Background tasks in .NET
What is a Background Task? A background task (or background service) is work that runs behind the scenes in an application without blocking the main user flow and often without direct user interaction. Think of it as a worker or helper that performs tasks independently while the main app continues doing other things. Problem Statement - What do you do when your downstream API is flaky or sometimes down for hours or even days , yet your UI and main API must stay responsive? Solution - This is a very common architecture problem in enterprise systems, and .NET gives us excellent tools to solve it cleanly: BackgroundService and exponential backoff retry logic. In this article, I’ll walk you through: A real production-like use case The architecture needed to make it reliable Why exponential backoff matters How to build a robust BackgroundService A full working code example The Use Case You have two APIs: API 1 : called frequently by the UI (hundreds or thousands of times). API 2 : a downstream system you must call, but it is known to be unstable, slow, or completely offline for long periods. If API 1 directly calls API 2: * Users experience lag * API 1 becomes slow or unusable * You overload API 2 with retries * Calls fail when API 2 is offline * You lose data What do we do then? Here goes the solution The Architecture Instead of calling API 2 synchronously, API 1 simply stores the intended call, and returns immediately. A BackgroundService will later: Poll for pending jobs Call API 2 Retry with exponential backoff if API 2 is still unavailable Mark jobs as completed when successful This creates a resilient, smooth, non-blocking system. Why Exponential Backoff? When a downstream API is completely offline, retrying every 1–5 seconds is disastrous: It wastes CPU and bandwidth It floods logs It overloads API 2 when it comes back online It burns resources Exponential backoff solves this. Examples retry delays: Retry 1 → 2 sec Retry 2 → 4 sec Retry 3 → 8 sec Retry 4 → 16 sec Retry 5 → 32 sec Retry 6 → 64 sec (Max delay capped at 5 minutes) This gives the system room to breathe. Complete Working Example (Using In-Memory Store) 1. The Model public class PendingJob { public Guid Id { get; set; } = Guid.NewGuid(); public string Payload { get; set; } = string.Empty; public int RetryCount { get; set; } = 0; public DateTime NextRetryTime { get; set; } = DateTime.UtcNow; public bool Completed { get; set; } = false; } 2. The In-Memory Store public interface IPendingJobStore { Task AddJobAsync(string payload); Task<List<PendingJob>> GetExecutableJobsAsync(); Task MarkJobAsCompletedAsync(Guid jobId); Task UpdateJobAsync(PendingJob job); } public class InMemoryPendingJobStore : IPendingJobStore { private readonly List<PendingJob> _jobs = new(); private readonly object _lock = new(); public Task AddJobAsync(string payload) { lock (_lock) { _jobs.Add(new PendingJob { Payload = payload, RetryCount = 0, NextRetryTime = DateTime.UtcNow }); } return Task.CompletedTask; } public Task<List<PendingJob>> GetExecutableJobsAsync() { lock (_lock) { return Task.FromResult(_jobs.Where(j => !j.Completed && j.NextRetryTime <= DateTime.UtcNow).ToList()); } } public Task MarkJobAsCompletedAsync(Guid jobId) { lock (_lock) { var job = _jobs.FirstOrDefault(j => j.Id == jobId); if (job != null) job.Completed = true; } return Task.CompletedTask; } public Task UpdateJobAsync(PendingJob job) => Task.CompletedTask; } 3. The BackgroundService with Exponential Backoff using System.Text; public class Api2RetryService : BackgroundService { private readonly IHttpClientFactory _clientFactory; private readonly IPendingJobStore _store; private readonly ILogger<Api2RetryService> _logger; public Api2RetryService(IHttpClientFactory clientFactory, IPendingJobStore store, ILogger<Api2RetryService> logger) { _clientFactory = clientFactory; _store = store; _logger = logger; } protected override async Task ExecuteAsync(CancellationToken stoppingToken) { _logger.LogInformation("Background retry service started."); while (!stoppingToken.IsCancellationRequested) { var jobs = await _store.GetExecutableJobsAsync(); foreach (var job in jobs) { var client = _clientFactory.CreateClient("api2"); try { var response = await client.PostAsync("/simulate", new StringContent(job.Payload, Encoding.UTF8, "application/json"), stoppingToken); if (response.IsSuccessStatusCode) { _logger.LogInformation("Job {JobId} processed successfully.", job.Id); await _store.MarkJobAsCompletedAsync(job.Id); } else { await HandleFailure(job); } } catch (Exception ex) { _logger.LogError(ex, "Error calling API 2."); await HandleFailure(job); } } await Task.Delay(TimeSpan.FromSeconds(5), stoppingToken); } } private async Task HandleFailure(PendingJob job) { job.RetryCount++; var delay = CalculateBackoff(job.RetryCount); job.NextRetryTime = DateTime.UtcNow.Add(delay); await _store.UpdateJobAsync(job); _logger.LogWarning("Retrying job {JobId} in {Delay}. RetryCount={RetryCount}", job.Id, delay, job.RetryCount); } private TimeSpan CalculateBackoff(int retryCount) { var seconds = Math.Pow(2, retryCount); var maxSeconds = TimeSpan.FromMinutes(5).TotalSeconds; return TimeSpan.FromSeconds(Math.Min(seconds, maxSeconds)); } } 4. The API 1 — Public Endpoint using System.Runtime.InteropServices; using System.Text.Json; [ApiController] [Route("api1")] public class Api1Controller : ControllerBase { private readonly IPendingJobStore _store; private readonly ILogger<Api1Controller> _logger; public Api1Controller(IPendingJobStore store, ILogger<Api1Controller> logger) { _store = store; _logger = logger; } [HttpPost("process")] public async Task<IActionResult> Process([FromBody] object data) { var payload = JsonSerializer.Serialize(data); await _store.AddJobAsync(payload); _logger.LogInformation("Stored job for background processing."); return Ok("Request received. Will process when API 2 recovers."); } } 5. The API 2 (Simulating Downtime) using System.Runtime.InteropServices; [ApiController][Route("api2")] public class Api2Controller: ControllerBase { private static bool shouldFail = true; [HttpPost("simulate")] public IActionResult Simulate([FromBody] object