built-in gateway. Organizations can now adopt team-based governance and delegated API management models across additional deployment options while benefiting from built-in gateway capabilities such as multi-region deployments, custom hostnames, and Private Link connectivity. Together, these enhancements make it easier for organizations to scale up API programs while maintaining operational simplicity. Looking ahead APIs remain the foundation of modern applications. But increasingly, they are no longer the only assets developers interact with. Models, agents, MCP tools, and agent-to-agent interactions are becoming important components of enterprise application architectures. The governance challenge is no longer limited to APIs alone. With these Build announcements, Azure API Management and Azure API Center continue to expand the governance foundation organizations rely onhelping teams discover, secure, govern, and observe APIs, models, agents, MCP tools, and AI interactions through a unified platform experience. As organizations build the next generation of AI-powered applications, we're committed to providing the governance, security, visibility, and operational controls required to run those systems with confidence at enterprise scale.237Views0likes0CommentsWhat's new in Azure Logic Apps at Microsoft Build 2026
Automation is entering a new era Automation has traditionally been powerful, but not always accessible. Building production-grade automations often requires specialized expertise in workflows, integrations, APIs, infrastructure, identity, security, networking, and operations. Organizations could build sophisticated solutions, but doing so typically requires dedicated development or integration teams AI is changing that equation. Across every organization, more people want to automate work. Developers want to build AI-powered applications faster. Startup teams want to move from idea to production without assembling complex infrastructure. Operations, security, and business teams want to leverage AI to automate repetitive processes and accelerate decision making. Expectations have changed as well. Builders increasingly expect natural language experiences, AI assistance, integrated knowledge, and faster paths from idea to execution. At the same time, organizations still need the governance, security, reliability, compliance, and operational controls required to run automation in production. This creates a new opportunity: making enterprise-grade automation accessible to far more builders without sacrificing the foundations required to operate at scale. At Build 2026, we're introducing Azure Logic Apps Automation along with several new Azure Logic Apps capabilities that help organizations build, connect, and operationalize AI-powered automation on Azure. Public Preview: Azure Logic Apps Automation Azure Logic Apps Automation is a new Logic Apps SKU designed to make enterprise-grade automation dramatically easier to build. Built on the same Azure platform organizations trust today, Logic Apps Automation provides a managed environment where workflows, AI agents, enterprise connectivity, knowledge services, and model access are available out of the box. A built-in AI assistant helps users move from intent to implementation using natural language. Developers can generate workflows, configure actions, create expressions, and build automations faster while maintaining full control over the final implementation. Logic Apps Automation also brings AI agents directly into the automation experience. Developers can build and use Microsoft Foundry agents alongside traditional workflow actions, enabling business processes that combine deterministic execution with AI-driven reasoning. Whether you're a startup building AI-native applications, an enterprise modernizing internal processes, or a developer looking to accelerate automation projects, Logic Apps Automation provides a simpler path from idea to production. General Availability: Azure Logic Apps MCP Server As AI agents become increasingly important participants in enterprise applications, organizations need a straightforward way to connect those agents to existing business processes. The Azure Logic Apps MCP Server is now generally available and enables developers to expose existing Logic Apps workflows as MCP-compatible tools that agents can discover and invoke directly. This allows organizations to reuse years of existing automation investments without building custom APIs or integration layers. Workflows that already connect enterprise systems, business applications, and operational processes can now become AI-callable capabilities in minutes. Public Preview: Invoke Microsoft Foundry Agents directly from Logic Apps Organizations increasingly build agents in Microsoft Foundry. With new Foundry integration capabilities, developers can now invoke Foundry agents directly from Logic Apps workflows. This enables business processes that combine enterprise systems, APIs, human approvals, schedules, events, and AI-driven reasoning within a single automation experience. Workflows can trigger agents, agents can provide analysis or recommendations, and Logic Apps coordinates the broader business process around those outcomes. Public Preview: Knowledge as a Service One of the biggest challenges organizations face when building AI-powered applications is making enterprise knowledge accessible. Retrieval-augmented generation often requires ingestion pipelines, chunking strategies, embedding models, vector databases, and retrieval infrastructure before developers can begin building the experiences they actually care about. Knowledge as a Service simplifies this process. Developers can upload documents directly into Logic Apps workflows, automatically ingest and process content, generate embeddings, and use retrieval as a built-in workflow capability. Instead of building and operating knowledge infrastructure, teams can focus on creating grounded AI experiences and intelligent automations that leverage organizational knowledge. Public Preview: Codeful Workflows with the Logic Apps Standard SDK Different developers prefer different ways of building software. Some teams prefer visual workflow design. Others want the flexibility and familiarity of code-first development. Codeful Workflows introduces a new code-first development experience for Azure Logic Apps Standard. Built on the Logic Apps Standard SDK, Codeful Workflows enable developers to create workflows directly in code using familiar .NET development patterns while continuing to benefit from Logic Apps connectors, orchestration capabilities, and operational infrastructure. Developers can build, test, debug, and run workflows locally while leveraging existing development tools, source control practices, and AI-assisted coding experiences. This gives teams more flexibility in how they build automation while preserving the benefits of the Logic Apps platform. Public Preview: Migration Agent for Azure Logic Apps Modernization remains a top priority for many organizations as they evaluate legacy integration platforms and prepare for the next generation of cloud-native architectures. The new Migration Agent for Azure Logic Apps helps simplify that journey. Designed to assist organizations migrating from BizTalk Server and other third-party integration solutions, the Migration Agent provides intelligent assessments, migration guidance, compatibility analysis, and automated recommendations. By reducing the manual effort traditionally associated with migration projects, organizations can accelerate modernization initiatives while lowering risk and improving confidence throughout the migration process. Looking ahead The future of automation is not simply about adding AI to existing workflows. It's about making powerful automation accessible to more builders while preserving the governance, reliability, security, and operational controls organizations require. Azure Logic Apps has long provided the foundation for enterprise integration and business process automation. With Logic Apps Automation, Foundry agent integration, MCP support, Knowledge as a Service, Codeful Workflows, and AI-powered migration capabilities, we're continuing to expand what's possible while making it easier for organizations to move from idea to production. We're excited to see what developers, startups, enterprises, and builders of every kind create next.279Views0likes0CommentsMicrosoft BizTalk Server Product Lifecycle Update
