Mobile App for a Delivery Marketplace

React Native: Key Advantages and Development Tools If you are considering a cross-platform mobile app that offers a native-like experience on both iOS and Android, React Native might be your ideal choice. Originating as an open-source mobile application framework from Meta, React Native harnesses the capabilities of the React library, enabling the creation of impressive native mobile applications. What's more, its compatibility with most major IDEs makes developers' lives easier. Utilizing JavaScript, CSS-style layouts, and the React Library, React Native equips developers to build well-structured apps with captivating interfaces. Notably, it delivers a seamless, native experience while effectively managing platform-specific elements. React Native Strong Suits Native-like performance delivers an experience closely resembling that of native applications. Reusable UI components speed up mobile app development starting from scratch is less necessary. Hot and live reloading speeds up development, especially for UI changes or bug fixes Modular architecture is flexible for updates and promotes team collaboration. Data binding amplifies the app's stability and reliability by instantly mirroring model changes in the UI. Active community support provides rapid troubleshooting, continuous updates, and a plethora of resources, ensuring the platform remains adaptive and robust. Cost-effectiveness with a single codebase for both iOS and Android platforms streamlines development time and resources, offering a more economical approach to app development. React Native Cross-Platform App Development Tools IDEs and Text Editors Visual Studio Code, Android Studio, Xcode for iOS and macOS, WebStorm SDK Expo platform facilitating quick mobile app development and testing Testing and Inspecting Enzyme, Detox, React Native Testing Library, Reactotron Beyond these, React Native provides numerous boilerplates, UI frameworks, libraries, and components available for navigation, animation, state management, and more, such as React Navigation and MobX. When to Use React Native for Your App Development 1. You start with MVP development React Native is particularly valuable for those launching MVPs or startup apps. Its feature of hot reloading speeds up the development process, reducing wait times for recompilation, especially when developers are tweaking the UI or fixing minor bugs. Plus, with a wide array of pre-built components at our disposal, from buttons, lists, maps to more complex components like navigation, modals, we can avoid building basic elements from scratch. CASE STUDY: An example of an MVP built on React Native, allowing our client, the US business, to launch the MVP fast and fit into the budget 2. You plan to extend your mobile app to a web version React Native can save both time and money when developing mobile apps alongside web apps. Extending your React Native app to the web with the help of existing developers will expedite launch and minimize costs. A hallmark of React Native's efficiency is its emphasis on reusing of business logic. At the outset, components primed for reuse are identified. Subsequently, these components are organized into distinct modules or files, forming a cohesive shared codebase or library. Taking it a step further, we can segment the application into Microfrontends, with the core logic isolated within Microservices. This modular approach empowers development teams to operate on different parts independently. Beyond the inherent advantages of React Native, tools such as Storybook come into play, enabling the creation of a shared UI library. This is especially beneficial when creating multiple applications with similar UI elements, which leads to a more efficient development process. CASE STUDY: An example of quick mobile and web apps development through to code reuse between React Native and React for the US startup 3. You build an app with real-time activities and updates For applications that rely on real-time data updates, like chat apps or live score updates, React Native's capabilities are indispensable as they can benefit from its efficient data handling and UI updates. We take advantage of React Native's Virtual DOM, which optimizes rendering and improves app performance. When data changes, only specific parts of the DOM get updated, ensuring efficiency. Then, we use a diffing algorithm to identify what has changed in the Virtual DOM and selectively update those parts of the actual DOM. This results in faster and more efficient updates, which is crucial for real-time data updates. One advantage of React, which we also leverage in React Native, is its use of state and props for data management. While the state is dynamic and can change over time, props remain consistent when passed from parent to child components. This system allows efficient data flow and updates in the application, benefitting real-time data handling. What's no less important, our developers apply numerous third-party libraries helping with real-time data handling, such as socket.io-client for WebSocket communication, or Firebase for real-time databases. CASE STUDY: A mobile banking app built on React Native with the support of instant, real-time payments for the EU startup Xamarin: Key Advantages and Development Tools If you are planning a top-notch mobile app for iOS, Android, Windows and MacOS with ease, Xamarin might be your answer. An open-source platform for native mobile app development, Xamarin provides: Xamarin.Forms: A cross-platform UI toolkit for creating native user interfaces on mobile and desktop with a unified codebase. This streamlines development and eases deployment across various platforms. Xamarin Native: Including Xamarin.iOS, Xamarin.Android, and Xamarin.Mac libraries, it lets developers craft platform-tailored UIs, ensuring optimal performance and access to unique platform features .NET MAUI: Evolving from Xamarin in 2022, .NET MAUI integrates the robustness of Xamarin.Forms with enhanced features, offering low-code solutions. It simplifies the task of developing both native mobile and desktop apps using C# and XAML. Stregths of Xamarin Near-native performance achieves standards almost identical to native for both Android and iOS applications. Comprehensive testing tools provide a vast array, including the Xamarin Test Cloud and Test Recorder. Microsoft support with Xamarin translates to savings in development costs and time, thanks to its ability to utilize a unified codebase for multiple platforms. Cost-effectiveness with Xamarin translates to savings in development costs and time, thanks to its ability to utilize a unified codebase for multiple platforms. Xamarin Cross-Platform App Development Tools IDEs Visual Studio, Rider SDK NuGet, Xamarin Inspector debugging tool, Prism framework for XAML, MFractor tool for code writing in Xamarin.Forms Design Adobe XD, InVision, Sketch, Balsamiq, etc Testing NUnit, xUnit.net, and Visual Studio Unit Testing Framework for unit testing, Instabug for beta testing When to Use Xamarin for Your App Development 1. You're developing enterprise-level apps We recommend Xamarin for enterprise-level apps because it's robust, compatible with .NET, and backed by Microsoft. If your enterprise already utilizes .NET-based applications, Xamarin facilitates the transition. The development team can craft the new app in C#, leveraging the expansive .NET ecosystem, from libraries and tools to APIs. Moreover, as a Microsoft product, Xamarin boasts consistent updates, thorough documentation, and dedicated support. Our developers find it seamless to integrate apps with services like Azure for cloud functionalities, Microsoft Graph for cloud data access, and even Office 365 for enhanced productivity features. With Xamarin, we take