Why Kafka is used in Microservices: The goal of Apache Kafka is to solve the scaling and reliability issues that hold older messaging queues back. A Kafka-centric microservice architecture uses an application setup where microservices communicate with each other using Kafka as an intermediary.
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What problems does Kafka solve?Kafka takes on the burden of handling all the problems related to distributed computing: node failures, replication or ensuring data integrity. It makes Kafka a great candidate for the fundamental piece of architecture, a central log that can serve as a source of truth for other services.
Does Kafka 3.1 need ZooKeeper?
Apache Kafka Needs No Keeper: Removing the Apache ZooKeeper Dependency. Currently, Apache Kafka® uses Apache ZooKeeper™ to store its metadata. Data such as the location of partitions and the configuration of topics are stored outside of Kafka itself, in a separate ZooKeeper cluster.
What happens if ZooKeeper goes down in Kafka?
If Zookeeper is down while all of this happens, broker ISR list becomes inaccurate. In theory, as long as no changes occur on the brokers and as long as all the brokers are alive, clients will have NO impact while administrators work on bringing up the Zk quorum.
Is ZooKeeper necessary for Kafka?
In Kafka architecture, Zookeeper serves as a centralized controller for managing all the metadata information about Kafka producers, brokers, and consumers. However, you can install and run Kafka without Zookeeper.
A zookeeper, sometimes referred as animal keeper, is a person who manages zoo animals that are kept in captivity for conservation or to be displayed to the public. They are usually responsible for the feeding and daily care of the animals.
A Kafka broker allows consumers to fetch messages by topic, partition and offset. Kafka brokers can create a Kafka cluster by sharing information between each other directly or indirectly using Zookeeper. A Kafka cluster has exactly one broker that acts as the Controller.
Currently, Apache Kafka® uses Apache ZooKeeper™ to store its metadata. Data such as the location of partitions and the configuration of topics are stored outside of Kafka itself, in a separate ZooKeeper cluster. In 2019, we outlined a plan to break this dependency and bring metadata management into Kafka itself.
Kafka was designed to deliver these distinct advantages over AMQP, JMS, etc.
- Kafka is highly scalable. Kafka is a distributed system, which is able to be scaled quickly and easily without incurring any downtime.
- Kafka is highly durable.
- Kafka is Highly Reliable.
- Kafka Offers High Performance.
The original use case for Kafka was to be able to rebuild a user activity tracking pipeline as a set of real-time publish-subscribe feeds. This means site activity (page views, searches, or other actions users may take) is published to central topics with one topic per activity type.
Kafka is primarily used to build real-time streaming data pipelines and applications that adapt to the data streams. It combines messaging, storage, and stream processing to allow storage and analysis of both historical and real-time data.
Kafka is Highly Reliable.
Kafka replicates data and is able to support multiple subscribers. Additionally, it automatically balances consumers in the event of failure. That means that it's more reliable than similar messaging services available.
Introduction. Apache Kafka 2.8. 0 is finally out and you can now have early-access to KIP-500 that removes the Apache Zookeeper dependency.