For more than 25 years, Microsoft BizTalk Server has supported mission-critical integration workloads for organizations around the world. From business process automation and B2B messaging to connectivity across industries such as financial services, healthcare, manufacturing, and government, BizTalk Server has played a foundational role in enterprise integration strategies. To help customers plan confidently for the future, Microsoft is sharing an update to the BizTalk Server product lifecycle and long-term support timelines. BizTalk Server 2020 will be the final version of BizTalk Server. Guidance to support long-term planning for mission-critical workloads This announcement does not change existing support commitments. Customers can continue to rely on BizTalk Server for many years ahead, with a clear and predictable runway to plan modernization at a pace that aligns with their business and regulatory needs. Lifecycle Phase End Date What’s Included Mainstream Support April 11, 2028 Security + non-security updates and Customer Service & Support (CSS) support Extended Support April 9, 2030 CSS support, Security updates, and paid support for fixes (*) End of Support April 10, 2030 No further updates or support (*) Paid Extended Support will be available for BizTalk Server 2020 between April 2028 and April 2030 for customers requiring hotfixes for non-security updates. CSS will continue providing their typical support. BizTalk Server 2016 is already out of mainstream support, and we recommend those customers evaluate a direct modernization path to Azure Logic Apps. Continued Commitment to Enterprise Integration Microsoft remains fully committed to supporting mission-critical integration, including hybrid connectivity, future-ready orchestration, and B2B/EDI modernization. Azure Logic Apps, part of Azure Integration Services — which includes API Management, Service Bus, and Event Grid — delivers the comprehensive integration platform for the next decade of enterprise connectivity. Host Integration Server: Continued Support for Mainframe Workloads Host Integration Server (HIS) has long provided essential connectivity for organizations with mainframe and midrange systems. To ensure continued support for those workloads, Host Integration Server 2028 will ship as a standalone product with its own lifecycle, decoupled from BizTalk Server. This provides customers with more flexibility and a longer planning horizon. Recognizing Mainframe modernization customers might be looking to integrate with their mainframes from Azure, Microsoft provides Logic Apps connectors for mainframe and midrange systems, and we are keen on adding more connectors in this space. Let us know about your HIS plans, and if you require specific features for Mainframe and midranges integration from Logic Apps at: https://aka.ms/lamainframe Azure Logic Apps: The Successor to BizTalk Server Azure Logic Apps, part of Azure Integration Services, is the modern integration platform that carries forward what customers value in BizTalk while unlocking new innovation, scale, and intelligence. With 1,400+ out-of-box connectors supporting enterprise, SaaS, legacy, and mainframe systems, organizations can reuse existing BizTalk maps, schemas, rules, and custom code to accelerate modernization while preserving prior investments including B2B/EDI and healthcare transactions. Logic Apps delivers elastic scalability, enterprise-grade security and compliance, and built-in cost efficiency without the overhead of managing infrastructure. Modern DevOps tooling, Visual Studio Code support, and infrastructure-as-code (ARM/Bicep) ensure consistent, governed deployments with end-to-end observability using Azure Monitor and OpenTelemetry. Modernizing Logic Apps also unlocks agentic business processes, enabling AI-driven routing, predictive insights, and context-aware automation without redesigning existing integrations. Logic Apps adapts to business and regulatory needs, running fully managed in Azure, hybrid via Arc-enabled Kubernetes, or evaluated for air-gapped environments. Throughout this lifecycle transition, customers can continue to rely on the BizTalk investments they have made while moving toward a platform ready for the next decade of integration and AI-driven business. Charting Your Modernization Path Microsoft remains fully committed to supporting customers through this transition. We recognize that BizTalk systems support highly customized and mission-critical business operations. Modernization requires time, planning, and precision. We hope to provide: Proven guidance and recommended design patterns A growing ecosystem of tooling supporting artifact reuse Unified Support engagements for deep migration assistance A strong partner ecosystem specializing in BizTalk modernization Potential incentive programs to help facilitate migration for eligible customers (details forthcoming) Customers can take a phased approach — starting with new workloads while incrementally modernizing existing BizTalk deployments. We’re Here to Help Migration resources are available today: Overview: https://aka.ms/btmig Best practices: https://aka.ms/BizTalkServerMigrationResources Video series: https://aka.ms/btmigvideo Feature request survey: https://aka.ms/logicappsneeds Reactor session: Modernizing BizTalk: Accelerate Migration with Logic Apps - YouTube Migration Agent (Complete refactoring from BizTalk to Logic Apps): Bringing all your Integration workloads to Logic Apps Standard | Microsoft Community Hub We encourage customers to engage their Microsoft accounts team early to assess readiness, identify modernization opportunities, and explore assistance programs. Your Modernization Journey Starts Now BizTalk Server has played a foundational role in enterprise integration success for more than two decades. As you plan ahead, Microsoft is here to partner with you every step of the way, ensuring operational continuity today while unlocking innovation tomorrow. To begin your transition, please contact your Microsoft account team or visit our migration hub. Thank you for your continued trust in Microsoft and BizTalk Server. We look forward to partnering closely with you as you plan the future of your integration platforms. Frequently Asked Questions Do I need to migrate now? No. BizTalk Server 2020 is fully supported through April 11, 2028, with paid Extended Support available through April 9, 2030, for non-security hotfixes. CSS will continue providing their typical support. You have a long and predictable runway to plan your transition. Will there be a new BizTalk Server version? No. BizTalk Server 2020 is the final version of the product. What happens after April 9, 2030? BizTalk Server will reach End of Support, and security updates or technical assistance will no longer be provided. Workloads will continue running but without Microsoft servicing. Is paid support available past 2028? Yes. Paid extended support will be available through