Apache Kafka became the de facto standard for processing data in motion. Kafka is open, flexible, and scalable. Unfortunately, the latter makes operations a challenge for many teams. Ideally, teams can use a serverless Kafka SaaS offering to focus on business logic. However, hybrid scenarios require a cloud-native platform that provides automated and elastic tooling to reduce the operations burden. This blog post explores how to leverage cloud-native and serverless Kafka offerings in a hybrid cloud architecture. We start from the perspective of data at rest with a data lake and explore its relation to data in motion with Kafka.
This post explores use cases and architectures for processing data in motion with Apache Kafka in Industrial IoT (IIoT) across verticals such as automotive, energy, steel manufacturing, oil&gas, cybersecurity, shipping, logistics. Use cases include predictive maintenance, quality assurance, track and track, real-time locating system (RTLS), asset tracking, customer 360, and more. Examples include BMW, Bosch, Baader, Intel, Porsche, and Devon.
Apache Kafka became the de facto standard for event streaming. Various vendors added Kafka and related tooling to their offerings or provide a Kafka cloud service. This blog post uses the car analogy – from the motor engine to the self-driving car – to explore the different Kafka offerings available on the market. The goal is not a feature-by-feature comparison. Instead, the intention is to educate about the different deployment models, product strategies, and trade-offs from the available options.
Apache Kafka and MQTT are a perfect combination for many IoT use cases. This blog series covers the pros and cons of both technologies. Various use cases across industries, including connected vehicles, manufacturing, mobility services, and smart city are explored. The examples use different architectures, including lightweight edge scenarios, hybrid integrations, and serverless cloud solutions. This post is part two: Connected Vehicles and V2X applications.
Hybrid cloud architectures are the new black for most companies. A cloud-first is obvious for many, but legacy infrastructure has to be maintained, integrated, and (maybe) replaced over time. Event Streaming with the Apache Kafka ecosystem is a perfect technology for building hybrid replication in real-time at scale.
The digital transformation connects the world. People, vehicles, factories, cities, digital services, and other “things” communicate with each other in real-time to provide a safe environment, efficient processes, and a fantastic user experience. This scenario only works well with data processing in real-time at scale. This blog post shares a presentation that explains why Apache Kafka plays a key role not just in one of these industries or use cases, but also to connect the different stakeholders to each other.
A smart city is an urban area that uses different types of electronic Internet of Things (IoT) sensors to collect data and then use insights gained from that data to manage assets, resources, and services efficiently. This blog post explores how Apache Kafka fits into the smart city architecture and the benefits and use cases.
Event Streaming with Apache Kafka disrupts the retail industry. Walmart’s real-time inventory system and Target’s omnichannel distribution and logistics are two great examples. This blog post explores a key use case for postmodern retail companies: Real-time omnichannel retail and customer 360.
This blog post explores an infrastructure checklist to build an open, flexible, and scalable event streaming architecture with Apache Kafka at the edge outside data centers.
Event Streaming with Apache Kafka disrupts the retail industry. This blog post explores a concrete use case as part of the overall story: A hybrid streaming architecture to build smart retail stores for autonomous or disconnected edge computing and replication to the cloud with Apache Kafka.