payload) { if (shouldFail) return StatusCode(503, "API 2 is down"); return Ok("API 2 processed payload"); } [HttpPost("toggle")] public IActionResult Toggle() { shouldFail = !shouldFail; return Ok($"API 2 failure mode = {shouldFail}"); } } 6. The Program.cs var builder = WebApplication.CreateBuilder(args); builder.Services.AddControllers(); builder.Services.AddSingleton<IPendingJobStore, InMemoryPendingJobStore>(); builder.Services.AddHttpClient("api2", c => { c.BaseAddress = new Uri("http://localhost:5000/api2"); }); builder.Services.AddHostedService<Api2RetryService>(); var app = builder.Build(); app.MapControllers(); app.Run(); Testing the Whole Flow #1 API 2 starts in failure mode All attempts will fail and exponential backoff kicks in. #2 Send a request to API 1 POST /api1/process { "name": "hello" } Job is stored. #3 Watch logs You’ll see: Retrying job in 2 seconds... Retrying job in 4 seconds... Retrying job in 8 seconds... ... #4 Bring API 2 back online: POST /api2/toggle Next retry will succeed: Job {id} processed successfully. Conclusion This pattern is extremely powerful for: Payment gateways ERP integrations Long-running partner APIs Unstable third-party services Internal microservices that spike or go offline References Background tasks with hosted services in ASP.NET CoreSimplifying Microservice Reliability with Dapr
What is Dapr? Dapr is an open-source runtime developed by Microsoft that is used in building resilient, event-driven, and portable applications. It works using the sidecar pattern, meaning every microservice gets a small companion container — the Dapr sidecar — which handles communication, retries, secrets, state, and more. What is Sidecar ? A sidecar is a helper process that runs beside your app, handling system tasks so your code can focus on business logic. Lets see some offerings from Dapr along with examples. #1 . Bindings Connects your app to external systems (like queues, email, or storage) with zero SDK or protocol handling. Without Dapr ❌ var httpClient = new HttpClient(); await httpClient.PostAsJsonAsync("https://api.sendgrid.com/send", email); * Manage HTTP endpoints & credentials * Change provider → rewrite logic With Dapr ✅ await daprClient.InvokeBindingAsync("send-email", "create", email); * One call, no SDK * Replace SendGrid → SMTP → Twilio just by editing config * No code change, no redeploy How to enable binding in for a Azure Container App Open Azure Portal → go to your Container App Environment. From the left pane, click on Container Apps, and choose your desired app (e.g., orders-api). In the Settings section, select Dapr. Enable Dapr toggle → switch it ON. Provide the basic Dapr settings: App ID: A unique name (e.g., orders-app). App Port: The internal port your API listens on (e.g., 8080). App Protocol: Choose HTTP or gRPC (usually HTTP). Click Save to apply. Now, under the same Container App Environment, go to Dapr Components. Click Create → select Binding → choose the type of binding (e.g., azure.storagequeues). #2 . Configuration Centralizes app settings, allowing live configuration updates without redeploying services. Without Dapr ❌ var featureFlag = Configuration["FeatureX"]; * Requires redeploys for every config change * No centralized versioning or dynamic update With Dapr ✅ var config = await daprClient.GetConfiguration("appconfigstore", new[] { "FeatureX" }); * Use Azure App Config, Consul, or any provider * Centralized updates — no redeploys * Consistent access via Dapr SDK How to enable configuration in for a Azure Container App Open Azure Portal → go to your Container App Environment. From the left pane, click on Container Apps, and choose your desired app (e.g., orders-api). In the Settings section, select Dapr. Enable Dapr toggle → switch it ON. Provide the basic Dapr settings: App ID: A unique name (e.g., orders-app). App Port: The internal port your API listens on (e.g., 8080). App Protocol: Choose HTTP or gRPC (usually HTTP). Click Save to apply. Now, under the same Container App Environment, go to Dapr Components. Click Create → select Configuration→ choose the type of configuration (e.g., configuration.azure.appconfig). #3 . Pub/Sub Enables event-driven communication between microservices without needing to know each other's endpoints. Without Dapr ❌ var client = new ServiceBusClient("<connection-string>"); var sender = client.CreateSender("order-topic"); await sender.SendMessageAsync(new ServiceBusMessage(orderJson)); * Tied to Azure Service Bus * Must manage SDKs, connections, retries * Hard to switch to another broker (Kafka, RabbitMQ) With Dapr ✅ await daprClient.PublishEventAsync("pubsub", "order-created", order); * pubsub component defined in YAML (can be Kafka, Redis Streams, etc.) * No SDK, no broker dependency * Just publish the event — Dapr handles transport & retries How to enable pub/sub in for a Azure Container App Open Azure Portal → go to your Container App Environment. From the left pane, click on Container Apps, and choose your desired app (e.g., orders-api). In the Settings section, select Dapr. Enable Dapr toggle → switch it ON. Provide the basic Dapr settings: App ID: A unique name (e.g., orders-app). App Port: The internal port your API listens on (e.g., 8080). App Protocol: Choose HTTP or gRPC (usually HTTP). Click Save to apply. Now, under the same Container App Environment, go to Dapr Components. Click Create → select Pub/Sub→ choose the type of configuration (e.g., pubsub.azure.servicebus.topics). #4 . Secret Stores Securely retrieves credentials and secrets from vaults, keeping them out of configs and code. Without Dapr ❌ var connString = Configuration["ConnectionStrings:DB"]; * Secrets stored in configs or env vars * Risk of leaks and manual rotation With Dapr ✅ var secret = await daprClient.GetSecretAsync("vault", "dbConnection"); * Fetch directly from Azure Key Vault, AWS Secrets, etc. * No secrets in configs * Secure by default, consistent across services How to enable Secret Stores in for a Azure Container App Open Azure Portal → go to your Container App Environment. From the left pane, click on Container Apps, and choose your desired app (e.g., orders-api). In the Settings section, select Dapr. Enable Dapr toggle → switch it ON. Provide the basic Dapr settings: App ID: A unique name (e.g., orders-app). App Port: The internal port your API listens on (e.g., 8080). App Protocol: Choose HTTP or gRPC (usually HTTP). Click Save to apply. Now, under the same Container App Environment, go to Dapr Components. Click Create → select Secret stores→ choose the type of configuration (e.g., secretstores.azure.keyvault). #5 . State Provides a consistent way to store and retrieve application data across services using a simple API. Without Dapr ❌ var cosmosClient = new CosmosClient(connStr); var container = cosmosClient.GetContainer("db", "state"); await container.UpsertItemAsync(order); * Direct dependency on Cosmos DB * Manual retry logic * Tight coupling to storage type With Dapr ✅ await daprClient.SaveStateAsync("statestore", "order-101", order); var data = await daprClient.GetStateAsync<Order>("statestore", "order-101"); * Plug any backend (Redis, Cosmos, PostgreSQL) * Dapr handles retries and consistency * Same code, different backend — total flexibility How to enable State in for a Azure Container App Open Azure Portal → go to your Container App Environment. From the left pane, click on Container Apps, and choose your desired app (e.g., orders-api). In the Settings section, select Dapr. Enable Dapr toggle → switch it ON. Provide the basic Dapr settings: App ID: A unique name (e.g., orders-app). App Port: The internal port your API listens on (e.g., 8080). App Protocol: Choose HTTP or gRPC (usually HTTP). Click Save to apply. Now, under the same Container App Environment, go to Dapr Components. Click Create → select State → choose the type of configuration (e.g., state.azure.cosmosdb). 🧩 Summary Think of Dapr as your invisible co-pilot for building distributed apps. It abstracts away all the repetitive plumbing — state management, pub/sub messaging, secret handling, and external bindings — letting you focus on writing features that matter. With Dapr, you don’t just write code that runs locally; you write code that just works across clouds, containers, and environments, without having to worry about wiring up retries, event delivery, or service-to-service communication manually. 🧰 Demo Source Code I've prepared complete sample on .Net core that touches all major Dapr features: * State Store * Pub/Sub * Bindings * Configuration * Secret Store You can explore it from Github-Dapr-Api Clone, run locally, and experiment — the project uses in-memory storage to keep things lightweight for testing and learning. 📚 References for Deep Dive Official Dapr Docs Dapr for .NET Developers — Microsoft Learn Dapr .NET SDK GitHubAMA Spotlight: Build Smarter with Azure Developer CLI 'AZD'
Weekly AMA 'Ask Me Anything': Build Smarter with Azure Developer CLI Calling all AI engineers, developers, and builders of the future, this is your backstage pass to the tools shaping scalable, agentic AI deployments. Join Kristen Womack, Product Manager for the Azure Developer CLI (azd) Developer CLI (azd), and the engineering team behind azd for a live Ask Me Anything session every Thursday at 12:30pm PT in the Azure AI Foundry Discord. Whether you're: 🧠 Orchestrating multi-agent systems 📦 Deploying LLM-powered apps with Azure AI Foundry 🔐 Navigating least-privilege infrastructure setups 🛠️ Debugging and optimizing reproducible workflows …this AMA is your chance to connect directly with the team building the CLI that powers it all. 💡 Why Join? Real-time answers from the azd engineers and product team Deployment walkthroughs for Foundry templates, from chatbots to document processors Tips for CI/CD, debugging, and reproducibility in enterprise environments Community-first mindset: bring your feedback, challenges, and ideas Kristen Womack brings deep insight into developer experience and product strategy; this is a rare opportunity to learn from the source and shape the future of AI tooling. 🔧 Get Ready Before you join: Install azd 👉 Install Guide Explore Kristen’s work 👉 www.kristenwomack.io Join the Discord 👉 Azure AI Foundry Community 🗓️ Weekly Schedule 🕧 Thursdays at 12:30pm PT 📍 Azure AI Foundry Discord Bring your questions. Bring your curiosity. Build with the best. Additional resources: check out the AZD for Beginners course https://aka.ms/azd-for-beginnersEssential Microsoft Resources for MVPs & the Tech Community from the AI Tour
Unlock the power of Microsoft AI with redeliverable technical presentations, hands-on workshops, and open-source curriculum from the Microsoft AI Tour! Whether you’re a Microsoft MVP, Developer, or IT Professional, these expertly crafted resources empower you to teach, train, and lead AI adoption in your community. Explore top breakout sessions covering GitHub Copilot, Azure AI, Generative AI, and security best practices—designed to simplify AI integration and accelerate digital transformation. Dive into interactive workshops that provide real-world applications of AI technologies. Take it a step further with Microsoft’s Open-Source AI Curriculum, offering beginner-friendly courses on AI, Machine Learning, Data Science, Cybersecurity, and GitHub Copilot—perfect for upskilling teams and fostering innovation. Don’t just learn—lead. Access these resources, host impactful training sessions, and drive AI adoption in your organization. Start sharing today! Explore now: Microsoft AI Tour Resources.How to Master GitHub Copilot: Build, Prompt, Deploy Smarter
Mastering GitHub Copilot: Build, Prompt, Deploy Smarter is a free, hands-on workshop designed to help developers go beyond autocomplete and unlock the true power of AI-assisted coding. Instead of toy examples, this course walks you through real-world software engineering challenges: messy codebases, multi-language projects, cloud deployments, and legacy system upgrades. You’ll learn practical skills like prompt engineering, advanced Copilot features, and AI pair programming techniques that make you faster, sharper, and more creative. Whether you’re a junior developer or a seasoned architect, mastering GitHub Copilot will help you: Reduce cognitive load and focus on system design Accelerate onboarding for new engineers Write cleaner, more consistent code Automate repetitive tasks to free up time for innovation AI coding tools like GitHub Copilot are no longer optional—they’re essential. This workshop gives you the skills to collaborate with Copilot effectively and stay competitive in the age of AI-powered development.Strategic Solutions for Seamless Integration of Third-Party SaaS
