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.
Apache Kafka is the central nervous system of many applications in various areas related to the automotive and manufacturing industry for processing analytical and transactional data in motion across edge, hybrid, and multi-cloud deployments. This article explores the event streaming landscape for automotive including connected vehicles, smart manufacturing, supply chain optimization, aftersales, mobility services, and innovative new business models.
Apache Kafka is the de facto standard for event streaming to process data in motion. This blog post explores when NOT to use Apache Kafka. What use cases are not a good fit for Kafka? What limitations does Kafka have? How to qualify Kafka out as it is not the right tool for the job?
Live commerce combines instant purchasing of a featured product and audience participation. This blog post explores the need for real-time data streaming with Apache Kafka between applications to enable live commerce across online stores and brick & mortar stores across regions, countries, and continents in any retail business. The discussion covers several buildings blocks of a live commerce enterprise architecture, including transactional data processing, omnichannel, natural language processing, augmented reality, edge computing, and more.
Natural Language Processing (NLP) helps many projects in the real world for service desk automation, customer conversation with a chatbot, content moderation in social networks, and many other use cases. Learn how event streaming with Apache Kafka is used in conjunction with Machine Learning platforms at the carmaker BMW, the online travel and booking portal Expedia, and the dating app Tinder for reliable real-time conversational AI, NLP, and chatbots.
Apache Kafka and Event Streaming are two of the most relevant buzzwords in tech these days. Ever wonder what my predicted TOP 5 Event Streaming Architectures and Use Cases for 2022 are to set data in motion? Check out the following presentation. Learn about the Kappa architecture, hyper-personalized omnichannel, multi-cloud deployments, edge analytics, and real-time cybersecurity.
This blog post explores how event streaming with Apache Kafka enables IoT analytics for cost savings, better consumer experience, and reduced risk in real estate and smart buildings. Examples include improved real estate maintenance and operations, smarter energy consumptions, optimized space usage, better employee experience, and better defense against cyber attacks.
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.
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.
The manufacturing industry is moving away from just selling machinery, devices, and other hardware. Software and services increase revenue and margins. Equipment-as-a-Service (EaaS) even outsources the maintenance to the vendor. This paradigm shift is only possible with reliable and scalable real-time data processing leveraging an event streaming platform such as Apache Kafka. This post explores how Kafka-native Condition Monitoring and Predictive Maintenance help with this innovation.