advantage of secure storage and encryption to protect sensitive business data at the enterprise-level. CASE STUDY: Crafting a Xamarin-based mobile app for a corporate learning management system 2. Your app demands extensive use of native APIs Xamarin offers full access to a vast array of NuGet packages, facilitating seamless integration with native APIs and UI controls on both iOS and Android. This equips your app with native features and controls, ensuring an experience that feels genuinely native to users. Moreover, Xamarin ensures uninterrupted access to platform-specific features, such as the camera, GPS, sensors, file system, and more. APIs like CLLocationManager for iOS and LocationManager for Android Android are readily accessible, enabling developers to harness the full potential of device-specific functionalities without restrictions. For example, we built a mobile app for a delivery marketplace that involved multiple APIs, including chat functionality integration with Google Maps tracking analytics barcode image processing, and more CASE STUDY: Crafting a Xamarin-based mobile app with native APIs and real-time functionality 3. You build an app with complex UIs If your app requires a complex yet consistent UI across different platforms, Xamarin emerges as a formidable choice. Xamarin.Forms empowers our development team to sculpt intricate user interfaces. These UIs may encompass diverse user interactions, advanced navigation mechanisms, dynamic content display, bespoke animations, multimedia integrations, vast data management, custom components, and responsive designs. While these elements amplify the user experience, they also compound the UI's complexity. Crafting such UIs demands meticulous planning, design, and testing for best usability and performance. However, when skillfully executed, they offer a robust and adaptable user experience. A salient feature of Xamarin.Forms is its ability to map shared UI components to their native counterparts on each platform. This ensures that every UI element not only appears native but also behaves as users anticipate on their specific device. To facilitate the integration with respective platform-specific features, our specialists use Xamarin.Android and Xamarin.iOS separate implementations for Android and iOS platforms. This allows developers to fine-tune the behavior and appearance of the app for each platform. Moreover, a plethora of third-party libraries exist to supplement Xamarin.Forms, furnishing additional UI controls and design patterns. Such resources can further refine and bolster the UI's complexity and utility. CASE STUDY: An advanced mobile app for drone data management in real time React Native vs Xamarin: The Differences that Matter React Native and Xamarin have long been contenders for the top spot in cross-platform mobile development. We've conducted comprehensive research to determine the current leading framework. React Native Xamarin Release 2015 2011 Owner Facebook Microsoft Programming languages TypeScript >NET, C# Development costs free free UI/UX simple simple Performance near-native near-native App memory consumption lower higher Maintainability instant updates updating lags Let's explore some independent analyses to understand how React Native and Xamarin fare against native app development. React Native vs Xamarin: Popularity and Community React Native As of now, the React Native developer community boasts over 2.5K contributors who commit code to the framework's codebase. "With so many people from the community contributing to React Native, we've seen as many as 266 new pull requests per month (up to 10 pull requests per day). Many of these are high-quality and implement widely used features." Martin Konichek, Ex-Software Engineer at Facebook, React Native team Increasing interest in React Native can be also observed on Google Trends. React Native employs JavaScript, which is currently among the most dynamic programming languages. The number of developers working with JavaScript is over 63 percent according to the Stack Overflow survey 2023. Thus, it's relatively easy to hire a professional developer for your app. Airbnb, Walmart, Skype, and Tesla are among the top users of React Native. Furthermore, Facebook's Showcase lists over 100 apps developed with this framework. We have also described some case studies of migrating to React Native in our blog. React Native has new releases every two weeks, which means the developers get the latest features quickly. The project has over 112K stars, which makes it one of the most starred repos on GitHub. Xamarin Founded in 2011, the Xamarin community has grown to 1.4M developers across 120 countries. The project was acquired by Microsoft in 2016 and became part of its Visual Studio IDE. This is one of the key reasons why large companies such as Slack, Siemens, and Pinterest rely on Xamarin development services. Overall, Xamarin is used by over 15.000 companies in fields like energy, transport, healthcare and others. Xamarin vs React Native: Comparison with Native Platforms React Native and Xamarin apps are developed to be compatible with any selected mobile platform. The native components built into the frameworks allow them to essentially “feel” native. Thus, everything a user can see in the React Native/Xamarin cross-platform apps will be displayed in a manner as close as possible to the native one depending on the specific requirements of each mobile platform. React Native (JavaScript) vs Native (Swift) John Calderaio, a Full-Stack Software Engineer, compared the performance of apps developed in native iOS (Swift) and React Native. His analysis considered the implementation of basic app elements in both hybrid and native development while also measuring CPU, GPU, and memory usage. The mobile apps John built with React Native and Swift have an almost identical physical appearance. In terms of performance, the React Native app utilized the CPU less efficiently (over 10% more) but was better in GPU usage and consumed less memory compared to the Swift version. Xamarin (C#) vs Native (Objective-C and Java) Mobile developer Kevin E. Ford compared the performance of apps developed using Native, Cordova, Classic Xamarin, and Xamarin.Forms. He evaluated apps on both iOS and Android and shared his findings on his blog. App Size. App size affects both deployment bandwidth and load time. Kevin found that Xamarin had additional size due to the .Net framework overhead. Load Time. Native technologies demonstrated the quickest load times. However, apps developed with Classic Xamarin were nearly as fast as those built with native languages. "I wanted to see how long it took the application to load into memory. While the initial load time is important, many mobile applications tend to stay in memory so it tends to have a limited impact. For this test I made sure to close all applications before each timing." Kevin Ford Data Load Time. Kevin tested the speed of loading 1,000 records from Azure Mobile Services. Remarkably, Xamarin outperformed the rest. CPU-Intensive Operation. In a test focusing on CPU-intensive operations, Xamarin again showcased superior performance. Objective-C lagged significantly, while Java was just a 0.2-second margin behind. Xamarin vs React Native: Code Sharing A primary advantage of cross-platform development is the potential to share most code between iOS and Android apps. Developers can write the code in JavaScript (React Native) or C# (Xamarin) without diving deep into Swift, Objective-C, or Java. This efficiency eliminates the redundancy of coding the same feature multiple times. React Native While the frameworks employ native components scripted in Objective-C, Swift, or Java, developers can incorporate native ( platform-specific) code. This feature allows