Author: Kai Waehner
Using Apache Flink® for Model Inference: A Guide for Real-Time AI Applications
Learn how Flink enables developers to connect real-time data to external models through remote inference, enabling seamless coordination between data processing and AI/ML workflows.
Unlock the Power of Data Streaming: Introducing The Ultimate Guide
Discover how to unlock the full potential of data streaming with Confluent's "Ultimate Data Streaming Guide." This comprehensive resource maps the journey to becoming a Data Streaming Organization (DSO), with best practices, industry success stories, & insights to scale your data streaming strategy.
Unlocking Industry 4.0: Rise of Smart Factory with Data Streaming
In the era of Industry 4.0, the fusion of smart, autonomous systems with digitization is propelling manufacturing and supply chain operations into uncharted efficiency. Industry 4.0, otherwise known as the Fourth Industrial Revolution, marks the normalization of the smart factory.
Real-Time Gaming Infrastructure for Millions of Users with Apache Kafka, ksqlDB, and WebSockets
The global video game market is bigger than the music and film industry combined. It includes Triple-A, casual/mid-core, mobile, and multiplayer online games. Various business models exist, such as hardware […]
Apache Kafka and SAP Integration with the Kafka Connect ODP Source Connector
SAP is a German multinational software corporation that develops and markets enterprise software to manage business operations and customer relations. SAP is most famous for its enterprise resource planning (ERP) […]
Use Cases and Architectures for HTTP and REST APIs with Apache Kafka
This blog post presents the use cases and architectures of REST APIs and Confluent REST Proxy, and explores a new management API and improved integrations into Confluent Server and Confluent […]
Apache Kafka Native MQTT at Scale with Confluent Cloud and Waterstream
With billions of Internet of Things (IoT) devices, achieving real-time interoperability has become a major challenge. Together, Confluent, Waterstream, and MQTT are accelerating Industry 4.0 with new Industrial IoT (IIoT) […]
Streaming Machine Learning with Tiered Storage and Without a Data Lake
The combination of streaming machine learning (ML) and Confluent Tiered Storage enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache […]
Machine Learning and Real-Time Analytics in Apache Kafka Applications
The relationship between Apache Kafka® and machine learning (ML) is an interesting one that I’ve written about quite a bit in How to Build and Deploy Scalable Machine Learning in […]
Internet of Things (IoT) and Event Streaming at Scale with Apache Kafka and MQTT
The Internet of Things (IoT) is getting more and more traction as valuable use cases come to light. A key challenge, however, is integrating devices and machines to process the […]
Real-Time Analytics and Monitoring Dashboards with Apache Kafka and Rockset
In the early days, many companies simply used Apache Kafka® for data ingestion into Hadoop or another data lake. However, Apache Kafka is more than just messaging. The significant difference […]
Microservices, Apache Kafka, and Domain-Driven Design
Microservices have a symbiotic relationship with domain-driven design (DDD)—a design approach where the business domain is carefully modeled in software and evolved over time, independently of the plumbing that makes […]
Machine Learning with Python, Jupyter, KSQL and TensorFlow
Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine […]
Using Apache Kafka to Drive Cutting-Edge Machine Learning
Machine learning and the Apache Kafka® ecosystem are a great combination for training and deploying analytic models at scale. I had previously discussed potential use cases and architectures for machine […]