Modern systems must be modular and interoperable by design. Integration is no longer a feature, it’s a requirement. Developers are expected to build architectures that connect easily with third-party platforms, but too often, core systems are designed in isolation. This disconnect creates friction for downstream teams and slows delivery. At Microsoft, SaaS platforms like SAP SuccessFactors and Eightfold support Talent Acquisition by handling functions such as requisition tracking, application workflows, and interview coordination. These tools help reduce costs and free up engineering focus for high-priority areas like Azure and AI. The real challenge is integrating them with internal systems such as Demand Planning, Offer Management, and Employee Central. This blog post outlines a strategy centered around two foundational components: an Integration and Orchestration Layer, and a Messaging Platform. Together, these enable real-time communication, consistent data models, and scalable integration. While Talent Acquisition is the use case here, the architectural patterns apply broadly across domains. Whether you're embedding AI pipelines, managing edge deployments, or building platform services, thoughtful integration needs to be built into the foundation, not bolted on later.Using DeepSeek-R1 on Azure with JavaScript
The pace at which innovative AI models are being developed is outstanding! DeepSeek-R1 is one such model that focuses on complex reasoning tasks, providing a powerful tool for developers to build intelligent applications. The week, we announced its availability on GitHub Models as well as on Azure AI Foundry. In this article, we’ll take a look at how you can deploy and use the DeepSeek-R1 models in your JavaScript applications. TL;DR key takeaways DeepSeek-R1 models focus on complex reasoning tasks, and is not designed for general conversation You can quickly switch your configuration to use Azure AI, GitHub Models, or even local models with Ollama. You can use OpenAI Node SDK or LangChain.js to interact with DeepSeek models. What you'll learn here Deploying DeepSeek-R1 model on Azure. Switching between Azure, GitHub Models, or local (Ollama) usage. Code patterns to start using DeepSeek-R1 with various libraries in TypeScript. Reference links DeepSeek on Azure - JavaScript demos repository Azure AI Foundry OpenAI Node SDK LangChain.js Ollama Requirements GitHub account. If you don't have one, you can create a free GitHub account. You can optionally use GitHub Copilot Free to help you write code and ship your application even faster. Azure account. If you're new to Azure, get an Azure account for free to get free Azure credits to get started. If you're a student, you can also get free credits with Azure for Students. Getting started We'll use GitHub Codespaces to get started quickly, as it provides a preconfigured Node.js environment for you. Alternatively, you can set up a local environment using the instructions found in the GitHub repository. Click on the button below to open our sample repository in a web-based VS Code, directly in your browser: Once the project is open, wait a bit to ensure everything has loaded correctly. Open a terminal and run the following command to install the dependencies: npm install Running the samples The repository contains several TypeScript files under the samples directory that demonstrate how to interact with DeepSeek-R1 models. You can run a sample using the following command: npx tsx samples/<sample>.ts For example, let's start with the first one: npx tsx samples/01-chat.ts Wait a bit, and you should see the response from the model in your terminal. You'll notice that it may take longer than usual to respond, and see a weird response that starts with a <think> tag. This is because DeepSeek-R1 is designed to be used for task that need complex reasoning, like solving problems or answering math questions, and not for you usual chat interactions. Model configuration By default, the repository is configured to use GitHub Models, so you can run any example using Codespaces without any additional setup. While it's great for quick experimentation, GitHub models limit the number of requests you can make in a day and the amount of data you can send in a single request. If you want to use the model more extensively, you can switch to Azure AI or even use a local model with Ollama. You can take a look at the samples/config.ts to see how the different configurations are set up. We'll not cover using Ollama models in this article, but you can find more information in the repository documentation. Deploying DeepSeek-R1 on Azure To experiment with the full capabilities of DeepSeek-R1, you can deploy it on Azure AI Foundry. Azure AI Foundry is a platform that allows you to deploy, manage and develop with AI models quickly. To use Azure AI Foundry, you need to have an Azure account. Let's start by deploying the model on Azure AI Foundry. First, follow this tutorial to deploy a serverless endpoint with the model. When it's time to choose the model, make sure to select the DeepSeek-R1 model in the catalog. Once your endpoint is deployed, you should be able to see your endpoint details and retrieve the URL and API key: Screenshot showing the endpoint details in Azure AI Foundry Then create a .env file in the root of the project and add the following content: AZURE_AI_BASE_URL="https://<your-deployment-name>.