Processing, storing, and sending data is at the heart of how we communicate and get business done. This involves implementing various applications, software, and mobile devices that together form an intricate web to process data and information. Programmers will often use message brokers to facilitate this constant flow of information. Message brokers and Pub/Sub messaging systems are instrumental in allowing applications, services, and systems to communicate effectively.

Maximizing the value of streaming data requires carefully navigating operational tradeoffs when developing and managing cloud native applications. Organizations that are rapidly producing and processing high volumes of data — like Netflix, Salesforce, Shopify and even the United States Postal Service (USPS), are constantly applying and testing new methods to manage the complexity of data streaming in the cloud.

Banking is about financial transactions. These are executed by sending payments and instructions over middleware. If you control the middleware, then you control the business. If the middleware fails, then the company fails. If you can see and analyze the transactions going through the middleware, you can see the business itself. And if you have real-time analytics of that data and it’s automatically actioned, then you can innovate and accelerate the company’s development.

MQTT is becoming the standard protocol for applications that operate in environments where network connectivity is intermittent or unreliable, reducing bandwidth usage is a priority, or where hardware resources are limited. In this post you will learn about some specific use cases where businesses are seeing value from making MQTT part of their tech stack.

Today’s enterprises can relate to this logic, especially concerning digital transformation projects. They have broken systems that need fixing, but they also spend a lot of effort fixing systems that don’t necessarily need those levels of intervention. Specifically, companies often face a dilemma: digital modernisation requires apps and systems to be upgraded and operate in the new technology norms. Yet those same systems often exist for good reasons.

The concept of containerization helps you run applications as lightweight virtual machines. As a web developer, setting up local development environments can be tiresome. However, using tools like Docker and Kubernetes gives developers an upper hand to quickly set up and deploy applications. This guide uses Docker to deploy a React app to Kubernetes.

You can integrate Edge Flow Manager (EFM) with Apache Kafka and forward agent heartbeats to defined Kafka topics. Learn how to perform the integration with Apache Kafka. To integrate EFM with Kafka, you need to configure Kafka and EFM properties. EFM supports the forwarding of agent heartbeats and acknowledges messages exchanged on the C2 protocol between the EFM server and MiNiFi agents.