developers to integrate platform-specific optimizations and leverage native functionalities in their mobile applications. By creating native modules that bridge JavaScript with platform-specific code (Objective-C/Swift for iOS or Java/Kotlin for Android), developers can fine-tune their app's performance and access platform-specific features while maintaining a single codebase. This not only speeds development up but also offers several advantages, including enhanced performance, access to device features, improved user experiences, efficient development, and cross-platform consistency. However, roughly 90% of the remaining codebase can be shared. Xamarin In this case, developers used C# complemented with .Net framework to build mobile apps for different mobile platforms. Notably, Xamarin consolidates the development environment, allowing all app builds within Visual Studio. Remarkably, Xamarin.Forms enables reuse of up to 96 percent of source code, expediting the development process. Xamarin vs React Native: Licensing Companies aiming for commercial app development must be circumspect about employing open-source code. Although cost-effective compared to proprietary libraries, open-source doesn't guarantee complete code protection. Both React Native and Xamarin function under the MIT license, a highly favored and flexible certification ensuring developer legal protection. The key features of MIT licensing are: no obligation to publicize the source code upon software distribution freedom to introduce modifications under any licensing absence of mandatory change documentation in the source code an implicit stance on patent usage Xamarin vs React Native: Supported Platforms Xamarin vs React Native: Developer Experience Taylor Milliman, a software engineer, built his first food blog app using React Native. The app allows accessing a database of over 1.000 recipes with necessary ingredients, bookmarking and sharing them with other customers. The developer found React Native to be a powerful tool and the future of mobile development. Taylor used the Udemy course and Facebook tutorials to get started. He encountered initial challenges with some components like the CSS flexbox. Still, after acquainting himself with React Native and its resources, Taylor now confidently handles these components. Besides, he noted the ability to share code between Android and iOS mobile apps and to reload immediately. Taylor admitted that he used Android Studio before and had to deal with 30-60 second build times as usual. Hot Reloading saves development time and makes it easier to get into the flow state avoiding time-wasting interruptions. "React Native is a perfect example of what can happen when we apply ideas that have proven successful in one area of software (web), to a seemingly separate area (mobile)." Taylor Milliman Xamarin Contrastingly, .NET Developer Nicu Maxian's 6 months experience with Xamarin presented challenges. He had to create an Android app with Xamarin by reusing Data and Domain layers belonging to the existing iOS app. From problematic updates to adapting to a new IDE, the journey was arduous: every update resulted in a "broken" environment, so the team had to spend hours to find a solution. Secondly, they ran behind schedule because they tried to adapt to working in a new IDE. Thirdly, a notable drawback was the Xamarin community's limited size compared to native developers. However, Nicu appreciated Xamarin's cross-platform solution and its shared code feature. "I still don't believe in Cross Platforms and I would probably stick to native development. I would say that the price for developing Xamarin app is bigger than native application. So, it's not worthy!" Nicu Maxian Both React Native and Xamarin have carved their own niches in cross-platform app development. However, the consensus among developers as of 2023 leans heavily towards React Native. With a developer community almost three times larger than Xamarin's, it's evident that React Native has gained considerable traction and preference. Trends and Forecasts React Native's Momentum: Since its introduction, React Native has consistently grown and has a strong, active community backing it. Its open-source nature ensures continuous improvement through community contributions. The Cross-Platform Future: Predictions point to a rising demand for cross-platform apps, with React Native as a favored choice. Business Adoption Rate: Several notable businesses have already adopted React Native, a testament to its scalability and adaptability. In conclusion, while both frameworks provide valuable tools, React Native's impressive growth underscores its dominant position in the industry. For businesses planning their mobile app development trajectory, aligning with React Native emerges as a forward-thinking and promising direction. Looking for professional mobile app developers? 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Azure SignalR Use Cases Azure SignalR is routinely chosen as the real-time backbone when organizations modernize legacy apps or design new interactive experiences. It can stream data to connected clients instantly instead of forcing them to poll for updates. Azure SignalR can push messages in milliseconds at scale. Live dashboards and monitoring Company KPIs, financial-market ticks, IoT telemetry and performance metrics can update in real time on browsers or mobile devices, and Microsoft’s Stream Analytics pattern documentation explicitly recommends SignalR for such dynamic dashboards. Real-time chat High-throughput chat rooms, customer-support consoles and collaborative messengers rely on SignalR’s group- and user-targeted messaging APIs. Instant broadcasting and notifications One-to-many fan-out allows live sports scores, news flashes, gaming events or travel alerts to reach every subscriber at once. Collaborative editing Co-authoring documents, shared whiteboards and real-time project boards depend on SignalR to keep all participants in sync. High-frequency data interactions Online games, instant polling/voting and live auctions need millisecond round-trips. Microsoft lists these as canonical "high-frequency data update" scenarios. IoT command-and-control SignalR provides the live metrics feed and two-way control channel that sit between device fleets and user dashboards. The official IoT sustainability blueprint ("Project 15") places SignalR in the visualization layer so operators see sensor data and alerts in real time. Azure SignalR Functionality and Value  Azure SignalR Service is a fully-managed real-time messaging service on Azure, so Microsoft handles hosting, scalability, and load-balancing for you. Because the platform takes care of capacity provisioning, connection security, and other plumbing, engineering teams can concentrate on application features. That same model also scales transparently to millions of concurrent client connections, while hiding the complexity of how those connections are maintained. In practice, the service sits as a logical transport layer (a proxy) between your application servers and end-user clients. It offloads every persistent WebSocket (or fallback) connection, leaving your servers free to execute only hub business logic. With those connections in place, server-side code can push content to clients instantly, so browsers and mobile apps receive updates without resorting to request/response polling. This real-time, bidirectional flow underpins chat, live dashboards, and location tracking scenarios. SignalR Service supports WebSockets, Server-Sent Events, and HTTP Long Polling, and it automatically negotiates the best transport each time a client connects. Azure SignalR Service Modes Relevant for Notifications Azure SignalR Service offers three operational modes - Default, Serverless, and