The Apache Kafka® Control Plane – ZooKeeper vs. KRaft

preview_player
Показать описание

In this tutorial, you'll learn about the Kafka Control Plane, which simplifies Kafka's architecture by removing its ZooKeeper dependency, allowing you to run Kafka in its entirety as a single system.

Jun Rao (Kafka Committer, PMC Member, VP of Kafka, and Co-Founder, Confluent) explains why this is significant, including its impact on the scalability of Kafka to support millions of topics/partitions in one cluster, the getting started and operational experience, configuration, and controller logic. Learn how the Kafka control plane enables synchronicity between cluster members and cluster metadata, the difference between ZooKeeper and KRaft, and the mechanics of the KRaft consensus protocol.

LEARN MORE

ABOUT CONFLUENT

#streamprocessing #apachekafka #kafka #confluent
  1. Confluent
  2. apache kafka
  3. kafka
  4. open source
  5. confluent
  6. data in motion
Рекомендации по теме
The Apache Kafka® 0:12:03

The Apache Kafka® Control Plane – ZooKeeper vs. KRaft

Building and Scaling 0:39:46

Building and Scaling a Control Plane for 1000s of Kafka Clusters

Data Plane – 0:11:31

Data Plane – Apache Kafka®'s Replication Protocol

Apache Kafka® Brokers: 0:08:06

Apache Kafka® Brokers: Introduction to the Data Plane

Apache Kafka® Architecture: 0:08:29

Apache Kafka® Architecture: Overview of Kafka's Internal Components

Kafka without Zookeeper 1:03:00

Kafka without Zookeeper | Kraft | KIP-500 | Apache Kafka Series - Part 09

Confluent Cloud Components 0:06:42

Confluent Cloud Components and Services

Scaling Apache Kafka 0:49:08

Scaling Apache Kafka Clusters on Confluent Cloud ft. Ajit Yagaty and Aashish Kohli

A Needle in 0:29:46

A Needle in a Haystack How to Find a Threat Hidden in Over 6 Billion Logs Per Day

Optimizing Apache Kafka's 0:48:55

Optimizing Apache Kafka's Internals with Its Original Co-Creator Jun Rao

Apache Kafka 101: 0:04:23

Apache Kafka 101: Partitioning (2023)

Lessons Learned From 0:28:21

Lessons Learned From Designing Serverless Apache Kafka ft. Prachetaa Raghavan

Building Confluent Cloud 0:40:55

Building Confluent Cloud with Frank Greco Jr., Confluent | Bay Area Apache Kafka® Meetup

Demo: Confluent for 0:07:10

Demo: Confluent for Kubernetes

Kubernetes Explained in 0:06:28

Kubernetes Explained in 6 Minutes | k8s Architecture

Configuring Apache Kafka® 0:08:59

Configuring Apache Kafka® Durability, Availability, and Ordering Guarantees

Using Apache Kafka 0:33:57

Using Apache Kafka as Cloud-Native Data System ft. Gwen Shapira

Apache Kafka Architecture 0:11:19

Apache Kafka Architecture

Cloudifying Apache Kafka 0:02:35

Cloudifying Apache Kafka with Confluent Cloud

Automating Multi-Cloud Apache 0:48:30

Automating Multi-Cloud Apache Kafka Cluster Rollouts

Apache Kafka UI 0:33:23

Apache Kafka UI Tools Overview ( Conduktor, Control Center, Kafdrop)

Stream Processing with 1:45:43

Stream Processing with Apache Kafka, Samza, and Flink (April 2022)

Using Kafka-Leader-Election to 0:51:07

Using Kafka-Leader-Election to Improve Scalability and Performance

Jun Rao, Confluent 0:37:17

Jun Rao, Confluent - Kafka Controller: A Deep Dive | Bay Area Apache Kafka® Meetup

Комментарии
Автор

sir is KRaft is mature for production for real projects??

BishalKarki-pehs
Автор

A query i have. During leader election, when 2 out of 3 replicas are available to vote, if both are having same offset means both are in sync with dead controlled, how it is decided which one to make as leader ?

abhishekjain