April 2030 for BizTalk Server 2020 customers looking for non-security hotfixes. CSS will continue to provide the typical support. What is the end of sale date for BizTalk Server? We will announce an end of sale date for BizTalk Server on July 2026. What about BizTalk Server 2016 or earlier versions? Those versions are already out of mainstream support. We strongly encourage moving directly to Logic Apps rather than upgrading to BizTalk Server 2020. Will Host Integration Server continue? Yes. Host Integration Server (HIS) 2028 will be released as a standalone product with its own lifecycle and support commitments. Can I reuse BizTalk Server artifacts in Logic Apps? Yes. Most of BizTalk maps, schemas, rules, assemblies, and custom code can be reused with minimal effort using Microsoft and partner migration tooling. We welcome feature requests here: https://aka.ms/logicappsneeds Does modernization require moving fully to the cloud? No. Logic Apps supports hybrid deployments for scenarios requiring local processing or regulatory compliance, and fully disconnected environments are under evaluation. More information of the Hybrid deployment model here: https://aka.ms/lahybrid. Does modernization unlock AI capabilities? Yes. Logic Apps enables AI-driven automations through Agent Loop, improving routing, decisioning, and operational intelligence. Where do I get planning support? Your Microsoft account team can assist with assessment and planning. Migration resources are also linked in this announcement to help you get started. Microsoft Corporation6.2KViews3likes1CommentClean up idle and always-failing Azure Logic App Consumption
If you’ve inherited an Azure subscription that’s been collecting Logic Apps Consumption workflows for a couple of years, you already know the shape of the problem: dozens of TestLA, webhook-test-2, poc-for-jira-FINAL workflows in the portal, half of them still Enabled, half of them quietly failing every five minutes against a connection that was rotated last quarter. They’re cheap, but they’re not free — polling triggers keep firing, alert rules keep paging, abandoned Microsoft.Web/connections keep pinning permissions, and the portal’s workflow list keeps getting harder to read. Source + full docs: GitHub - dengyanbo/LA-CleanUp What it gives you Two color-coded tables — Idle (no runs in the last -IdleDays days; never-run workflows land here too) and AlwaysFailing (ran in the window, but not a single Succeeded ). An optional, timestamped CSV ( LogicAppCleanup-Candidates-<yyyyMMdd-HHmmss>.csv ) with a stable column set, easy to drop in a Teams channel or PR for owner review before you delete anything. A per-item y/N/q deletion loop — y deletes, N /Enter skips, q quits the loop without touching anything else. A final summary with scanned / idle / always-failing / deleted / skipped / failed counts. Server-side OData $filter on run history so the scan is fast even on a subscription with thousands of workflow runs in the window. Lazy State lookup (Enabled/Disabled) — only fetched for actual candidates, not for every healthy workflow. What it is not: it does not touch Logic Apps Standard ( Microsoft.Web/sites with kind=workflowapp ) — those store run history in storage tables and need a completely different tool (see LogicAppAdvancedTool). It also does not GC Microsoft.Web/connections , and it does not iterate subscriptions — one invocation, one subscription, deliberately. Quick start Prerequisites PowerShell 5.1+ (Windows PowerShell or PowerShell 7 — both fine). Azure CLI on PATH: https://aka.ms/azcli An interactive az login against the subscription that owns the Logic Apps. Logic App Contributor on the relevant RGs (or plain Contributor) is enough — you need list + delete on Microsoft.Logic/workflows , plus the ARM token your az login already grants. Get the script git clone https://github.com/dengyanbo/LA-CleanUp.git cd LA-CleanUp One-liner — defaults (90-day idle, 90-day failure window, current sub) .\Invoke-LogicAppCleanup.ps1 A typical run looks like this: [INFO] Active subscription: Contoso-Integration (1111-2222-...) [INFO] Signed in as : alice@contoso.com [INFO] Idle cutoff : runs older than 2026-02-20T03:08:00Z (>90 days) [INFO] Failure window : checking runs since 2026-02-20T03:08:00Z (last 90 days) [INFO] Listing Logic App (Consumption) workflows... [ OK ] Found 13 workflow(s). [ 1/13] order-processor (rg-integration) [ 2/13] webhook-test (MyTest) ... [ OK ] Scan complete. Idle: 9, AlwaysFailing: 1, Errors: 0 === Idle Logic Apps (no runs in last 90 days) === Name ResourceGroup Location State LastStatus LastRunTime ---- ------------- -------- ----- ---------- ----------- webhook-test MyTest australiaeast Enabled Never poc-for-jira rg-integration eastus Enabled Succeeded 2025-09-04T... ... === Always-Failing Logic Apps (no successful run in last 90 days) === Name ResourceGroup Location State LastStatus LastRunTime ---- ------------- -------- ----- ---------- ----------- nightly-export rg-integration eastus Enabled Failed 2026-05-20T... Export the 10 candidate(s) to CSV? (y/N): y [ OK ] CSV written: ...\LogicAppCleanup-Candidates-20260521-110800.csv Starting per-item deletion review. Answer y to delete, N (or Enter) to skip, q to quit. (1/10) Delete [Idle] webhook-test in MyTest ? (y/N/q): y [INFO] Deleting webhook-test ... [ OK ] Deleted: webhook-test (2/10) Delete [Idle] poc-for-jira in rg-integration ? (y/N/q): N Skipped. ... === Summary === Scanned : 13 Idle : 9 Always-failing : 1 Scan errors : 0 Deleted : 4 Skipped : 6 Delete failures : 0 That’s the whole workflow. The commands you’ll actually use 1. Scope to one resource group with a tighter idle threshold .\Invoke-LogicAppCleanup.ps1 -IdleDays 60 -ResourceGroup rg-integration 2. Only review always-failing apps (skip the idle pile) .\Invoke-LogicAppCleanup.ps1 -SkipIdle 3. Only review idle apps (skip always-failing) .\Invoke-LogicAppCleanup.ps1 -SkipAlwaysFailing 4. Incident-driven cleanup — tight window, focused RG .\Invoke-LogicAppCleanup.ps1 -IdleDays 30 -FailureWindowDays 7 ` -ResourceGroup rg-integration-prod This answers: “Within prod-integration, which workflows haven’t run in a month, and which have been failing all week?” 5. Dry-run (there is no -WhatIf ) The per-item y/N/q prompt is the safety model. To dry-run, just answer N to every prompt — or q at the first one. The CSV is still written before the deletion loop starts, so you walk away with the report and zero deletions. Parameters — cheat sheet Parameter Default Meaning -IdleDays 90 No runs in this many days ⇒ flagged Idle. Never-run workflows land here too. -FailureWindowDays 90 Ran in this window but no Succeeded ⇒ flagged AlwaysFailing. -ResourceGroup (none) Restrict the scan to a single RG. -SkipIdle switch Skip the Idle bucket entirely. -SkipAlwaysFailing switch Skip the AlwaysFailing bucket entirely. Why Invoke-RestMethod instead of az rest This is the gotcha I want every other Logic Apps scripter to know about, because it eats hours. The Logic Apps Management REST API is queried with OData — $top , $filter , the usual: GET /subscriptions/.../workflows/{wf}/runs ?api-version=2016-06-01 &$top=1 &$filter=startTime ge 2026-02-20T03:08:00Z and status eq 'Succeeded' On Windows PowerShell, az is a .cmd shim. The URL you pass to az rest --uri "..." is re-parsed by cmd.exe , and the & characters separating OData query parameters get interpreted as command separators. Symptoms range from '$filter' is not recognized as an internal or external command to silent wrong-page returns where the filter is just dropped and you get the most recent N runs instead. Quoting heroics — single quotes, double quotes, triple-escaped ^& — don’t fully solve it across PS 5.1 and PS 7. The fix is to skip az