국내 No.1 에너지 IT기업 ‘해줌’의 컨플루언트 클라우드 도입 스토리 | 알아보고 등록하기

Confluent Announces General Availability of Confluent Cloud for Apache Flink®, Simplifying Stream Processing to Power Next-Gen Apps

Confluent Cloud for Apache Flink®, a leading cloud-native, serverless Flink service is now available on AWS, Google Cloud, and Microsoft Azure

Confluent’s fully managed, cloud-native service for Flink helps customers build high-quality data streams for data pipelines, real-time applications, and analytics

London, UK – March 19, 2024 – Confluent, Inc. (NASDAQ:CFLT), the data streaming pioneer, announced the general availability of Confluent Cloud for Apache Flink®, a fully managed service for Apache Flink® that enables customers to process data in real time and create high-quality, reusable data streams. Confluent Cloud for Apache Flink® is available across Amazon Web Services (AWS), Google Cloud, and Microsoft Azure. Backed by Confluent’s 99.99% uptime SLA, Confluent’s cloud-native service for Flink enables reliable, serverless stream processing.

Organizations are under incredible pressure to deliver exceptional customer experiences and streamline operations with cutting-edge use cases like fraud detection, predictive maintenance, and real-time inventory and supply chain management. Stream processing is a critical part of bringing these real-time experiences to life because it enables organizations to act on data as it arrives rather than waiting to process it in batches when the data is often already stale and out of date.

As the compute layer in the data streaming infrastructure, stream processing helps teams filter, join, and enrich data in real time to make it more usable and valuable for sharing with downstream applications and systems. It creates high-quality data streams that can be reused for multiple projects and provides improved agility, data consistency, and cost savings compared to traditional batch processing solutions. As the de facto stream processing standard, Flink is relied upon by innovative companies like Airbnb, Uber, Netflix, and Stripe to support mission-critical streaming workloads. That is what sparked the surge in Flink’s popularity. In 2023, Flink was downloaded almost one million times.

"Stream processing is essential for extracting timely insights from continuous data streams to power a wide range of critical use cases including fraud detection, dynamic pricing, and real-time inventory and supply chain management,” said Stewart Bond, research VP, data integration and data intelligence software at IDC. “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.”

As a leading cloud-native, serverless Flink offering, Confluent Cloud for Apache Flink® enables customers to easily build high-quality, reusable data streams to power all of their real-time applications and analytics needs.

“Stream processing allows organizations to transform raw streams of data into powerful insights,” said Shaun Clowes, chief product officer at Confluent. “Flink’s high performance, low latency, and strong community make it the best choice for developers to use for stream processing. With Kafka and Flink fully integrated in a unified platform, Confluent removes the technical barriers and provides the necessary tools so organizations can focus on innovating instead of infrastructure management.”

With Confluent Cloud for Apache Flink®, customers can:

  • Effortlessly filter, join, and enrich data streams with Flink, the de facto standard for stream processing
  • Enable high-performance and efficient stream processing at any scale, without the complexities of infrastructure management
  • Experience Kafka and Flink as a unified platform, with fully integrated monitoring, security, and governance

"Conditions in the automotive logistics industry can change rapidly, requiring immediate action to address delays, reroute vehicles, and update systems and customers," said Jeffrey Jennings, sr. consultant, data and integration services at ACERTUS. "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."

"To meet rising customer demands in a volatile energy market, we need to deliver near real-time data to our client-facing applications,” said Sami AlAshabi, solutions architect at Essent. “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.”

Apache Flink powers real-time use cases and next-generation experiences

Flink powers the real-time use cases customers demand. Flink enables customers to build streaming data pipelines, event-driven applications, and real-time analytics to power use cases like personalized recommendations, dynamic pricing, and anomaly detection. Confluent Cloud for Apache Flink® is an easy way for companies to get started with these stream processing use cases.

Easier AI development with streaming data pipelines

Streaming data pipelines supply real-time data to critical data systems across an organization, including data warehouses, databases, and data lakes, to ensure they always reflect the current state of the business. As generative AI becomes a top priority for many companies, vector databases are another data system that must be continuously updated with timely and well-curated data from streaming data pipelines.

If the data in a vector database becomes stale or low fidelity because of pipelines that rely on periodic batch processing and public datasets, the reliability and relevance of generative AI diminishes. Flink can be used to create streaming data pipelines to ensure vector databases are supplied with cleaned, business-contextualized, real-time data to support generative AI applications.

Confluent Cloud for Apache Flink® enables users to build streaming data pipelines for vector databases with ease, ensuring generative AI applications have access to their organization’s most relevant and valuable data in real time. Confluent integrates with leading vector database vendors, such as Elastic, Pinecone, Rockset, SingleStore, and Zilliz to further simplify and accelerate the development of critical generative AI initiatives even further.

More accurate real-time alerts for event-driven applications

Flink can analyze streams of data and immediately trigger an alert when a particular event or pattern happens in event-driven applications. Time is often a critical part of this equation, and Flink offers advanced windowing capabilities that give customers control over how data is grouped for processing — for example, analyzing transactions over a specific time period for anomalies.

With Confluent Cloud for Apache Flink®, customers can build next-gen event-driven applications that can analyze transaction data and trigger alerts for faster fraud detection or help stores better manage their inventory and share accurate delivery times.

Faster decisions for real-time analytics

Unlike its batch counterparts, Flink can analyze real-time data streams to generate insights and help businesses accelerate decision-making. Flink can process massive amounts of data quickly with low, sub-second latency, interactive queries, and advanced pattern recognition functions.

Confluent Cloud for Apache Flink® can manage and process billions of data points for timely movie, show, and music recommendations and provide up-to-date information on order volumes, popular menu items, and delivery times for food delivery.

Confluent Cloud for Apache Flink® is now generally available on all three major cloud service providers. Customers can sign up for Confluent Cloud to easily access Confluent’s fully managed offering for Flink. To help customers quickly build and deploy Flink applications, Confluent has a global network of system integrators, including Deloitte, Ness Digital Engineering, Somerford Associates, Improving, Psyncopate, Platformatory, Synthesis Software Technologies (Pty) Ltd and iLink Digital. These system integrators can provide on-site engineering assistance and technical support to help customers accelerate their stream processing use cases.

Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion — designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.

Confluent and associated marks are trademarks or registered trademarks of Confluent, Inc.