Data Mesh is a new architecture paradigm that gets a lot of buzzes these days. This blog post looks into this principle deeper to explore why no single technology is the perfect fit to build a Data Mesh. Examples show why an open and scalable decentralized real-time platform like Apache Kafka is often the heart of the Data Mesh infrastructure, complemented by many other data platforms to solve business problems.
The public sector includes many different areas. Some groups leverage cutting-edge technology, like military leverage. Others like the public administration are years or even decades behind. This blog series explores both edges to show how data in motion powered by Apache Kafka adds value for innovative new applications and modernizing legacy IT infrastructures. This is part 2: Use cases and architectures for a Smart City.
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.
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.
Event Streaming with Apache Kafka and API Management / API Gateway solutions (Apigee, Mulesoft Anypoint, Kong, TIBCO Mashery,…
A digital twin is a virtual representation of something else. This can be a physical thing, process or…
Live Demo – 100.000 Connected Cars – Real Time Processing and Analytics with Kubernetes, Kafka, MQTT and TensorFlow leveraging Confluent and HiveMQ.
Data integration and processing in Industrial IoT (IIoT, aka Industry 4.0 or Automation Industry). Apache Kafka, its ecosystem (Kafka Connect, KSQL) and Apache PLC4X are a great open source choice to implement this integration end to end in a scalable, reliable and flexible way.
KSQL UDF for sensor analytics. Leverages the new API features of KSQL to build UDF / UDAF functions easily with Java to do continuous stream processing with Apache Kafka. Use Case: Connected Cars – Real Time Streaming Analytics using Deep Learning.