₹1,499
₹3,099
51% OffHurry Up, Shop Now!
0H:0M:0S
Final Price inclusive of all taxes
Cash on Delivery
Free Delivery
Get it delivered in 3-6 days
size
17.78 x 2.54 x 22.86 cm
Product Information
Ideal For
General Readers, Fiction Lovers, Mythology & Historical Fiction Readers, Indian Mythology Enthusiasts, Young Adults (YA) & Adults, College Students, Competitive Exam Aspirants (General Reading / Culture), Gift Purpose (Books Gift Set), Spiritual & Philosophy Interest Readers, Library / Book Collection Buyers
Country Of Origin
India
About Author
Gwen Shapira Is A System Architect At Confluent Helping Customers Achieve Success With Their Apache Kafka Implementation. She Has 15 Years Of Experience Working With Code And Customers To Build Scalable Data Architectures, Integrating Relational And Big Data Technologies. She Currently Specializes In Building Real-Time Reliable Data Processing Pipelines Using Apache Kafka. Gwen Is An Oracle Ace Director, An Author Of "Hadoop Application Architectures", And A Frequent Presenter At Data Driven Conferences. Gwen Is Also A Committer On The Apache Kafka And Apache Sqoop Projects.
Author Name
Gwen Shapira
Genre
Programming & Software Development
No Of Pages
485
Publisher
O'Reilly Media, O'Reilly Media
Product Description
- Premium Quality: This updated hardcover edition spans 485 pages and serves as a comprehensive, authoritative reference on the Apache Kafka streaming platform.
- Product Design: Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages - and moving all this data is just as important as the data itself.
- User Experience: Application architects, developers, and production engineers new to the Kafka streaming platform will learn how to handle data in motion.
- Versatile Occasion: Additional chapters cover Kafka's AdminClient API, transactions, new security features, and tooling changes, ensuring the content reflects the latest developments in the platform.
- Ideal For: Designed for software professionals across experience levels who work with real-time data pipelines, distributed systems, and enterprise application architecture.