Classic - so architects can match the service’s behavior to the surrounding application design. Default mode keeps the traditional ASP.NET Core SignalR pattern: hub logic runs inside your web servers, while the service proxies traffic between those servers and connected clients. Because the hub code and programming model stay the same, organizations already running self-hosted SignalR can migrate simply by pointing existing hubs at Azure SignalR Service rather than rewriting their notification layer. Serverless mode removes hub servers completely. Azure SignalR Service maintains every client connection itself and integrates directly with Azure Functions bindings, letting event-driven functions publish real-time messages whenever they run. In that serverless configuration, the Upstream Endpoints feature can forward client messages and connection events to pre-configured back-end webhooks, enabling full two-way, interactive notification flows even without a dedicated hub server. Because Azure Functions default to the Consumption hosting plan, this serverless pairing scales out automatically when event volume rises and charges for compute only while the functions execute, keeping baseline costs low and directly tied to usage. Classic mode exists solely for backward compatibility - Microsoft advises choosing Default or Serverless for all new solutions. Azure SignalR Integration with Azure Functions Azure SignalR Service teams naturally with Azure Functions to deliver fully managed, serverless real-time applications, removing the need to run or scale dedicated real-time servers and letting engineers focus on code rather than infrastructure. Azure Functions can listen to many kinds of events - HTTP calls, Event Grid, Event Hubs, Service Bus, Cosmos DB change feeds, Storage queues and blobs, and more - and, through SignalR bindings, broadcast those events to thousands of connected clients, forming an automatic event-driven notification pipeline. Microsoft highlights three frequent patterns that use this pipeline out of the box: live IoT-telemetry dashboards, instant UI updates when Cosmos DB documents change, and in-app notifications for new business events. When SignalR Service is employed with Functions it runs in Serverless mode, and every client first calls an HTTP-triggered negotiate Function that uses the SignalRConnectionInfo input binding to return the connection endpoint URL and access token. Once connected, Functions that use the SignalRTrigger binding can react both to client messages and to connection or disconnection events, while complementary SignalROutput bindings let the Function broadcast messages to all clients, groups, or individual users. Developers can build these serverless real-time back-ends in JavaScript, Python, C#, or Java, because Azure Functions natively supports all of these languages. Azure SignalR Notification-Specific Use Cases Azure SignalR Service delivers the core capability a notification platform needs: servers can broadcast a message to every connected client the instant an event happens, the same mechanism that drives large-audience streams such as breaking-news flashes and real-time push notifications in social networks, games, email apps, or travel-alert services. Because the managed service can shard traffic across multiple instances and regions, it scales seamlessly to millions of simultaneous connections, so reach rather than capacity becomes the only design question. The same real-time channel that serves people also serves devices. SignalR streams live IoT telemetry, sends remote-control commands back to field hardware, and feeds operational dashboards. That lets teams surface company KPIs, financial-market ticks, instant-sales counters, or IoT-health monitors on a single infrastructure layer instead of stitching together separate pipelines. Finally, Azure Functions bindings tie SignalR into upstream business workflows. A function can trigger on an external event - such as a new order arriving in Salesforce - and fan out an in-app notification through SignalR at once, closing the loop between core systems and end-users in real time. Azure SignalR Messaging Capabilities for Notifications Azure SignalR Service supplies targeted, group, and broadcast messaging primitives that let a Platform Engineering Director assemble a real-time notification platform without complex custom routing code. The service can address a message to a single user identifier. Every active connection that belongs to that user-whether it’s a phone, desktop app, or extra browser tab-receives the update automatically, so no extra device-tracking logic is required. For finer-grained routing, SignalR exposes named groups. Connections can be added to or removed from a group at runtime with simple methods such as AddToGroupAsync and RemoveFromGroupAsync, enabling role-, department-, or interest-based targeting. When an announcement must reach everyone, a single call can broadcast to every client connected to a hub.  All of these patterns are available through an HTTP-based data-plane REST API. Endpoints exist to broadcast to a hub, send to a user ID, target a group, or even reach one specific connection, and any code that can issue an HTTP request-regardless of language or platform-can trigger those operations.  Because the REST interface is designed for serverless and decoupled architectures, event-generating microservices can stay independent while relying on SignalR for delivery, keeping the notification layer maintainable and extensible. Azure SignalR Scalability for Notification Systems Azure SignalR Service is architected for demanding, real-time workloads and can be scaled out across multiple service instances to reach millions of simultaneous client connections. Every unit of the service supplies a predictable baseline of 1,000 concurrent connections and includes the first 1 million messages per day at no extra cost, making capacity calculations straightforward. In the Standard tier you may provision up to 100 units for a single instance; with 1,000 connections per unit this yields about 100,000 concurrent connections before another instance is required. For higher-end scenarios, the Premium P2 SKU raises the ceiling to 1,000 units per instance, allowing a single service deployment to accommodate roughly one million concurrent connections. Premium resources offer a fully managed autoscale feature that grows or shrinks unit count automatically in response to connection load, eliminating the need for manual scaling scripts or schedules. The Premium tier also introduces built-in geo-replication and zone-redundant deployment: you can create replicas in multiple Azure regions, clients are directed to the nearest healthy replica for lower latency, and traffic automatically fails over during a regional outage. Azure SignalR Service supports multi-region deployment patterns for sharding, high availability and disaster recovery, so a single real-time solution can deliver consistent performance to users worldwide. Azure SignalR Performance Considerations for Real-Time Notifications Azure SignalR documentation emphasizes that the size of each message is a primary performance factor: large payloads negatively affect messaging performance, while keeping messages under about 1 KB preserves efficiency. When traffic is a broadcast to thousands of clients, message size combines with connection count and send rate to define outbound bandwidth, so oversized broadcasts quickly saturate throughput; the guide therefore recommends minimizing payload size in broadcast scenarios. Outbound bandwidth is calculated as outbound connections × message size / send interval, so smaller messages let the same SignalR tier push many more notifications per second before hitting throttling limits, increasing throughput without extra units. Transport choice also matters: under identical conditions WebSockets deliver the highest performance, Server-Sent Events are slower, and Long Polling is slowest, which is why Azure SignalR selects WebSocket when it is permitted. Microsoft’s Blazor guidance notes that WebSockets give lower latency than Long Polling and are therefore preferred for real-time updates. The same performance guide explains heavy message traffic, large payloads, or the extra routing work required by broadcasts and group messaging can tax CPU, memory, and network resources even when connection counts are within limits, highlighting the need to watch message volume and complexity as carefully as connection scaling. Azure SignalR Security for Notification Systems Azure SignalR Service provides several built-in capabilities that a platform team can depend on when hardening a real-time notification solution. Flexible authentication choices The service accepts access-key connection strings, Microsoft Entra ID application credentials, and Azure-managed identities, so security teams can select the mechanism that best fits existing policy and secret-management practices.  