How can real-time data be made available in the cloud without migrating complex systems?
Apache Kafka: Real-Time Data Replication
Today I want to talk about an alternative for making data from legacy systems available to cloud applications without requiring a complete migration. The idea is to allow companies to benefit from the scalability and cost reduction offered by the cloud without the risks associated with a complex migration.
I am referring to the use of Change Data Capture (CDC) combined with data streaming technologies such as Apache Kafka, enabling real-time data replication without impacting on-premises systems.
This approach allows new applications to consume continuously updated data without relying directly on the traditional integration layer.
The need
In a project carried out for a large Chilean financial cooperative, a common challenge emerged: supporting multiple digital channels with an architecture that was not designed to scale at that level.
The integration layer based on a service bus began to suffer from traffic spikes, resulting in instability and high operational costs.
The initial solution was to replicate data through batch processes (ETL), but this did not meet the real-time data requirements expected by users.
It was at this point that streaming with CDC became a viable solution.
A modern and scalable solution
CDC enables the capture of changes (insert, update, delete) directly from database logs in a non-intrusive manner.
These events are transformed into open formats (such as JSON) and sent to a streaming platform.
Apache Kafka stands out for providing high scalability, flexibility, and near real-time processing capabilities.
With this architecture, data is processed, transformed, and distributed to cloud databases with minimal latency.
Challenges
Despite its benefits, this approach brings important challenges:
- Paradigm shift: moving from relational models to event-driven systems;
- Data modeling: aligning legacy structures with new models;
- Legacy knowledge: older systems are often poorly documented;
- Exception handling: dealing with inconsistencies and failures;
- Monitoring: the need for real-time observability.
Benefits
- Real-time data: applications always have access to up-to-date information;
- Reduced legacy load: less pressure on on-premises systems;
- Scalability: distributed processing in the cloud;
- Innovation: a foundation for analytics, AI, and fraud detection;
- Agility: faster development of new applications.
Learn more
If you are interested in this approach, it is essential to have a well-defined strategy and an experienced team.
Schedule an initial conversation with TruStep. We can review your current scenario, understand existing dependencies, and discuss paths for a gradual modernization, while keeping operations running during the transition.