<region>.models.ai.azure.com/v1" AZURE_AI_API_KEY="<your-api-key>" Tip: if you're copying the endpoint from the Azure AI Foundry portal, make sure to add the /v1 at the end of the URL. Open the samples/config.ts file and update the default export to use Azure: export default AZURE_AI_CONFIG; Now all samples will use the Azure configuration. Explore reasoning with DeepSeek-R1 Now that you have the model deployed, you can start experimenting with it. Open the samples/08-reasoning.ts file to see how the model handles more complex tasks, like helping us understand a well-known weird piece of code. const prompt = ` float fast_inv_sqrt(float number) { long i; float x2, y; const float threehalfs = 1.5F; x2 = number * 0.5F; y = number; i = *(long*)&y; i = 0x5f3759df - ( i >> 1 ); y = *(float*)&i; y = y * ( threehalfs - ( x2 * y * y ) ); return y; } What is this code doing? Explain me the magic behind it. `; Now run this sample with the command: npx tsx samples/08-reasoning.ts You should see the model's response streaming piece by piece in the terminal, while describing its thought process before providing the actual answer to our question. Screenshot showing the model's response streaming in the terminal Brace yourself, as it might take a while to get the full response! At the end of the process, you should see the model's detailed explanation of the code, along with some context around it. Leveraging frameworks Most examples in this repository are built with the OpenAI Node SDK, but you can also use LangChain.js to interact with the model. This might be especially interested if you need to integrate other sources of data or want to build a more complex application. Open the file samples/07-langchain.ts to have a look at the setup, and see how you can reuse the same configuration we used with the OpenAI SDK. Going further Now it's your turn to experiment and discover the full potential of DeepSeek-R1! You can try more advanced prompts, integrate it into your larger application, or even build agents to make the most out of the model. To continue your learning journey, you can check out the following resources: Generative AI with JavaScript (GitHub): code samples and resources to learn Generative AI with JavaScript. Build a serverless AI chat with RAG using LangChain.js (GitHub): a next step code example to build an AI chatbot using Retrieval-Augmented Generation and LangChain.js.Mastering Query Fields in Azure AI Document Intelligence with C#
Introduction Azure AI Document Intelligence simplifies document data extraction, with features like query fields enabling targeted data retrieval. However, using these features with the C# SDK can be tricky. This guide highlights a real-world issue, provides a corrected implementation, and shares best practices for efficient usage. Use case scenario During the cause of Azure AI Document Intelligence software engineering code tasks or review, many developers encountered an error while trying to extract fields like "FullName," "CompanyName," and "JobTitle" using `AnalyzeDocumentAsync`: The error might be similar to Inner Error: The parameter urlSource or base64Source is required. This is a challenge referred to as parameter errors and SDK changes. Most problematic code are looks like below in C#: BinaryData data = BinaryData.FromBytes(Content); var queryFields = new List<string> { "FullName", "CompanyName", "JobTitle" }; var operation = await client.AnalyzeDocumentAsync( WaitUntil.Completed, modelId, data, "1-2", queryFields: queryFields, features: new List<DocumentAnalysisFeature> { DocumentAnalysisFeature.QueryFields } ); One of the reasons this failed was that the developer was using `Azure.AI.DocumentIntelligence v1.0.0`, where `base64Source` and `urlSource` must be handled internally. Because the older examples using `AnalyzeDocumentContent` no longer apply and leading to errors. Practical Solution Using AnalyzeDocumentOptions. Alternative Method using manual JSON Payload. Using AnalyzeDocumentOptions The correct method involves using AnalyzeDocumentOptions, which streamlines the request construction using the below steps: Prepare the document content: BinaryData data = BinaryData.FromBytes(Content); Create AnalyzeDocumentOptions: var analyzeOptions = new AnalyzeDocumentOptions(modelId, data) { Pages = "1-2", Features = { DocumentAnalysisFeature.QueryFields }, QueryFields = { "FullName", "CompanyName", "JobTitle" } }; - `modelId`: Your trained model’s ID. - `Pages`: Specify pages to analyze (e.g., "1-2"). - `Features`: Enable `QueryFields`. - `QueryFields`: Define which fields to extract. Run the analysis: Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync( WaitUntil.Completed, analyzeOptions ); AnalyzeResult result = operation.Value; The reason this works: The SDK manages `base64Source` automatically. This approach matches the latest SDK standards. It results in cleaner, more maintainable code. Alternative method using manual JSON payload For advanced use cases where more control over the request is needed, you can manually create the JSON payload. For an example: var queriesPayload = new { queryFields = new[] { new { key = "FullName" }, new { key = "CompanyName" }, new { key = "JobTitle" } } }; string jsonPayload = JsonSerializer.Serialize(queriesPayload); BinaryData requestData = BinaryData.FromString(jsonPayload); var operation = await client.AnalyzeDocumentAsync( WaitUntil.Completed, modelId, requestData, "1-2", features: new List<DocumentAnalysisFeature> { DocumentAnalysisFeature.QueryFields } ); When to use the above: Custom request formats Non-standard data source integration Key points to remember Breaking changes exist between preview versions and v1.0.0 by checking the SDK version. Prefer `AnalyzeDocumentOptions` for simpler, error-free integration by using built-In classes. Ensure your content is wrapped in `BinaryData` or use a direct URL for correct document input: Conclusion In this article, we have seen how you can use AnalyzeDocumentOptions to significantly improves how you integrate query fields with Azure AI Document Intelligence in C#. It ensures your solution is up-to-date, readable, and more reliable. Staying aware of SDK updates and evolving best practices will help you unlock deeper insights from your documents effortlessly. Reference Official AnalyzeDocumentAsync Documentation. Official Azure SDK documentation. Azure Document Intelligence C# SDK support add-on query field.Build AI Agents with MCP Tool Use in Minutes with AI Toolkit for VSCode
