Uploaded byconfluent
Introduction to Kafka Streams
Pooja Rallabhandi is a software engineer at Ticketmaster focused on web and stream-based applications, with a passion for women in technology. The document discusses the features and origins of Apache Kafka, a distributed streaming platform created at LinkedIn, highlighting its capabilities in data persistence, high throughput, and low latency for real-time decision making. Additionally, it includes links for downloads, quickstart guides, and resources related to Apache Kafka.
More Related Content
Similar to Introduction to Kafka Streams
![Support, Monitoring, Continuous Improvement & Scaling Agentic Automation [3/3]](https://cdn.slidesharecdn.com/ss_thumbnails/agenticcommunityseries-day3-cfd-251120170304-ddef8112-thumbnail.jpg?width=640&height=640&fit=bounds)
Introduction to Kafka Streams
- 1.
- 2. Pooja Rallabhandi § SoftwareEngineer @ Ticketmaster, Scottsdale § Work on Web and Stream based applications § Passionate about Women in Technology § LinkedIn : www.linkedin.com/in/poojaralla § Twitter: @pzralla Confluent CTO, Neha Narkhede @ Kafka Summit 2018
- 3. DATA STORE CLIENT A Create Concert CLIENTB Sell Inventory on Concert CLIENT C Create Inventory for Concert A P I G A T E W A Y Concert APIs INVENTORY APIs
- 4. Poor performance Increasein Dependencies Data Not Available Data Server Copyright © 2015 -2018 Confluent, Inc. All rights reserved
- 5. § A datalog that keeps track of changes as they happen § Maintains the order in which events occurred § Data is persisted in the log § Clean-up is configurable § An approach to reactive programming § Process data as it is being generated § Helps in real-time decision making Copyright © 2015 -2018 Confluent, Inc. All rights reserved
- 6. Features § Distributed streamingplatform § Data persistence § High throughput § Low Latency Origin § Created @ LinkedIn in 2010 § Open source, top-level Apache project since 2012 § Confluent provides an Enterprise version
- 7. § Messages asKey/Value pair § Topics § Partitions § Data Retention § Delete § Compact
- 8. CENTRALIZED DATA STORE Copyright ©LinkedIn. All rights reserved
- 9. Copyright © Ticketmaster.All rights reserved
- 10.
- 11.
- 12.
- 13. § Kafka streamscommit logs from a system into Topics § Uses pull based model § High throughput and low latency § KStreams API for data transformation § Kafka Connect for data transfer
- 15. § Download ApacheKafka: https://kafka.apache.org/downloads § Quickstart guide: https://kafka.apache.org/quickstart § Tutorials: https://www.tutorialspoint.com/apache_kafka/ https://docs.confluent.io/current/tutorials/index.html § Confluent published Use Cases and Resources https://www.confluent.io/resources/