rest entirely. The script grabs an ARM token once with az account get-access-token , caches it on a script-scoped variable, refreshes it proactively at the 45-minute mark (ARM tokens last ~60), and calls Invoke-RestMethod directly: $tok = az account get-access-token --resource 'https://management.azure.com/' -o json | ConvertFrom-Json Invoke-RestMethod -Method Get -Uri $url ` -Headers @{ Authorization = "Bearer $($tok.accessToken)" } That bypasses cmd.exe entirely. Bonus: caching the token makes the script noticeably faster on subscriptions with many candidates, since we’re no longer shelling out to az for every REST call. Why $top=1 matters more than you’d think The script never pages run history. For each surviving workflow it asks two existence questions: ?api-version=2016-06-01&$top=1&$filter=startTime ge <cutoff> ?api-version=2016-06-01&$top=1&$filter=startTime ge <cutoff> and status eq 'Succeeded' If the first one returns zero rows ⇒ the workflow is Idle. Otherwise, if the second one returns zero rows ⇒ AlwaysFailing. Both queries are O(1) server-side because startTime is indexed and the response is capped at one row. Even on a chatty workflow with tens of thousands of runs in the window, the answer comes back in tens of milliseconds. This is also why the script can afford to be sequential per workflow — there’s no need for parallelism when each existence check is essentially free. Why “AlwaysFailing” is defined the way it is The bucket is “ran in the window, but not a single Succeeded run in the window” — not “all runs are Failed ”. That distinction matters: Workflows whose runs are Running , Waiting , or Cancelled but never Succeeded get classified as AlwaysFailing. That’s usually what you want — a workflow that has been “Waiting” for 30 days is just as broken as one that’s been failing for 30 days. Long-running workflows that legitimately haven’t completed yet look the same to the classifier. If you operate that kind of workflow, widen -FailureWindowDays so a slow but eventually-Succeeded run shows up in the window. The reported LastStatus column in the table is the status of the most recent run, so you can usually eyeball the difference between “failing” and “still running.” A field-tested rollout If you’re running this on a subscription you don’t fully own, this multi-pass rollout has worked well: Run with -SkipAlwaysFailing first. Idle workflows are the safe pile — if they haven’t done anything in 90+ days, deleting them rarely surprises anyone. Export the CSV. Don’t delete yet — answer q at the first delete prompt. Drop the CSV in a Teams channel or PR. Give owners a few days to object. Re-run and actually delete the ones nobody claimed. Then run with -SkipIdle for the AlwaysFailing bucket. These often have an owner who just hasn’t noticed the breakage — treat the first pass as a bug-bash list, not a delete list. Things to know before you run it Consumption only. Logic Apps Standard is out of scope — different model, different APIs, run history in storage tables. Use LogicAppAdvancedTool for those. No -Force , no -WhatIf . The per-item y/N/q prompt is the entire safety model. That’s deliberate — cleanup tools that take a -Force get used with -Force . One subscription per invocation. The script operates on whatever az account show returns. Use az account set --subscription <id> to switch deliberately. Microsoft.Web/connections are not deleted. API connections are typically shared; the script intentionally leaves them alone. GC them with a separate pass. Run history disappears with the workflow. Once you delete the Logic App, Azure removes its run history too. Export the CSV first if you want any record. Enabled vs. Disabled is reported, not enforced. A Disabled workflow can still be Idle. The script shows the state in the table so you can decide. Where to go next The GitHub repo has the full reference — parameter table, CSV schema, the “how it works” deep dive on lazy State fetch, bearer-token caching, server-side $filter , considerations and limitations, and the recommended rollout: 👉 https://github.com/dengyanbo/LA-CleanUp Issues and PRs welcome. A few directions on the roadmap: an optional disable-instead-of-delete mode for the first pass ( PATCH ...?api-version=2019-05-01 with properties.state = 'Disabled' ), a cross-subscription mode that iterates az account list with a confirmation per sub, and a companion API-connection GC script that uses Resource Graph to join connections against workflow definitions in one query.179Views0likes0CommentsRun Javascript code on Agent Loop
We have recently introduced support for Code interpreters inside of Azure Logic Apps Agent Loop, extending the support we had for Python. When partnered with a LLM, this allow builders to express their goals or intents via natural language and obtain executable results. These capabilities become powerful in the areas of data analysis, visualizations, validations and transformations. Our first language supported for code interpreter is JavaScript, with other languages following later. Historically, customers have had concerns about an LLM performing data analysis, calculations and transformations due to context window exhaustion which can lead to hallucinations. Code interpreters help in this regard as they can perform this analysis without filling up context windows and providing more reliable results. You can see the code interpreter with JavaScript in action in this video from Kent Weare. After watching the video, you can deep dive in the details. How it works When Agent Loop evaluates code generated by an AI agent (for example, through a code interpreter), we run it inside a V8 isolate using the isolated‑vm library. V8 is the JavaScript engine that powers Node.js and Chrome—it’s what actually executes JavaScript code. An isolate is a lightweight, independent environment within V8, with its own memory and execution context. Running code inside an isolate gives us strong separation from the host runtime. Each execution has its own memory (“heap”) and cannot directly access the host’s memory, file system, or network. This helps ensure that agent-generated code stays contained and doesn’t interfere with the rest of the system. This approach is not intended to be a full security sandbox, and we don’t treat it as safe for fully untrusted code. However, it provides meaningful defense-in-depth: Memory usage is limited per isolate, preventing a single execution from consuming all available resources Execution can be bounded with timeouts, allowing us to terminate long-running or infinite loops Failures are isolated, so crashes in agent-generated code won’t bring down the runtime process In practice, this is about reducing blast radius. By isolating execution and enforcing limits, we make sure that code—regardless of whether it’s generated by a user or an AI agent—cannot disrupt the engine that runs it. Use case: Expense Validations To help illustrate, this capability, let’s take an accounts payable example built in Logic Apps Standard. Zava uses a 3 rd party expense application to capture employee expenses. The 3rd party expense application will export transactions in CSV format. Zava has some very specific business validations that need to execute before the expenses can be processed by the ERP. To solve this problem, we will build an agentic business process in Logic Apps that includes our new JavaScript code interpreter. Our code interpreter will be able to ingest and parse our CSV file and then apply our business validations for us. The outcome is a report that identifies both valid and invalid transactions. Prior to uploading to the ERP (Dataverse), we will route our request to a human in the loop process for their oversight. This allows