We’re excited to announce Agent Builder, the newest evolution of what was formerly known as Prompt Builder, now reimagined and supercharged for intelligent app development. This powerful tool in AI Toolkit enables you to create, iterate, and optimize agents—from prompt engineering to tool integration—all in one seamless workflow. Whether you're designing simple chat interactions or complex task-performing agents with tool access, Agent Builder simplifies the journey from idea to integration. Why Agent Builder? Agent Builder is designed to empower developers and prompt engineers to: 🚀 Generate starter prompts with natural language 🔁 Iterate and refine prompts based on model responses 🧩 Break down tasks with prompt chaining and structured outputs 🧪 Test integrations with real-time runs and tool use such as MCP servers 💻 Generate production-ready code for rapid app development And a lot of features are coming soon, stay tuned for: 📝 Use variables in prompts �� Run agent with test cases to test your agent easily 📊 Evaluate the accuracy and performance of your agent with built-in or your custom metrics ☁️ Deploy your agent to cloud Build Smart Agents with Tool Use (MCP Servers) Agents can now connect to external tools through MCP (Model Control Protocol) servers, enabling them to perform real-world actions like querying a database, accessing APIs, or executing custom logic. Connect to an Existing MCP Server To use an existing MCP server in Agent Builder: In the Tools section, select + MCP Server. Choose a connection type: Command (stdio) – run a local command that implements the MCP protocol HTTP (server-sent events) – connect to a remote server implementing the MCP protocol If the MCP server supports multiple tools, select the specific tool you want to use. Enter your prompts and click Run to test the agent's interaction with the tool. This integration allows your agents to fetch live data or trigger custom backend services as part of the conversation flow. Build and Scaffold a New MCP Server Want to create your own tool? Agent Builder helps you scaffold a new MCP server project: In the Tools section, select + MCP Server. Choose MCP server project. Select your preferred programming language: Python or TypeScript. Pick a folder to create your server project. Name your project and click Create. Agent Builder generates a scaffolded implementation of the MCP protocol that you can extend. Use the built-in VS Code debugger: Press F5 or click Debug in Agent Builder Test with prompts like: System: You are a weather forecast professional that can tell weather information based on given location. User: What is the weather in Shanghai? Agent Builder will automatically connect to your running server and show the response, making it easy to test and refine the tool-agent interaction. AI Sparks from Prototype to Production with AI Toolkit Building AI-powered applications from scratch or infusing intelligence into existing systems? AI Sparks is your go-to webinar series for mastering the AI Toolkit (AITK) from foundational concepts to cutting-edge techniques. In this bi-weekly, hands-on series, we’ll cover: 🚀SLMs & Local Models – Test and deploy AI models and applications efficiently on your own terms locally, to edge devices or to the cloud 🔍 Embedding Models & RAG – Supercharge retrieval for smarter applications using existing data. 🎨 Multi-Modal AI – Work with images, text, and beyond. 🤖 Agentic Frameworks – Build autonomous, decision-making AI systems. Watch on Demand Share your feedback Get started with the latest version, share your feedback, and let us know how these new features help you in your AI development journey. As always, we’re here to listen, collaborate, and grow alongside our amazing user community. Thank you for being a part of this journey—let’s build the future of AI together! Join our Microsoft Azure AI Foundry Discord channel to continue the discussion 🚀Microsoft at the European AI and Cloud Summit 2025- Düsseldorf, Germany | Microsoft Event Guide
Join Microsoft and community experts in-person, in one place. The European Collab Summit, European AI & Cloud Summit, and European BizApps Summit are co-located in 2025 – converging on Düsseldorf, Germany, May 26-28, 2025. Get ready for an exciting experience at the European Collaboration Summit, European AI & Cloud Summit, and European BizApps Summit! Taking place from May 26-28, 2025, in Düsseldorf, Germany. This event gives you the chance to explore over 250 sessions packed with insights on Microsoft 365, AI, Azure, Power Platform, Fabric, and so much more. The best part? With a small upgrade, your ticket to one conference opens the door to all three! You’ll have the flexibility to attend the sessions that excite you the most, while connecting with Microsoft experts and other tech enthusiasts along the way. Don’t miss out on this amazing opportunity to learn, grow, and network! The summit will feature pre-conference tutorials, keynotes, breakouts, and more—all dedicated to Copilot and AI, Power Platform, Azure and Microsoft 365 products. With the goal of over 3,000 attendees with 250 sessions across the events. But that's not all!! Along with the European AI and Cloud Summit, which focuses on Artificial Intelligence, Microsoft Azure, OpenAI, and Cloud Security; European Collaboration Summit and the European BizApps Summit, which centers on the Microsoft Power Platform, Microsoft Fabric, Citizen Development, and Low Code/No Code Business Applications. See sessions from all three conferences on the sessions page. Kicking off on May 26 with pre-conference tutorials, the events all run May 26-28, 2025. Join in: The European Collab Summit 2025 | May 26-28, 2025 |European AI and CloudSummit Since its humble beginnings in 2012 with just 200 attendees, the European Collaboration Summit has grown into the world’s largest event focused on Microsoft collaboration technologies. Originally centered on SharePoint, it quickly became a launchpad for innovations like SharePoint Server 2013 and early Office 365. Today, with over 3,000 attendees from around the globe, it’s a dynamic melting pot of professionals—from CEOs to students—gathering in Germany to connect, learn, and grow. At its core, CollabSummit champions knowledge-sharing, meaningful connections, and an inclusive community. Thank you to Adis Jugo, Mustafa Toroman, Brett Lonsdale, Margit Jugo and the wonderful teams of volunteers and sponsors that make these events happen. 