Kafka

Back-end & Platform Engineering Technology Enabler

Apache Kafka is an open-source distributed streaming platform designed for the management of data flows in real time that guarantees reliability and scalability. Used by leading companies for the collection, transformation and distribution of data, Kafka allows large volumes of data to be managed between different systems.

Since 2018, Bitrock has been training and certifying its staff on Apache Kafka, developing a solid expertise in the technology. We are able to assist companies in the design, implementation and management of optimized Kafka solutions, adapted to every type of need.

OVERVIEW

Apache Kafka is a distributed platform designed to manage data flows in real time. Its architecture is based on a distributed commit log, where data is organized into “topics” and subdivided into “partitions”. This structure allows for parallel and efficient data processing. Furthermore, Kafka stores data persistently, allowing already processed streams to be re-read and processed.

The main advantages of Apache Kafka include:

Scalability: Kafka can handle increasing volumes of data by distributing the load over multiple nodes, maintaining high performance.
Low latency: It guarantees rapid transmission of messages, making it suitable for applications that require real-time processing.
High reliability: Data replication across different brokers ensures continuity of service even in the event of hardware or network failures.
Flexibility and extensibility: thanks to a vast ecosystem of tools and connectors, such as Kafka Streams and Kafka Connect, it can be easily integrated with other technologies, facilitating the implementation of complete solutions.

These characteristics make Apache Kafka an excellent choice for building scalable, reliable and real-time data pipelines.

solutions

Apache Kafka offers several flexible solutions for working with real-time data streams:

Kafka Streams is a library for processing real-time data streams within Java applications. It simplifies the processing of streaming data, allowing you to create event-driven applications, analyze data in real time and build complex data pipelines.
Kafka Connect is a framework for scalable and reliable integration between Apache Kafka and other systems. It can be used to import data from various sources into Kafka or export data from Kafka to other systems in order to facilitate integration with external systems, such as databases and legacy applications.

Kafka Streams and Kafka Connect are used in numerous sectors and are key tools for:

Real-time analytics: provide immediate information on data in motion such as user behavior, system performance or financial transactions.
Event-Driven Architectures: build reactive and dynamic event-based architectures, where applications react in real time to data changes.
Data Pipelines: transform, filter and aggregate data from different sources in real time.
Monitoring and Log Aggregation: centralize and analyze logs from different applications.
Machine Learning: feed machine learning models with streaming data.

use cases

In today’s technological landscape, real-time data processing has become a fundamental requirement for companies operating in critical sectors such as finance. Apache Kafka, thanks to its distributed and scalable architecture, has established itself as the leading solution for high-speed data stream management.

BANKING SECTOR

A typical use case involves the implementation of Kafka-based transaction monitoring systems to analyze millions of daily transactions. These systems examine parameters such as the geolocation of transactions, their frequency, their amounts and the merchants involved. When an anomalous pattern is detected, such as a transaction made in a country other than the customer’s country of residence a few minutes after another local transaction, the system automatically generates an alert and can activate preventive measures such as temporarily blocking the card.

INTERNATIONAL PAYMENTS

Kafka is used to detect money laundering activities. The systems implemented track the flow of money between different accounts and jurisdictions in real time, identifying suspicious patterns such as layering (the practice of carrying out multiple transactions to mask the origin of the funds) by analyzing the sequence and nature of the transactions over a few milliseconds.

FINANCIAL TRADING

Kafka supports fraud prevention by monitoring thousands of transactions per second to identify patterns of market manipulation such as “spoofing” (the insertion of fictitious orders to influence the price of an asset). The systems analyze parameters such as order volume, size and timing in real time, generating immediate alerts when they detect potentially manipulative behavior.

INSURANCE SECTOR

Kafka is used to prevent fraud on claims through systems that collect and analyze data from connected vehicles, road cameras and IoT sensors in real time. In the event of a claim, these systems instantly verify the consistency between the declared data and the data actually recorded, identifying potential inconsistencies that could indicate fraud.