for additional control as unwinding in an ERP is always a tedious task. Below, is a picture of our solution. Within it we can see both deterministic steps before and after our Agent action. Within our agent action, we have tools that will help our agent address our company objectives. These tools include calling a batch API to upload valid expense records to Dataverse. Another tool that will take care of uploading invalid records to a different table, our human in the loop action to seek approval from our human stakeholder and a tool that will help us obtain business knowledge from SharePoint. You might be asking, ok where does the code interpreter come in? Within our Agent action, we will discover a toggle that allows you to enable it. The code interpreter gets invoked based upon instruction in the model. Here is a subset of the prompt from this workflow that describes how to invoke the code interpreter. For example: ### Step 2 -- Parse and Validate The expense CSV data is available from the Get_file_content action. Use code interpreter to parse ALL rows from the CSV. For each row, normalize: Category: title case - Amount: decimal number - SubmittedDate: ISO 8601 format (e.g. "2026-01-05T00:00:00Z") - ReceiptAttached: convert "Yes"/"No" to true/false Then apply the business rules from Step 1 to classify every record as VALID or INVALID. You won’t see the code interpreter modelled as a tool within our agent action, but we see the execution outcome within our run history. In the following screenshot we can see this illustrated. Within our agent action, we can see that we are on our 4 th turn and we have executed the code interpreter action. In the code window, we can see the code that was generated for our us. This is the result of the LLM working together with the code interpreter to generate and execute this code. Note: In this scenario, we are dynamically generating this code at runtime. This allows for ultimate flexibility if we have different source inputs and we are relying upon the LLM and code interpreter to adapt to these fluid inputs. If we were interested in a more deterministic approach we can also pass pre-written code into this action where it can also execute. This will result in less flexibility, but more deterministic behavior. Running JavaScript code in Logic Apps Consumption Agent Loop Logic Apps Consumption has a slightly different architecture to Logic Apps Standard. In Logic Apps Standard, we offer dedicated compute and storage for customers which provides workload isolation across customers. When it comes to Logic Apps Consumption, we provide a multi-tenant offering allowing customers to take advantage of a lower price point due to shared resource utilization. In order to allow customer isolation, customers need to have an integration account attached to their consumption workflow. This will allow the code interpreter to run in isolated compute thus avoiding any potential disruptions to other customers. You can provision an Integration Account by searching for Integration Accounts at the top of the Azure portal. You can select any of the SKUs available, including the Free SKU for non-production/non-SLA scenarios. With an Integration Account created, we can associate this Integration Account with our consumption logic app by clicking on Settings – Integration Account.704Views0likes0CommentsBulk-configure diagnostic settings on Azure Logic Apps Consumptions
Bulk-configure diagnostic settings on Azure Logic Apps — without clicking through the Portal LA-BulkDiag is a small, single-file PowerShell script that does the whole job in one guided run. It enumerates every Consumption Logic App in a resource group, shows you which ones already have settings, lets you pick a scope (every bare LA / every LA / a hand-picked subset), and creates the diagnostic setting on each. It auto-renames on collision so re-running is safe, and it ships with 129 Pester tests covering helpers, parameter binding, and end-to-end flows with a mocked az . Source + full docs: GitHub - dengyanbo/LA-BulkDiag: Bulk diagnostics configuration for Azure Logic Apps What it gives you A numbered, color-coded table of every Consumption LA in the RG and its current diagnostic-setting state (bare / has N / list failed). A single scope prompt — bare / all / pick / cancel — so the common cases are one keystroke. Selection grammar for the picker / -Selection : 1,3-5,8 , bare , all , none . Auto-rename on name collision ( la-diag → la-diag-1 → …) so the upsert behavior of Azure’s API never silently replaces an existing setting. Preflight verification of the destination workspace / storage account via az resource show before touching any Logic App. -WhatIf for a dry-run preview. Non-zero exit code if any LA failed, so it composes cleanly in CI. What it is not: it does not target Standard Logic Apps ( Microsoft.Web/sites with kind=workflowapp ) — those use a different API. It also doesn’t target Event Hub destinations. For everything else, see the “Scope and what this is NOT” section in the GitHub README. Quick start Prerequisites PowerShell 5.1+ (Windows PowerShell or PowerShell 7 — both fine). Azure CLI on PATH: https://aka.ms/installazurecliwindows An interactive az login against the subscription that owns the Logic Apps. Built-in Monitoring Contributor on the RG is enough. Get the script git clone https://github.com/dengyanbo/LA-BulkDiag.git cd LA-BulkDiag One-liner — fully interactive You don’t need to know the destination IDs up front; the script will ask: .\Set-LogicAppDiagnostics.ps1 -ResourceGroup my-rg -SettingName la-diag You’ll see something like: Sub: my-sub (00000000-...) User: alice@contoso.com Destination not provided on the command line. Configure interactively: (paste the full ARM resource ID; leave blank to skip a destination) Log Analytics workspace resource ID: /subscriptions/.../workspaces/my-ws Storage account resource ID: Inspecting 3 Logic App(s) ... Logic Apps in 'my-rg': [ 1] order-processor bare (no settings) [ 2] notification-sender has 1: corp-governance [ 3] data-loader bare (no settings) How do you want to apply 'la-diag'? 1) bare -- apply to every BARE LA (recommended) 2) all -- apply to EVERY LA (may fail Azure-side on non-bare ones) 3) pick -- go into the selective picker 0) cancel Choice [1]: 1 Applying to every BARE LA. ==> order-processor Creating ... OK (Created). ==> data-loader Creating ... OK (Created). ================ Summary ================ LogicApp FinalName Status -------- --------- ------ order-processor la-diag Created data-loader la-diag Created Selected: 2 Succeeded: 2 Renamed: 0 Failed: 0 Not selected: 1 That’s the whole workflow. The commands you’ll actually use Grab the destination IDs once: $wsId = az monitor log-analytics workspace show -g ws-rg -n my-ws --query id -o tsv $saId = az storage account show -g sa-rg -n mysa --query id -o tsv 1. Apply to every bare LA — fully automated .\Set-LogicAppDiagnostics.ps1 -ResourceGroup my-rg ` -WorkspaceId $wsId -SettingName la-diag -Selection bare -Selection bare skips both the scope prompt and the y/N confirm — perfect for CI. 2. Send to both a workspace and a storage account .\Set-LogicAppDiagnostics.ps1 -ResourceGroup my-rg ` -WorkspaceId $wsId -StorageAccountId $saId ` -SettingName la-diag -Selection all 3. Metrics only, storage-only .\Set-LogicAppDiagnostics.ps1 -ResourceGroup my-rg ` -StorageAccountId $saId -SettingName la-metrics ` -Preset metrics-only -Selection all Available presets: all (default) / logs-only / metrics-only / workflowruntime . 4. Specific Logic Apps by index — non-interactive After running once and seeing the numbered table, you can target them directly: .\Set-LogicAppDiagnostics.ps1 -ResourceGroup my-rg -WorkspaceId $wsId ` -SettingName la-diag -Selection '1,3-5,8' 5. Dry-run before committing .