Event Streaming in 3 Minutes
https://cnfl.io/event-streams-and-des... | What is event streaming? Danica Fine (Staff Developer Advocate, Confluent) explains the basics—from an event to an event stream to event stream processing, and how it works.
Event streaming is a sequence of continuous data points that originate from Apache Kafka®, the de facto distributed system for brokering messages in highly available environments. Data points could also stem from the physical world if a measuring tool is present, for example, a temperature reading sent by a jet engine sensor could be an event. Each data point from a system is referred to as an event—a fundamental unit for stream processing. Events have a repeating and evolving nature, hence the ongoing delivery of events is referred to as a stream. Event stream processing (ESP) is when we combine streams of data together for real-time data delivery, which opens new capabilities like real-time data processing and analytics. This is where the true power of event streaming lies.
LEARN MORE
► Designing Events and Event Streams: https://cnfl.io/event-streams-and-des...
► Event Sourcing course: https://cnfl.io/event-sourcing-fundam...
► Kafka Streams course: https://cnfl.io/kafka-streams-introdu...
► Learn Apache Kafka with Tutorials: https://cnfl.io/confluent-developer-w...
► Join the Confluent Developer Community: https://cnfl.io/join-community-what-i...
ABOUT CONFLUENT
Confluent is pioneering a fundamentally new category of data infrastructure focused on 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.
#streamprocessing #kafkastreams #apachekafka #kafka #confluent
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