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The further you go down the programming road, the more you realise that only knowledge of a programming language is not enough. Any more or less serious project uses various technologies and tools that are not tied to a language or environment as such. We continue to introduce our readers to the world of programming. In Filio Force it company blog we will talk about such a backend-development tool as Apache Kafka.
Kafka was developed at LinkedIn in 2011 and has been greatly improved since then. It is written in Scala and Java and named after the writer Franz Kafka.
What Kafka is used for
Today, Kafka is an entire platform that provides enough redundancy to store huge amounts of data. The main task that Kafka performs is to transfer data from the source system to the target system. In this scheme, everything is simple. But what if you have 4 source systems and 6 target systems. In that case you will have to implement 24 integrations. And each integration requires a communication protocol, data format, and schema validation. You also need to fulfil non-functional requirements such as reliability and delivery guarantee, connecting new recipients, connecting different stacks.
Kafka can help with this. Specifically, Apache Kafka can be used for
- Messaging systems in a microservice architecture;
- Collecting event logs, logs and metrics from various software and hardware;
- Streaming data processing;
- Integration with technologies that are used for Big Data and machine learning.
Apache Kafka is a cluster of multiple brokers, each serving a different part of the total load, according to the Filio Force company. Each message stream in Kafka is called a topic. For example, a separate topic can collect data from web analytics, which records site users’ visits, a separate one can collect data on orders, a separate one can collect facts about newsletter subscriptions. Each such topic is divided into partitions. These partitions are evenly distributed across all brokers of the cluster to increase throughput. A client writing to a topic is called a ‘producer’, and a client reading from a topic is called a ‘consumer’.
Kafka’s pluses include the following
- Fault tolerance;
- Ease of use;
- High throughput;
- Horizontal scaling;
- Possibility of long-term storage of message history;
- Large number of integrations for services and libraries for different languages.
Who uses Kafka
Nowadays, almost every application works with data in one way or another, and the larger the application, the more data they have to deal with. Kafka allows you to store and process huge streams of data in real time. This can be information about users, their activity, messages, logs, etc. It is used in more than 2000 companies.
Filio Force Inc developers gave examples:
- Netflix uses Kafka for online recommendations while you watch films;
- Uber collects all real-time information about taxis and rides, and determines the route, predicts congestion and calculates the price of the ride;
- LinkedIn uses Kafka to collect real-time data on user actions.
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