Application-centric client authentication flow Clients first call the application’s /negotiate endpoint. The app issues a redirect containing an access token and the service URL, keeping user identity validation inside the application boundary while SignalR only delivers traffic.  Managed-identity authentication for serverless upstream calls In Serverless mode, an upstream endpoint can be configured with ManagedIdentity. SignalR Service then presents its own Azure identity when invoking backend APIs, removing the need to store or rotate custom secrets.  Private Endpoint network isolation The service can be bound to an Azure Private Endpoint, forcing all traffic onto a virtual network and allowing operators to block the public endpoint entirely for stronger perimeter control. The notification system can meet security requirements for financial notifications, personal health alerts, or confidential business communications and other sensitive enterprise scenarios. Azure SignalR Message Size and Rate Limitations Client-to-server limits Azure imposes no service-side size ceiling on WebSocket traffic coming from clients, but any SignalR hub hosted on an application server starts with a 32 KB maximum per incoming message unless you raise or lower it in hub configuration. When WebSockets are not available and the connection falls back to long-polling or Server-Sent Events, the platform rejects any client message larger than 1 MB. Server-to-client guidance Outbound traffic from the service to clients has no hard limit, but Microsoft recommends staying under 16 MB per message. Application servers again default to 32 KB unless you override the setting (same sources as above). Serverless REST API constraints If you publish notifications through the service’s serverless REST API, the request body must not exceed 1 MB and the combined headers must stay under 16 KB. Billing and message counting For billing, Azure counts every 2 KB block as one message: a payload of 2,001 bytes is metered as two messages, a 4 KB payload as three, and so on. Premium-tier rate limiting The Premium tier adds built-in rate-limiting controls - alongside autoscaling and a higher SLA - to stop any client or publisher from flooding the service. Azure SignalR Pricing and Costs for Notification Systems Azure SignalR Service is sold on a pure consumption basis: you start and stop whenever you like, with no upfront commitment or termination fees, and you are billed only for the hours a unit is running. The service meters traffic very specifically: only outbound messages are chargeable, while every inbound message is free. In addition, any message that exceeds 2 KB is internally split into 2-KB chunks, and the chunks - not the original payload - are what count toward the bill. Capacity is defined at the tier level. In both the Standard and Premium tiers one unit supports up to 1 000 concurrent connections and gives unlimited messaging with the first 1 000 000 messages per unit each day free of charge. For US regions, the two paid tiers of Azure SignalR Service differ only in cost and in the extras that come with the Premium plan - not in the raw connection or message capacity. In Central US/East US, Microsoft lists the service-charge portion at $1.61 per unit per day for Standard and $2.00 per unit per day for Premium. While both tiers share the same capacity, Premium adds fully managed auto-scaling, availability-zone support, geo-replication and a higher SLA (99.95% versus 99.9%). Finally, those daily rates change from region to region. The official pricing page lets you pick any Azure region and instantly see the local figure. Azure SignalR Monitoring and Diagnostics for Notification Systems Azure Monitor is the built-in Azure platform service that collects and aggregates metrics and logs for Azure SignalR Service, giving a single place to watch the service’s health and performance. Azure SignalR emits its telemetry directly into Azure Monitor, so every metric and resource log you configure for the service appears alongside the rest of your Azure estate, ready for alerting, analytics or export. The service has a standard set of platform metrics for a real-time hub: Connection Count (current active client connections) Inbound Traffic (bytes received by the service) Outbound Traffic (bytes sent by the service) Message Count (total messages processed) Server Load (percentage load across allocated units) System Errors and User Errors (ratios of failed operations) All of these metrics are documented in the Azure SignalR monitoring data reference and are available for charting, alert rules, and autoscale logic. Beyond metrics, Azure SignalR exposes three resource-log categories: Connectivity logs, Messaging logs and HTTP request logs. Enabling them through Azure Monitor diagnostic settings adds granular, per-event detail that’s essential for deep troubleshooting of connection issues, message flow or REST calls. Finally, Azure Monitor Workbooks provide an interactive canvas inside the Azure portal where you can mix those metrics, log queries and explanatory text to build tailored dashboards for stakeholders - effectively turning raw telemetry from Azure SignalR into business-oriented, shareable reports. Azure SignalR Client-Side Considerations for Notification Recipients Azure SignalR Service requires every client to plan for disconnections. Microsoft’s guidance explains that connections can drop during routine hub-server maintenance and that applications "should handle reconnection" to keep the experience smooth. Transient network failures are called out as another common reason a connection may close. The mainstream client SDKs make this easy because they already include automatic-reconnect helpers. In the JavaScript library, one call to withAutomaticReconnect() adds an exponential back-off retry loop, while the .NET client offers the same pattern through WithAutomaticReconnect() and exposes Reconnecting / Reconnected events so UX code can react appropriately. Sign-up is equally straightforward: the connection handshake starts with a negotiate request, after which the AutoTransport logic "automatically detects and initializes the appropriate transport based on the features supported on the server and client", choosing WebSockets when possible and transparently falling back to Server-Sent Events or long-polling when necessary. Because those transport details are abstracted away, a single hub can serve a wide device matrix - web and mobile browsers, desktop apps, mobile apps, IoT devices, and even game consoles are explicitly listed among the supported client types. Azure publishes first-party client SDKs for .NET, JavaScript, Java, and Python, so teams can add real-time features to existing codebases without changing their core technology stack. And when an SDK is unavailable or unnecessary, the service exposes a full data-plane REST API. Any language that can issue HTTP requests can broadcast, target individual users or groups, and perform other hub operations over simple HTTP calls. Azure SignalR Availability and Disaster Recovery for Notification Systems Azure SignalR Service offers several built-in features that let a real-time notification platform remain available and recoverable even during severe infrastructure problems: Resilience inside a single region The Premium tier automatically spreads each instance across Azure Availability Zones, so if an entire datacenter fails, the service keeps running without intervention.  