Not all workloads should go to the cloud! Low latency, cybersecurity, and cost-efficiency require a suitable combination of edge computing and cloud integration. This blog post explores hybrid data streaming with Apache Kafka anywhere. A live demo shows data synchronization from the edge to the public cloud across continents with Kafka on Hivecell edge hardware and serverless Confluent Cloud.
This post explores why Apache Kafka is the new black for integration projects, how Kafka fits into the discussion around cloud-native iPaaS solutions, and why event streaming is a new software category. A concrete real-world example shows the difference between event streaming and traditional integration platforms respectively iPaaS.
Apache Kafka became the central nervous system of many applications in various different areas related to the automotive industry. This blog post explores various real-world deployments across several fields including connected vehicles, smart manufacturing, and innovative mobility services. Examples include car makers such as Audi, BMW, Porsche, and Tesla, plus a few mobility services such as Uber, Lyft, and Here Technologies.
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.
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