101 on the Conference What: European Collaboration Summit, European Cloud Summit, and European BizApps Summit Where: Düsseldorf, Germany CCD Congress Center, Stockumer Kirchstraße 61, 40474 Düsseldorf, Germany When: May 26th-28th 2025 Content: Microsoft presence at the European Collab Summit (ECS) | 3 keynotes | 8 Microsoft Breakout sessions | Microsoft for Startups Booth | Women in Tech and Allies Meet Up Review all sessions, tutorials, and speakers. Registration: Register today | Use the MICROSOFT15 discount code to save 15% off registration. Cost: Summit Ticket - 845 EUR Summit + Tutorial – 1485 EUR Master Pass – 1844 EUR Learn more about ticket prices Primary X handle & official hashtag: Twitter/Instagram: @collabsummit, LinkedIn, YouTube, Facebook Note: For this guide, we’ll use their main acronym ECS to talk about the event European Collaboration Summit and be clear when highlighting content in either Collab, Cloud or Biz app side of things. Microsoft keynotes Summit Keynote The Future of AI Is Already Here Speaker: Marco Casalaina, VP Products, Azure AI and AI Futurist Date/Time: May 27th, 9:30am | Expo City European Collab Summit Microsoft Keynote Unlocking the Future of Work with AI and Microsoft 365 Speaker: Vesa Juvonen, Principal Product Manager Date/Time: May 28th, 9:00am | Room 1 Bizapps Microsoft Keynote Reimaging the future of business applications using Generative AI Speaker: Gurkan Salk, General Manager, Head of Product Copilot for Sales, Service and Finance May 28th, 9:00am | Room 3 Cloud and AI Microsoft Keynote Leveraging Microsoft AI: Navigating the EU AI Act and Unlocking Future Opportunities Speaker: Azar Koulibaly, General Manager and Associate General Counsel May 28th, 9:00am | Room 2 😎Register today | Note: Use the MICROSOFT15 discount code to save 15% off registration. Microsoft-led breakout sessions Seize the chance to choose the sessions that perfectly match your role and interests! Every breakout session is packed with thrilling product updates, captivating demos, inspiring customer stories, invaluable best practices, and deep insights into product and solution strategies. Plus, you'll get exclusive guidance on what the future holds. Don't miss out on this exciting opportunity! You can review each full agenda for European Collab Summit sessions plus, use the event mobile app (iOS and Android) to add sessions to your schedule. Microsoft-led Cloud sessions Professionals, entrepreneurs, and businesses can explore opportunities with Azure, Copilot, and OpenAI, enhancing their knowledge and networking. Attendees will experience demos, discussions, and insights into Microsoft's cloud strategy. The focus is on understanding the impact of cloud adoption and promoting Responsible AI. “Microsoft Defender for Cloud: Deployment Best Practices” with Dominik Hoefling | May 27. 11:00am | Room 14b “Integrating AI with Semantic Kernel” With Majid Hajin | May 27. 11:00am | Room 2 “Build apps that don't fail in production” with Waldek Mastykarz and Garry Trinder | May 27, 12:00pm | Room 2 “Building an Automation Framework Using Ansible for Configuring and Installing Line of Business Appl... with Kimmo Forss | May 27, 12:00pm | Room 14a “Supercharge Your Startup: Build Faster, Smarter, and Cheaper with AI Agents” with Amit Svarzenberg | May 27, 2:30pm | Room 15a “You’ve built an intelligent app powered by Gen AI models—now what?” with Julia Muiruri | May 27, 3:30pm | Room 2 “Microsoft server protection - one agent to rule them all” with Tom Janetscheck | May 27, 4:50pm | Room 2 “Orchestrating Intelligence with Multi-Agent AI Workflows” with Daron Yondem | May 27, 4:50pm | Room 14b “Build voice-based AI agents on Azure” with Boris Bazilevskiy | May 27, 4:50pm | Room 14a “AI Agents for the Rest of Us: Building with the Azure AI Agent Service” with Korey Stegared-Pace | May 27, 5:50pm | Room 2 “Personalize your AI: model Fine-Tune with your data in Azure OpenAI” with Massimo Bonanni | May 28. 10:20am | Room 14b “Building Application Landing zones in Azure” with Kimmo Forss | May 28. 11:20am | Room 14a “How to compile models and build agentic applications capable of exploiting the power of Copilot+ PCs...” with Sam Kemp | May 28. 11:20am | Room 14b “Add multi-channel communication to your AI apps” with Boris Bazilevskiy | May 28. 11:20am | Room 14b “Copilot for Security - advanced automation scenarios” with Shruti Ailani and Bert-Jan Pals | May 28. 1:30pm | Room 14b “From Traction to Production: Maturing your LLMOps step by step” with Maxim Salnikov | May 28. 1:30pm | Room 16a “Device Intelligence with SLM: A Path to Edge Deployment and Cloud Integration” with Lee Stott | May 28. 1:30pm | Room 1 “Measure and mitigate risks for a generative AI app” with Carlotta Castelluccio | May 28. 2:50pm | Room 2 “Build Serverless AI Agents with Semantic Kernel & Azure Cosmos DB” with Mark Brown | May 28. 