Protection from regional outages For region-level faults, you can add replicas of a Premium-tier instance in other Azure regions. Geo-replication keeps configuration and data in sync, and Azure Traffic Manager steers every new client toward the closest healthy replica, then excludes any replica that fails its health checks. This delivers fail-over across regions.  Easier multi-region operations Because geo-replication is baked into the Premium tier, teams no longer need to script custom cross-region connection logic or replication plumbing - the service now "makes multi-region scenarios significantly easier" to run and maintain.  Low-latency global routing Two complementary front-door options help route clients to the optimal entry point: Azure Traffic Manager performs DNS-level health probes and latency routing for every geo-replicated SignalR instance. Azure Front Door natively understands WebSocket/WSS, so it can sit in front of SignalR to give edge acceleration, global load-balancing, and automatic fail-over while preserving long-lived real-time connections. Verified disaster-recovery readiness Microsoft’s Well-Architected Framework stresses that a disaster-recovery plan must include regular, production-level DR drills. Only frequent fail-over tests prove that procedures and recovery-time objectives will hold when a real emergency strikes. How Belitsoft Can Help Belitsoft is the engineering partner for teams building real-time applications on Azure. We build fast, scale right, and think ahead - so your users stay engaged and your systems stay sane. We provide Azure-savvy .NET developers who implement SignalR-powered real-time features. Our teams migrate or build real-time dashboards, alerting systems, or IoT telemetry using Azure SignalR Service - fully managed, scalable, and cost-predictable. Belitsoft specializes in .NET SignalR migrations - keeping your current hub logic while shifting the plumbing to Azure SignalR. You keep your dev workflow, but we swap out the homegrown infrastructure for Azure’s auto-scalable, high-availability backbone. The result - full modernization. We design event-driven, serverless notification systems using Azure SignalR in Serverless Mode + Azure Functions. We’ll wire up your cloud events (CosmosDB, Event Grid, Service Bus, etc.) to instantly trigger push notifications to web and mobile apps. Our Azure-certified engineers configure Managed Identity, Private Endpoints, and custom /negotiate flows to align with your zero-trust security policies. Get the real-time UX without security concerns. We build globally resilient real-time backends using Azure SignalR Premium SKUs, geo-replication, availability zones, and Azure Front Door. Get custom dashboards with Azure Monitor Workbooks for visualizing metrics and alerting. Our SignalR developers set up autoscale and implement full-stack SignalR notification logic using the client SDKs (.NET, JS, Python, Java) or pure REST APIs. Target individual users, dynamic groups, or everyone in one go. We implement auto-reconnect, transport fallback, and UI event handling.

Benefits of Azure Functions With Azure Functions, enterprises offload operational burden to Azure or outsource infrastructure management to Microsoft. There are no servers/VMs for operations teams to manage. No patching OS, configuring scale sets, or worrying about load balancer configuration. Fewer infrastructure management tasks mean smaller DevOps teams and free IT personnel. Functions Platform-as-a-Service integrates easily with other Azure services - it is a prime candidate in any 2025 platform selection matrix. CTOs and VPs of Engineering see adopting Functions as aligned with transformation roadmaps and multi-cloud parity goals. They also view Functions on Azure Container Apps as a logical step in microservice re-platforming and modernization programs, because it enables lift-and-shift of container workloads into a serverless model. Azure Functions now supports container-app co-location and user-defined concurrency - it fits modern reference architectures while controlling spend. The service offers pay-per-execution pricing and a 99.95% SLA on Flex Consumption. Many previous enterprise blockers - network isolation, unpredictable cold starts, scale ceilings - are now mitigated with the Flex Consumption SKU (faster cold starts, user-set concurrency, VNet-integrated "scale-to-zero"). Heads of Innovation pilot Functions for business-process automation and novel services, since MySQL change-data triggers, Durable orchestrations, and browser-based Visual Studio Code enable quick prototyping of automation and new products. Functions enables rapid feature rollout through code-only deployment and auto-scaling, and new OpenAI bindings shorten minimum viable product cycles for artificial intelligence, so Directors of Product see it as a lever for faster time-to-market and differentiation. Functions now supports streaming HTTP, common programming languages like .NET, Node, and Python, and browser-based development through Visual Studio Code, so team onboarding is low-friction. Belitsoft applies deep Azure and .NET development expertise to design serverless solutions that scale with your business. Our Azure Functions developers architect systems that reduce operational overhead, speed up delivery, and integrate seamlessly across your cloud stack. Future of Azure Functions Azure Functions will remain a cornerstone of cloud-native application design. It follows Microsoft's cloud strategy of serverless and event-driven computing and aligns with containers/Kubernetes and AI trends. New features will likely be backward-compatible, protecting investments in serverless architecture. Azure Functions will continue integrating with other Azure services. .NET functions are transitioning to the isolated worker model, decoupling function code from host .NET versions - by 2026, the older in-process model will be phased out. What is Azure Functions Azure Functions is a fully managed serverless service - developers don’t have to deploy or maintain servers. Microsoft handles the underlying servers, applies operating-system and runtime patches, and provides automatic scaling for every Function App. Azure Functions scales out and in automatically in response to incoming events - no autoscale rules are required. On Consumption and Flex Consumption plans you pay only when functions are executing - idle time isn’t billed. The programming model is event-driven, using triggers and bindings to run code when events occur. Function executions are intended to be short-lived (default 5-minute timeout, maximum 10 minutes on the Consumption plan). Microsoft guidance is to keep functions stateless and persist any required state externally - for example with Durable Functions entities.  