\Set-LogicAppDiagnostics.ps1 -ResourceGroup my-rg -WorkspaceId $wsId ` -SettingName la-diag -Selection all -WhatIf 6. Just inspect — list LAs + existing settings, change nothing .\Set-LogicAppDiagnostics.ps1 -ResourceGroup my-rg -WorkspaceId $wsId ` -SettingName whatever -Selection none 7. Run the tests .\unit_test\Run-Tests.ps1 Auto-installs Pester 5 to CurrentUser if missing. Expected: Passed=129 Failed=0 . Selection grammar — cheat sheet Input Meaning 1 , 3 , 7 single index (1-based, matches the table) 1,3,5 multiple indices 1-5 inclusive range 1,3-5,8 mixed bare all LAs with no existing settings (recommended) all every LA (may fail on already-configured ones) none (or empty / q / cancel ) exit without changes Why the auto-rename matters Azure’s diagnostic-settings API is PUT — calling create --name la-diag on a Logic App that already has a setting named la-diag silently replaces the existing one. That’s a footgun if a colleague already set something up by hand. LA-BulkDiag refuses to overwrite. Instead, when -SettingName is already in use on a given LA, it auto-appends -1 , -2 , … until it finds a free name, and reports the actual name in the summary’s FinalName column. If you genuinely want to replace an existing setting, delete it first: az monitor diagnostic-settings delete -n <existing-name> --resource <la-id> Where to go next The GitHub repo has the full reference — parameter table, exit codes, status-value glossary, troubleshooting matrix (RBAC, MFA, throttling, category/sink conflicts), known limitations, and the full test inventory: 👉 https://github.com/dengyanbo/LA-BulkDiag150Views0likes0CommentsAnnouncing the public preview of Oracle Database built-in connector for Azure Logic Apps Standard
Announcing the public preview of Oracle Database built-in connector for Azure Logic Apps Standard Run Oracle Database operations natively in your Logic Apps Standard workflows. Today we’re excited to announce the public preview of Oracle Database built-in connector for Azure Logic Apps (Standard). This connector brings first-class Oracle Database connectivity to single-tenant workflows by running in-process with the Logic Apps runtime, helping you build reliable, high-throughput integrations with Oracle-backed systems while keeping network traffic within your chosen network boundary. Why this matters? In-process execution: Operations execute within the Logic Apps Standard runtime for streamlined connectivity and lower latency. No on-premises data gateway (when your Logic App has network connectivity to Oracle): Simplify architecture and reduce operational overhead. Better fit for enterprise network topologies: Use VNET integration, private endpoints, and network controls consistent with your environment. Purpose-built Oracle capabilities: Get Oracle-focused actions including Execute stored procedure, a common gap for generic JDBC-based approaches. Designed for scale: Built-in connectors align with the direction of Logic Apps Standard for performance and operational consistency across workloads. On-premises integrations: With Hybrid Logic Apps, you can connect on-premises Oracle databases from on-premises-hosted Logic Apps. What can you do with the connector? The Oracle Database built-in connector currently supports the following actions: Get tables: Discover tables (and views, depending on permissions) available to your connection. Get rows: Read rows from a selected table with pagination support. Insert row: Insert a row into a selected table. Execute query: Run SQL statements (for example, select, update, delete) and return results when applicable. Execute stored procedure: Call stored procedures to encapsulate business logic and advanced operations. Connector details at a glance Logic Apps SKU: Standard (single-tenant). Execution model: Built-in (in-process) connector. Connectivity: No gateway required when your Logic App runtime can reach the Oracle endpoint (for example, via VNET integration). Oracle versions: Supports Oracle Database 11 and later (compatible with the managed driver). Authentication: Username and password. Triggers: The connector is actions-only in the current release. Getting started Ensure network connectivity from your Logic App Standard runtime to your Oracle Database endpoint (host and port), including any required DNS and firewall rules. Create a new Oracle Database connection in the Logic Apps designer. Provide connection parameters o Server address o Username o Password Choose a server address format that matches your environment: o Easy Connect (host/port/service name) for quick setup. o TNS descriptor for advanced connection configuration. Add an action (for example, Get rows or Execute stored procedure) and start building your workflow. Known limitations (current release) No triggers: The connector currently supports actions only. Update/Delete actions: Use Execute query or Execute stored procedure for update/delete scenarios. Connection validation: Some connection issues may surface at workflow runtime rather than during connection creation. Timeouts: Default query timeout is 30 seconds (configurable via app settings). The function host may impose an upper limit (commonly up to 10 minutes depending on configuration). Case sensitivity: Oracle identifiers can be case sensitive; ensure table/column names match your schema as defined. Troubleshooting and observability When issues occur, you’ll typically see failures surfaced through workflow run history and diagnostics. Oracle error details are returned as standard connector failures, and many common Oracle error conditions map to familiar HTTP status codes (for example, authentication failures, connectivity issues, and timeouts). 401 (authentication): Verify username/password, account lock status, and password expiry policies. 502 (connectivity): Verify host/port reachability, DNS resolution, firewall rules, and Oracle listener availability. 504 (timeout): Verify query complexity, indexes, and configured timeouts (query timeout and host timeout). 404 (object not found): Verify schema/table/view names and permissions; ensure correct casing. 429 (resource/session limits): Review Oracle session limits and workflow concurrency patterns. Get started today If you’re building new integrations with Oracle, or modernizing legacy workloads, try the Oracle Database built-in connector in your Logic Apps Standard workflows and let us know what you build. We’re especially interested in feedback on triggers, advanced authentication options, and additional Oracle operations you’d like to see next. Thank you for your continued feedback and partnership as we expand built-in connectivity across Azure Logic Apps. References: Connect to Oracle Database from Workflows - Azure Logic Apps | Microsoft LearnLogic Apps Newsletter - May 2026
