간단한 서버리스 스트림 처리

"To meet rising customer demands in a volatile energy market, we need to deliver near real-time data to our client-facing applications. Relying on batch processing can cause performance issues and result in poor decision-making based on outdated data. By using Kafka and Flink together in a unified platform, our teams will be able to easily build intelligent streaming data pipelines that can extract data from various sources, process it in real time, and feed it to our downstream consumers for timely analysis without any operational challenges. We’re excited about Confluent’s fully managed Flink service, because it will help make stream processing accessible to everyone by creating high quality, reusable data streams to fuel innovation and data exploration across our lines of business.”

"Conditions in the automotive logistics industry can change rapidly, requiring immediate action to address delays, reroute vehicles, and update systems and customers. Confluent's serverless Flink service will enable us to instantly and efficiently transform, integrate, and enrich massive volumes of data in our transportation management system, providing real-time visibility into the status and location of vehicles for both systems and customers."

"Apache Flink is becoming a prominent stream processing framework in this shift towards real-time insights. Flink and Apache Kafka are commonly used together for real-time data processing, but differing data formats and inconsistent schemas can cause integration challenges and hinder the quality of streaming data for downstream systems and consumers. A fully managed, unified Kafka and Flink platform with integrated monitoring, security, and governance capabilities can provide organizations with a seamless and efficient way to ensure high-quality and consistent data streams to fuel real-time applications and use cases, while reducing operational burdens and costs."

"스트림 처리에는 이벤트 데이터 스트림의 실시간 통합 및 변환이 포함되며, 금융 분야의 사기 탐지부터 이커머스 분야의 맞춤형 추천에 이르기까지 다양한 산업 분야의 시스템을 지원합니다. Apache Flink와 Apache Kafka를 함께 사용하면 데이터 재사용성을 높이고 다운스트림 중복 처리를 방지할 수 있습니다. Flink와 Kafka를 완전 관리형 서비스로 제공하면 복잡한 인프라 관리 없이 스트림 처리가 가능하므로 팀에서는 비즈니스를 차별화하는 실시간 스트리밍 애플리케이션과 파이프라인 구축에 집중할 수 있습니다."