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This article expands on the most commonly used RabbitMQ use cases, from microservices to real-time notifications and IoT. Key Takeaways RabbitMQ is a versatile message broker that improves communication across various applications, including microservices, background jobs, and IoT devices.
The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.
Further, with the growth and scale of Amazon.com, boundless horizontal scale needed to be a key design point--scaling up simply wasn't an option. Use cases such as gaming, ad tech, and IoT lend themselves particularly well to the key-value data model where the access patterns require low-latency Gets/Puts for known key values.
Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., The digital twin model is worth a close look when designing the next generation of IoT applications.
Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., The digital twin model is worth a close look when designing the next generation of IoT applications.
Internet of Things (IoT). Offers Easy Navigation & Seamless User Experience: Single page app has a simple design, and it delivers an experience like a desktop or mobile app. Consistent with the Statista report, 9% of eCommerce firms invested in progressive web apps (PWA) in 2021. Internet of Things (IoT). Dark Mode.
Examples include tracking a fleet of trucks, analyzing large numbers of banking transactions for potential fraud, managing logistics in the delivery of supplies after a disaster or during a pandemic, recommending products to ecommerce shoppers, and much more. Real-time digital twins are designed to be easy to develop and modify.
Examples include tracking a fleet of trucks, analyzing large numbers of banking transactions for potential fraud, managing logistics in the delivery of supplies after a disaster or during a pandemic, recommending products to ecommerce shoppers, and much more. Real-time digital twins are designed to be easy to develop and modify.
To scale to a larger number of users and support the growth in data volume spurred by social media, web, mobile, IoT, ad-tech, and ecommerce workloads, these tools require customers to invest in even more infrastructure to maintain performance.
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