2:50pm | Room 14b Microsoft-led Collab sessions Ensuring your organization is fully prepared to harness the capabilities of Copilot for Microsoft 365 is vital. The upcoming sessions are designed to focus on technical readiness, offering the latest insights and best practices. Our experts will guide you on how to effectively utilize AI to unlock the full potential of Copilot and maximize its benefits for your organization. “AI Beginner Development Powerclass” with Carlotta Castelluccio, Korey Stegared-Pace, and Lee Stott | May 26, 9:00am | Room 6 “Building experiences for the Microsoft 365 Powerclass” with Vesa Juvonen, Hugo Bernier, David Warner II, Paolo Pialorsi, Stephan Bisser, Thomas Goelles, Derek Cash-Peterson, and Julie M Turner | May 26, 9:00am | Room 8 “Microsoft 365 Copilot extensibility using VS Code - hands-on workshop” with Waldek Mastykarz, Paolo Pialorsi, and Garry Trinder | May 26, 9:00am | Room 16a “Microsoft Cloud Security Powerclass” with Tom Janetscheck and Jussi Roine “Copilot in Dynamics 365 Finance” with Severin Bock | May 26, 9:00am | Room 18a+b “Build Your Own Agent Using Microsoft Copilot Studio and Power Platform!” with Henry Jammes, Damien Bird, Bülent Altinsoy, Dewain Robinson, and Daniel Laskewitz | May 26, 9:00am | Room 17a+b “Am I Entitled? How to manage permissions dynamically in the age of Copilot” with Al Eardley | May 27, 11:00am | Room 17b “Latest platform and extensibility options for SharePoint and Viva Connections” with Vesa Juvonen | May 27, 11:00am | Room 1 “Secure and govern Microsoft 365 Copilot” with Erica Toelle | May 27, 12:00pm | Room 16b “What's New and Next for Engage and Teams: Knowledge, Storyline, Communities, Copilot and Moderation... with Dan Holme | May 27, 12:00pm | Room 1 “What's New and Next for Engage and Teams: Communications, Channels, Leadership, Campaigns and Events” with Dan Holme | May 27, 2:30pm | Room 1 “Maximizing your Information Architecture Strategy with Microsoft 365 Content Features for Copilot a... with Mikael Svenson and Kasper Larsen | May 27, 3:30pm | Room 18b “Extensibility Options to Improve Your Employee Experiences within Viva Connections and SharePoint” with Vesa Juvonen | May 27, 3:30pm | Room 16b “Insider Risk Management - Technical Deep Dive” with Bernd Vellguth | May 27, 4:50pm | Room 19a “Unlocking the Potential of People Data in Microsoft 365” with Wictor Wilén | May 27, 5:50pm | Room 1 “Microsoft Defender for Office 365 - Defense in-depth" with Dominik Hoefling | May 27, 5:50pm | Room 19a “The intranet of tomorrow: Beautiful, flexible, and AI ready” with Vesa Juvonen | May 27, 5:50pm | Room 16b “Designing Business-Centric Solutions with Microsoft 365 Copilot” with Andreas Krüger | May 28, 10:20am | Room 17b “Extending Microsoft 365 Copilot” with Paolo Pialorsi | May 27, 11:00am | Room 16b “How well do Copilot and Agents know you and your team?” with Wictor Wilén | May 28, 11:20am | Room 1 “Extending Microsoft 365 Copilot with Declarative Agents” with Vesa Juvonen and Paolo Pialorsi | May 28, 11:20am | Room 16b “Together We Succeed: Harnessing Community for Career Success” with Vesa Juvonen, Garry Trinder, and Waldek Mastykarz | May 28th, 1:30pm | Run Events Stage (Expo) “SharePoint Embedded - API for your applications” with Dragan Panjkov | May 28, 2:50pm | Room 18a Microsoft-led BizApps sessions Browse these sessions to learn about Power Platform, Power BI, Microsoft Fabric, Business Apps, Dynamics 365, and Citizen Development. “Modernize your Contact Center with Dynamics 365” with Ivica Ivančić | May 27. 11:00am | Room 6 “Unlocking the Power of AI in Microsoft Fabric” with Josh Ndemenge | May 27, 12:00pm | Room 8 “Building Power Apps in the Modern Era” with April Dunnam | May 27, 12:00pm | Room 3 “Copilot in Dynamics 365 Finance” with Severin Bock | May 27, 2:30pm | Room 7b “Mission UX: Decoding the Science of User Experience in Microsoft 365 and Power Platform” with David Warner II and Hugo Bernier | May 27, 2:30pm | Room 3 “Unleash the power of Custom Actions in Power Automate Desktop” with Dieter De Cock | May 27, 2:30pm | Room 5 “Quickstart to Microsoft Power Pages” with Dragan Panjkov | May 27, 3:30pm | Room 7a “Building Secure and Reliable Copilot Agents created with Copilot Studio” with Marco Rocca and Fabio Franzini | May 27, 5:50pm | Room 5 “Innovating with Power Platform's Copilot Studio: Extending and Enhancing SAP with Intelligent Agent... with Marysol Mantilla | May 28. 11:20am | Room 5 “The art of crafting effective prompts for your Power Platform AI tools” with April Dunnam | May 28. 11:20am | Room 3 “Copilot Studio - You Can't Improve What You Can't Measure” with Henry Jammes | May 28. 1:30pm | Room 3 “Transforming Document Management in Power Platform with Intelligent Automation” with Marco Rocca and Fabio Franzini | May 28. 3:50pm | Room 6 European AI and Cloud Summit startup stage, Powered by Microsoft for Startups Supported and co-organized by ECS and Microsoft for Startups, the Microsoft Startup Stage dynamic space is where major industry players connect to explore groundbreaking solutions. on Day1 we will introduce current Microsoft Startup AI Partners and Microsoft Startups highlighting how startups, engage with potential investors and build AI solutions, and learn from visionary thought leaders in AI and cloud computing. On Day 2 we have dedicated AI Startup pitch competition at the end of the day the Startup Pitch Competition winners will receive prestigious awards, including membership in the Microsoft for Startups Program, unlocking exclusive resources, mentorship, and growth opportunities. Showcasing Microsoft Pegasus Startups Holistic AI Synthesized Tips for Attendees Introduce Yourself Your unique insights matter! Engage with others and share your perspective. Participate Fully Put away your laptops and stay focused. Immerse yourself in sessions for in-depth learning, tips, and tricks. Share your Knowledge Don’t hesitate to offer your expertise. Sharing what you know can help others and strengthen the community. Ask Questions and Provide Feedback Your inquiries and suggestions can shape the future of our products. Don’t hold back—your voice matters! Stay Hydrated and Dress Comfortably Keep your energy up and your mind sharp. Dress for movement to enjoy the full experience. Learn more Visit CollabSummit.eu and follow the action on X/Twitter: @CollabSummit / #CollabSummit, @Microsoft365, @MSFTCopilot, @SharePoint, @OneDrive, @MicrosoftTeams, @MSPowerPlat, @Microsoft365Dev, and @MSFTAdoption. We hope to see you in Germany for one of the most impactful events of the year! The European Collaboration Summit offers unique opportunities to connect with industry leaders, explore innovations, and gain insights that can transform your career. With tailored sessions, hands-on demos, and discussions on collaboration tools, it’s the perfect platform to stay ahead of trends. Don’t miss the chance to join a thriving community and unlock your potential! Don't miss out on this incredible opportunity – register today and take advantage of the exclusive discount!