The App Service platform automatically applies OS and runtime security patches, so Function Apps receive updates without manual effort. Azure Functions includes built-in triggers and bindings for services such as Azure Storage, Event Hubs, and Cosmos DB, eliminating most custom integration code. Azure Functions Core Architecture Components Each Azure Function has exactly one trigger, making it an independent unit of execution. Triggers insulate the function from concrete event sources (HTTP requests, queue messages, blob events, and more), so the function code stays free of hard-wired integrations. Bindings give a declarative way to read from or write to external services, eliminating boiler-plate connection code. Several functions are packaged inside a Function App, which supplies the shared execution context and runtime settings for every function it hosts. Azure Function Apps run on the Azure App Service platform. The platform can scale Function Apps out and in automatically based on workload demand (for example, in Consumption, Flex Consumption, and Premium plans). Azure Functions offers three core hosting plans - Consumption, Premium, and Dedicated (App Service) - each representing a distinct scaling model and resource envelope. Because those plans diverge in limits (CPU/memory, timeout, scale-out rules), they deliver different performance characteristics. Function Apps can use enterprise-grade platform features - including Managed Identity, built-in Application Insights monitoring, and Virtual Network Integration - for security and observability. The runtime natively supports multiple languages (C#, JavaScript/TypeScript, Python, Java, PowerShell, and others), letting each function be written in the team’s preferred stack. Advanced Architecture Patterns Orchestrator functions can call other functions in sequence or in parallel, providing a code-first workflow engine on top of the Azure Functions runtime. Durable Functions is an extension of Azure Functions that enables stateful function orchestration. It lets you build long-running, stateful workflows by chaining functions together. Because Durable Functions keeps state between invocations, architects can create more-sophisticated serverless solutions that avoid the traditional stateless limitation of FaaS. The stateful workflow model is well suited to modeling complex business processes as composable serverless workflows. It adds reliability and fault tolerance. As of 2025, Durable Functions supports high-scale orchestrations, thanks to the new durable-task-scheduler backend that delivers the highest throughput. Durable Functions now offers multiple managed and BYO storage back-ends (Azure Storage, Netherite, MSSQL, and the new durable-task-scheduler), giving architects new options for performance. Azure Logic Apps and Azure Functions have been converging. Because Logic Apps Standard is literally hosted inside the Azure Functions v4 runtime, every benefit for Durable Functions (stateful orchestration, high-scale back-ends, resilience, simplified ops) now spans both the code-first and low-code sides of Azure’s workflow stack. Architects can mix Durable Functions and Logic Apps on the same CI/CD pipeline, and debug both locally with one tooling stack. They can put orchestrator functions, activity functions, and Logic App workflows into a single repo and deploy them together. They can also run Durable Functions and Logic Apps together in the same resource group, share a storage account, deploy from the same repo, and wire them up through HTTP or Service Bus (a budget for two plans or an ASE is required). Azure Functions Hosting Models and Scalability Options Azure Functions offers five hosting models - Consumption, Premium, Dedicated, Flex Consumption, and container-based (Azure Container Apps). The Consumption plan is billed strictly “per-execution”, based on per-second resource consumption and number of executions. This plan can scale down to zero when the function app is idle. Microsoft documentation recommends the Consumption plan for irregular or unpredictable workloads. The Premium plan provides always-ready (pre-warmed) instances that eliminate cold starts. It auto-scales on demand while avoiding cold-start latency. In a Dedicated (App Service) plan the Functions host “can run continuously on a prescribed number of instances”, giving fixed compute capacity. The plan is recommended when you need fully predictable billing and manual scaling control. The Flex Consumption plan (GA 2025) lets you choose from multiple fixed instance-memory sizes (currently 2 GB and 4 GB). Hybrid & multi-cloud Function apps can be built and deployed as containers and run natively inside Azure Container Apps, which supplies a fully-managed, KEDA-backed, Kubernetes-based environment. Kubernetes-based hosting The Azure Functions runtime is packaged as a Docker image that “can run anywhere,” letting you replicate serverless capabilities in any Kubernetes cluster. AKS virtual nodes are explicitly supported. KEDA is the built-in scale controller for Functions on Kubernetes, enabling scale-to-zero and event-based scale out. Hybrid & multi-cloud hosting with Azure Arc Function apps (code or container) can be deployed to Arc-connected clusters, giving you the same Functions experience on-premises, at the edge, or in other clouds. Arc lets you attach Kubernetes clusters “running anywhere” and manage & configure them from Azure, unifying governance and operations. Arc supports clusters on other public clouds as well as on-premises data centers, broadening where Functions can run. Consistent runtime everywhere Because the same open-source Azure Functions runtime container is used across Container Apps, AKS/other Kubernetes clusters, and Arc-enabled environments, the execution model, triggers, and bindings remain identical no matter where the workload is placed. Azure Functions Enterprise Integration Capabilities Azure Functions runs code without you provisioning or managing servers. It is event-driven and offers triggers and bindings that connect your code to other Azure or external services. It can be triggered by Azure Event Grid events, by Azure Service Bus queue or topic messages, or invoked directly over HTTP via the HTTP trigger, enabling API-style workloads. Azure Functions is one of the core services in Azure Integration Services, alongside Logic Apps, API Management, Service Bus, and Event Grid. Within that suite, Logic Apps provides high-level workflow orchestration, while Azure Functions provides event-driven, code-based compute for fine-grained tasks. Azure Functions integrates natively with Azure API Management so that HTTP-triggered functions can be exposed as managed REST APIs. API Management includes built-in features for securing APIs with authentication and authorization, such as OAuth 2.0 and JWT validation. It also supports request throttling and rate limiting through the rate-limit policy, and supports formal API versioning, letting you publish multiple versions side-by-side. API Management is designed to securely publish your APIs for internal and external developers. Azure Functions scales automatically - instances are added or removed based on incoming events. Azure Functions Security Infrastructure hardening Azure App Service - the platform that hosts Azure Functions - actively secures and hardens its virtual machines, storage, network connections, web frameworks, and other components.  VM instances and runtime software that run your function apps are regularly updated to address newly discovered vulnerabilities.  Each customer’s app resources are isolated from those of other tenants.  Identity & authentication Azure Functions can authenticate users and callers with Microsoft Entra ID (formerly Azure AD) through the built-in App Service Authentication feature.  The Functions can also be configured to use any standards-compliant OpenID Connect (OIDC) identity provider.  