In this issue: Ace Aviator of the Month News from our product group News from our community Ace Aviator of the Month May 2026's Ace Aviator: Yahya Ajwad What's your role and title? What are your responsibilities? I work as Chief Architect and AI Lead at Epical. My role is centered around technical leadership, architecture, and advisory mostly within cloud adoption and transformation programs. I help customers design and implement integration platforms. I also support customers in navigating the AI landscape, with a focus on how integration platforms impact AI readiness and how AI can be used to create value in the platforms we build. Internally at Epical, I lead our Microsoft and Azure cloud integration offering, as well as our CoreAI team and AI initiatives. Can you give us some insights into your day-to-day activities? One moment it is about how we can utilize AI to deliver things cheaper and faster without compromising security, governance and quality. Next, a customer contacts us with an undocumented BizTalk environment asking us what to do next (that's where the fun begins). Usually followed up by the question about how much does their future integration platform in Azure will cost down to the last cent (good luck answering that 😜 hint: the right answer is always: "less than BizTalk"). And hey, public cloud might not be good enough for their security, so thank God for private connectivity. I also spend time helping customers identify the best cloud integration strategies and patterns and for their business needs, choosing the right platforms and components for specific use cases, and ensuring that the platforms we design are as secure, scalable, maintainable, and cost-efficient as possible. Increasingly, this also includes sprinkling AI so bosses are happy (joking I'm a true AI believer myself). Internally, I support Epical with technical business development and help ensure that we stay relevant. What motivates and inspires you to be an active member of the Aviators/Microsoft community? I honestly believe that IT in general would never have been the same without communities and the willingness to share knowledge and support one another. The Logic Apps and Azure Integration community is especially unique because it is both practical and open. People share real experiences which makes it incredibly valuable when trying to solve real-world challenges. What motivates me is the opportunity to learn by sharing, receive feedback, and be part of a community where everyone contributes to each other’s growth. Between us, I'm here for the stickers ;) Looking back, what advice do you wish you had been given earlier? Be kind, stay curious and be helpful. Share what you know, even if it feels small or irrelevant. Those small insights often help others more than you think and that will definitely help you grow. Also, focus on learning the fundamentals. Tools and platforms change quickly, and what is popular today might not matter in a few weeks. Strong basics will always stay relevant. Keep learning and try new things all the time. What has helped you grow professionally? Being around kind, skilled, and generous people both in the community and at work who are willing to teach, challenge my thinking, and share their knowledge. Also, finding mentors who are open to mentor me, listen to all my questions even the silly ones, and who are willing to guide me and correct me when I’m hallucinating. If you had a magic wand that could create a feature in Logic Apps, what would it be? I don’t need to wish for one, you guys (Shout-out to Harold, Dyvia and the team) have already created it: Logic Apps Migration Assistant Agents. That stuff is definitely magic. News from our product group Network Connectivity Check APIs for Logic App Standard This post introduces built-in network troubleshooting APIs for Logic App Standard when integrated with a virtual network. Three endpoints—connectivityCheck, dnsCheck, and tcpPingCheck—let you validate end‑to‑end connectivity to services such as Azure SQL, Key Vault, Storage, Service Bus, and Event Hubs, perform DNS resolution, and test TCP reachability from the actual worker hosting your workflows. It covers supported provider types, credential options including Managed Identity and app settings, example payloads, and known limitations (e.g., SMB port 445 cannot be tested). Step-by-step guidance shows how to call the APIs via Azure API Playground or CLI to quickly isolate network issues. Service Bus SBMP Retirement: What BizTalk Server 2020 Customers Need to Know Azure Service Bus will retire the Service Bus Messaging Protocol (SBMP) on September 30, 2026, impacting BizTalk Server 2020 customers using the SB‑Messaging adapter. Microsoft has released a hotfix that adds Advanced Message Queuing Protocol (AMQP) support to the adapter for CU6 and CU7. With the hotfix, AMQP becomes the default transport while SBMP remains an opt‑in fallback; an updated hotfix based on the new Service Bus SDK is expected in June. Guidance includes migrating configurations to AMQP, installing and validating the hotfix in non‑production, and testing large message/file scenarios. The hotfix can be requested via support (KB5091375). Migrate Data Ingestion from Data Collector to Log Ingestion With the HTTP Data Collector API for Log Analytics deprecated and heading out of support in September 2026, this guide shows Logic Apps users how to move to the Log Ingestion API. It explains impacts—such as 403 errors for new Data Collector connections and missing data in newly created custom log tables—and provides a migration path using the HTTP action. Steps include creating a Data Collection Endpoint (DCE) and Data Collection Rule (DCR), deriving the full ingestion URL, mapping sample data to define schema, assigning the Monitoring Metrics Publisher role to the Logic App’s managed identity, and verifying success (HTTP 204). Introducing AI Skill Assessment in Azure API Center Azure API Center now includes automated AI skill assessment, providing governance and quality scoring for skills at scale using an “LLM‑as‑a‑judge” approach. The system evaluates outputs against defined criteria and ships with four default dimensions—Documentation Clarity, Help Completeness, Discoverability, and Safe Usage—each scored 1–5 with configurable thresholds. Developers get detailed reports showing pass/fail, per‑dimension scores, structural checks, and schema validation, helping them decide which skills are production‑ready. Platform administrators can extend or customize criteria to match organizational standards. The feature centralizes oversight and reduces manual review effort, improving confidence when adopting AI skills across integration solutions. Introducing the plugin marketplace for Azure API Center Azure API Center adds a plugin marketplace endpoint (public preview) that exposes a version‑controlled catalog of organizational AI plugins—such as MCP servers and skills—directly from your API Center data plane. Developers can discover and install plugins from familiar tools like Claude Code and GitHub Copilot CLI using simple marketplace commands. The endpoint inherits the API Center portal’s authentication model, ensuring governance and security while platform teams control publication. The article explains the problem it addresses, the marketplace.git URL format, quick start commands, and documentation to enable the feature—streamlining how teams curate, manage, and consume AI plugins in enterprise environments. News from our community Control the Initial State of Logic Apps Standard Workflows Post by Sandro Pereira This tip explains how to prevent Logic Apps Standard workflows from auto-starting after deployment, a risky default in production. Unlike Consumption, Standard doesn’t expose a state property in ARM. Instead, each workflow’s initial state is controlled via App Service application settings using the pattern “Workflows.<WorkflowName>.FlowState=Disabled.” The post shows how to define these keys in local.settings.json (or pipelines/Bicep), deploy with workflows disabled, and enable them when ready. It also notes acceptable values (Disabled/disabled) and clarifies that omitting the keys leaves workflows enabled by default—reducing unwanted executions and noisy alerts. 