Radpoint – a system that supports the work of radiologists both in the area of work management and analysing examination results. It receives dozens of sensitive data every day, which must not only be secure, but also handled in real time.

Managing large volumes of data is a big challenge – especially in projects where security and speed of information processing play a key role. How does Apache Kafka effectively meet business needs for analytics and monitoring? We break it down – a solution that provides the foundation for scalable and secure solutions in big data projects.

Problem: Real-time management of large amounts of data ​

In companies working with large volumes of data, one of the most common challenges is the need to handle communication between microservices and process events and information in real time. In traditional systems, communication between modules often requires high bandwidth and high reliability.

For Radpoint, the problem was to transfer and log events between different services with minimal latency and to store and process data securely. The company needed a solution that would allow dynamic scaling while ensuring uninterrupted data availability even in the event of failure.

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Solution: Apache Kafka for large data flows ​

Apache Kafka offers a solution that is perfectly suited to handle large data flows with minimal latency. One of its key advantages is its high throughput and low latency, making it ideal for real-time applications that process huge amounts of data.

Apache Kafka acts as a distributed system for queuing and publishing messages, enabling seamless communication between systems. For Radpoint, this meant being able to monitor events and analyse them in real time, significantly increasing operational efficiency.

Scalability and reliability of Apache Kafka ​

Apache Kafka's distributed architecture enables horizontal scaling to handle increasing volumes of data without compromising on performance. The use of this solution at Radpoint has enabled incremental growth of processes and services, as well as the flexibility to adapt to dynamic business needs. Apache Kafka is also highly reliable, which is crucial for systems where downtime can generate financial and operational losses. Thanks to its replication and recovery mechanisms, a system based on this solution is resilient to failures, ensuring data stability and security.

Possibility of integration with various technologies ​

Apache Kafka supports a wide range of protocols and data systems, allowing it to integrate seamlessly with many technologies. This means that it can be easily deployed in companies with a variety of technological architectures.

For Radpoint, which uses a microservices architecture, Apache Kafka acted as a central 'message broker', enabling the efficient exchange of information between services and access to key data in real time. Integration with other technologies was key, as it enabled business processes to be tightly coupled with data from different sources.

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Stream processing in Apache Kafka, a real-time analytics tool ​

Apache Kafka enables stream processing, allowing companies to create event-based architectures and analyse data in real time. This provides Radpoint with the ability to monitor business processes and generate analytics on the fly.

The Kafka Stream API enables data to be processed directly in the stream, allowing the company to analyse large amounts of data without the need to store it in advance, significantly speeding up the decision-making process and enabling an immediate response to changing conditions.

Data security with Apache Kafka ​

Data security is a key component of any modern information processing system, particularly for companies operating in industries where data is particularly sensitive.

Apache Kafka offers a wide range of security features such as authentication, authorisation and data encryption, making data transfer secure at every stage of its processing.

The implementation of these safeguards has enabled Radpoint to meet the highest standards of information protection, as well as ensuring compliance with data privacy regulations.

Case study Radpoint ​

Radpoint's implementation of Apache Kafka was driven by the need for a highly scalable and reliable system to manage communications and monitor events. The company deployed the solution as a central 'message broker' in its microservices architecture, enabling efficient communication between services.

Apache Kafka was used to transfer events between services and record and monitor real-time analysis. This provided Radpoint with the confidence that the system was not only efficient, but also fault-tolerant, which was key to ensuring continuity of operations.

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Is Apache Kafka the key to secure and fast big data processing? ​

Apache Kafka is a comprehensive tool that offers scalability, high availability and data security, making it an excellent choice for companies working with large volumes of information. With its real-time data processing capabilities, integration with various technologies and strong security features, it supports companies in managing data more efficiently and securely.

For Radpoint, the implementation of Apache Kafka has provided greater flexibility and stability, enabling the company to better adapt to changing business needs and manage processes more efficiently.