Network isolation Function apps can integrate with an Azure Virtual Network. Outbound traffic is routed through the VNet, giving the app private access to protected resources.  Private Endpoint support lets function apps on Flex Consumption, Elastic Premium, or Dedicated (App Service) plans expose their service on a private IP inside the VNet, keeping all traffic on the corporate network.  Credential management Managed identities are available for Azure Functions; the platform manages the identity so you don’t need to store secrets or rotate credentials.  Transport-layer protection You can require HTTPS for all public endpoints. Azure documentation recommends redirecting HTTP traffic to HTTPS to ensure SSL/TLS encryption.  App Service (and therefore Azure Functions) supports TLS 1.0 – 1.3, with the default minimum set to TLS 1.2 and an option to configure a stricter minimum version.  Security monitoring Microsoft Defender for Cloud integrates directly with Azure Functions and provides vulnerability assessments and security recommendations from the portal.  Environment separation Deployment slots allow a single function app to run multiple isolated instances (for example dev, test, staging, production), each exposed at its own endpoint and swappable without downtime.  Strict single-tenant / multi-tenant isolation Running Azure Functions inside an App Service Environment (ASE) places them in a fully isolated, dedicated environment with the compute that is not shared with other customers - meeting high-sensitivity or regulatory isolation requirements.  Azure Functions Monitoring Azure Monitor exposes metrics both at the Function-App level and at the individual-function level (for example Function Execution Count and Function Execution Units), enabling fine-grained observability. Built-in observability Native hook-up to Azure Monitor & Application Insights – every new Function App can emit metrics, logs, traces and basic health status without any extra code or agents.  Data-driven architecture decisions Rich telemetry (performance, memory, failures) – Application Insights automatically captures CPU & memory counters, request durations and exception details that architects can query to guide sizing and design changes.  Runtime topology & trace analysis Application Map plus distributed tracing render every function-to-function or dependency call, flagging latency or error hot-spots so that inefficient integrations are easy to see.  Enterprise-wide data export Diagnostic settings let you stream Function telemetry to Log Analytics workspaces or Event Hubs, standardising monitoring across many environments and aiding compliance reporting.  Infrastructure-as-Code & DevOps integration Alert and monitoring rules can be authored in ARM/Bicep/Terraform templates and deployed through CI/CD pipelines, so observability is version-controlled alongside the function code.  Incident management & self-healing Function-specific "Diagnose and solve problems" detectors surface automated diagnostic insights, while Azure Monitor action groups can invoke runbooks, Logic Apps or other Functions to remediate recurring issues with no human intervention.  Hybrid / multi-cloud interoperability OpenTelemetry preview lets a Function App export the very same traces and logs to any OTLP-compatible endpoint as well as (or instead of) Application Insights, giving ops teams a unified view across heterogeneous platforms.  Cost-optimisation insights Fine-grained metrics such as FunctionExecutionCount and FunctionExecutionUnits (GB-seconds = memory × duration) identify high-cost executions or over-provisioned plans and feed charge-back dashboards.  Real-time storytelling tools Application Map and the Live Metrics Stream provide live, clickable visualisations that non-technical stakeholders can grasp instantly, replacing static diagrams during reviews or incident calls.  Kusto log queries across durations, error rates, exceptions and custom metrics to allow architects prove performance, reliability and scalability targets. Azure Functions Performance and Scalability Scaling capacity Azure Functions automatically add or remove host instances according to the volume of trigger events. A single Windows-based Consumption-plan function app can fan out to 200 instances by default (100 on Linux). Quota increases are possible. You can file an Azure support request to raise these instance-count limits. Cold-start behaviour & mitigation Because Consumption apps scale to zero when idle, the first request after idleness incurs extra startup latency (a cold start). Premium plan keeps instances warm. Every Premium (Elastic Premium) plan keeps at least one instance running and supports pre-warmed instances, effectively eliminating cold starts. Scaling models & concurrency control Functions also support target-based scaling, which can add up to four instances per decision cycle instead of the older one-at-a-time approach. Premium plans let you set minimum/maximum instance counts and tune per-instance concurrency limits in host.json. Regional characteristics Quotas are scoped per region. For example, Flex Consumption imposes a 512 GB regional memory quota, and Linux Consumption apps have a 500-instance-per-subscription-per-hour regional cap. Apps can be moved or duplicated across regions. Microsoft supplies guidance for relocating a Function App to another Azure region and for cross-region recovery. Downstream-system protection Rapid scale-out can overwhelm dependencies. Microsoft’s performance guidance warns that Functions can generate throughput faster than back-end services can absorb and recommends applying throttling or other back-pressure techniques. Configuration impact on cost & performance Plan selection and tuning directly affect both. Choice of hosting plan, instance limits and concurrency settings determine a Function App’s cold-start profile, throughput and monthly cost. How Belitsoft Can Help Our serverless developers modernize legacy .NET apps into stateless, scalable Azure Functions and Azure Container Apps. The team builds modular, event-driven services that offload operational grunt work to Azure. You get faster delivery, reduced overhead, and architectures that belong in this decade. Also, we do CI/CD so your devs can stop manually clicking deploy. We ship full-stack teams fluent in .NET, Python, Node.js, and caffeine - plus SignalR developers experienced in integrating live messaging into serverless apps. Whether it's chat, live dashboards, or notifications, we help you deliver instant, event-driven experiences using Azure SignalR Service with Azure Functions. Our teams prototype serverless AI with OpenAI bindings, Durable Functions, and browser-based VS Code so you can push MVPs like you're on a startup deadline. You get your business processes automated so your workflows don’t depend on somebody's manual actions. Belitsoft’s .NET engineers containerize .NET Functions for Kubernetes and deploy across AKS, Container Apps, and Arc. They can scale with KEDA, trace with OpenTelemetry, and keep your architectures portable and governable. Think: event-driven, multi-cloud, DevSecOps dreams - but with fewer migraines. We build secure-by-design Azure Functions with VNet, Private Endpoints, and ASE. Our .NET developers do identity federation, TLS enforcement, and integrate Azure Monitor + Defender. Everything sensitive is locked in Key Vault. Our experts fine-tune hosting plans (Consumption, Premium, Flex) for cost and performance sweet spots and set up full observability pipelines with Azure Monitor, OpenTelemetry, and Logic Apps for auto-remediation. Belitsoft helps you build secure, scalable solutions that meet real-world demands - across industries and use cases. We offer future-ready architecture for your needs - from cloud migration to real-time messaging and AI integration. Consult our experts.