10 Azure Function App Limitations for Enterprise Integration Post by Tarun Garg The post outlines ten reasons Azure Function Apps may be a poor fit for enterprise integration workloads. Issues include cold-start latency, limited orchestration and state management, operational complexity at scale, and the need to hand-roll observability. It also highlights security and network isolation challenges, cost variability under heavy throughput, strong dependence on custom code, risks around versioning and breaking changes, and insufficient governance controls for integration use cases. The takeaway: Function Apps excel at granular compute, but integration programs often benefit from managed orchestration layers and patterns better aligned to enterprise requirements. Logic Apps Standard: how accidentally blocking access from Edge results in CORS errors Post by Şahin Özdemir Şahin Özdemir explains a troubleshooting case where Logic Apps Standard action inputs/outputs stopped loading in the Azure portal, appearing like a CORS issue. The root cause was a blocked “Local Network Access” permission in Microsoft Edge, not misconfigured CORS. The article advises checking Edge’s site permissions and re-enabling local network access before diving into CORS diagnostics. By validating browser settings first, engineers can avoid unnecessary changes to integration apps and resolve portal rendering failures quickly—saving time and reducing confusion when workflow views suddenly fail to load. Logic apps – Handling AND OR conditions Post by Anitha Eswaran Anitha Eswaran explains how to correctly implement combined AND/OR logic in Azure Logic Apps when the designer view becomes confusing. Using a real example—validating item numbers—she shows how to check for empty values or specific suffixes (W/WN) and when to terminate processing. The article demonstrates building expressions to explicitly control evaluation order and outcomes, avoiding unintended behavior from default AND logic. Practical screenshots and expression snippets help readers structure conditions, handle arrays from trigger data, and create maintainable workflows that reflect real business rules. Why Enterprises Are Migrating from Logic Apps (Consumption) to Logic Apps (Standard): Practical Insights from the Field Post by Kunal Saha Kunal Saha outlines why organizations reach an inflection point where Logic Apps Standard becomes a better fit than Consumption. Drawing from field experience, he highlights drivers like consolidated app-level management, richer local development workflows, environment isolation, and cost predictability for sustained workloads. The piece discusses when per-execution billing ceases to be efficient, how Standard’s hosting model supports enterprise governance, and migration considerations around triggers, connectors, and stateful patterns. The article encourages teams to evaluate workload characteristics and operational needs to determine the right time to modernize to Standard. Event Debouncing with Logic Apps and Azure Table Storage Post by Daniel Jonathan This article presents an event debouncing pattern for webhook-heavy systems using three Logic Apps and a single Azure Table Storage table. Incoming events are buffered by upserting rows keyed by entity ID, ensuring only the latest state is retained. A timer-driven workflow processes pending rows after a cooldown window, fetches fresh state from the source, and calls downstream APIs, deleting entries on success or resetting on failure. Benefits include implicit deduplication, reduced downstream load, and operational transparency in Storage Explorer. The pattern suits moderate scale without Service Bus, with caveats for strict ordering or very high throughput scenarios. XML to JSON in Logic Apps: Fixing the “Object vs Array” Trap Post by Prashant Singh Prashant Singh explains a common pitfall when converting XML to JSON in Logic Apps: json(xml(...)) yields an array when multiple nodes exist, but a single object when only one node is present—breaking For each loops. He outlines three remedies: debatch directly with xpath() to always return a node set; wrap the target node with array() to normalize object/array differences; or use coalesce() with array() to safely handle missing nodes. With clear examples and expressions, the post helps engineers avoid brittle assumptions and build resilient workflows that handle single, multiple, or absent records cleanly. DevUP Talks 02 - 2026 Q1 Reflections with Ahmed Bayoumy, Sebastian Meyer and Andrew Wilson Video by Mattias Lögdberg This 12‑minute panel discussion surveys how AI and automation are changing day‑to‑day engineering work. Mattias Lögdberg hosts Ahmed Bayoumy, Sebastian Meyer, and Andrew Wilson to share early field perspectives: the shift from experimentation to production, emerging testing responsibilities around AI‑assisted code, and how integration teams are adapting operating models and skills. The conversation favors practical observations over hype, offering a snapshot of what practitioners are seeing at the start of 2026. It’s a compact watch for leaders tracking real impacts rather than theoretical roadmaps. How low can you code? From ‘drag-and-drop’ dreams to try–catch reality Post by Sonny Gillissen Sonny Gillissen argues that early low‑code promised simplicity but often obscured complexity with visual designers and limited tooling. He suggests AI can shift low‑code from diagramming boxes to describing intent—letting teams express business behavior in natural terms, with systems generating implementations. The piece calls for focusing on domain clarity, robust data/APIs, and guardrails over chasing more drag‑and‑drop. For integration engineers, it frames a path where Logic Apps and related platforms become orchestration shells around AI‑assisted specifications, improving maintainability without hiding the hard parts. Legacy Integration to Azure: 40% Cost Savings and Faster Delivery Post by Adaptiv (post by Simon Clendon) This piece outlines lessons from migrating legacy integration platforms to Microsoft Azure. It details the discovery work needed to untangle historical integrations, the diplomacy required with stakeholders, and the engineering patterns that de-risk cutovers. Highlights include modernizing HR workflows, establishing clear migration decision trees, and treating AI as a force multiplier rather than a silver bullet. The article emphasizes measurable outcomes—around 40% cost savings and faster delivery—while cautioning against underestimating analysis, testing, and organizational change, and recommending experienced partners to accelerate the journey. Using the Right Tool Is Not Over‑Engineering Post by Marcelo Gomes Marcelo Gomes argues that many integration failures stem from tool misalignment rather than flawed logic. Using a market‑stall analogy, he outlines when to rely on API Management for exposure and control, where Logic Apps should orchestrate rather than absorb all work, and why Azure Storage underpins durable, production‑ready designs. The piece encourages architects to map responsibilities explicitly—governance at the edge, orchestration in workflows, compute where it belongs—so systems scale cleanly without masking complexity under a single service. Choosing fit‑for‑purpose components, he suggests, is discipline—not over‑engineering. Using Event Grid to detect deleted files and trigger Logic App Post by Sandro Pereira (author: Luis Rigueira) This walkthrough shows how to capture Azure Storage blob deletion events with Event Grid and invoke a Logic App for downstream actions like audit, recovery, or notifications. It explains why native Blob triggers don’t fire on delete, then sets up a System Topic on the storage account, configures a Logic App with the “When a resource event occurs” trigger for Microsoft.Storage.BlobDeleted, and parses the event payload for container, file name, content‑type, and timestamp. The post provides expressions and screenshots to build the flow end‑to‑end, enabling reliable reactions to file deletions without custom functions.