Shannon Retail Park, Dublin Rd, Athlone, Co. Westmeath, N37 E2P6
sales@zinkworks.com
Enhancing Data Integration and Processing with Kafka Connect and Kafka Streams
OVERVIEW
Zinkworks played a pivotal role in developing and implementing Amdocs Network Data Fabric (NDF).
Leveraging our expertise in advanced data processing technologies, we ensured seamless integration of diverse data sources and legacy platforms, guaranteeing no data loss during downstream delivery, even with the rapid growth of IoT devices generating non-standard data formats. We focused on making the solution highly extensible for easy addition of new integrations, efficiently processing large volumes of data, and supporting feature tuning for optimal configurations.
Engagement Model
Staff Augmentation
Technologies Used
Kafka, Java, Kubernetes, Docker, Python, Jenkins, Jira
Team Size
0
Engineers
Engagement Timeframe
0
Years
THE CHALLENGE
Clients frequently have their data sources modelled in different ways. They have multiple data sources/origins, which often communicate with a diverse number of legacy platforms to produce their output data.
With the rapid growth of IoT devices that are constantly producing data (not in a standard format), We would need to develop a solution that was reliable and that would guarantee no data loss when delivering this data downstream.
Solution
Zinkworks selected Kafka Connect and Kafka Streams as the foundational technologies due to their robust capabilities in integrating new data sources, processing, and sink connectors while maintaining the distributed nature of the product.
These open-source components of Apache Kafka provide a comprehensive framework for connecting Kafka with external systems such as databases, key-value stores, search indexes, and file systems.
BENEFITS
Kafka Connect and Kafka Streams provide robust solutions for data integration and processing.
Kafka Connect offers a flexible, scalable data-centric pipeline that efficiently handles both streaming and batch systems, leveraging existing connectors to reduce time to production. Kafka Streams enhances data transfer with state management, flexibility, and scalability, using meaningful data abstractions and extending existing data processors for efficient, tailored processing.
Proof of value
Improved Data Integration
Seamless integration of diverse data sources, including legacy systems and IoT devices, ensuring consistent and reliable data flow.
Enhanced Scalability
Ability to scale from single-node deployments to organization-wide services, accommodating growing data volumes and processing needs.
Flexibility and Customization
Support for feature tuning, allowing customers to configure the system to their specific requirements, including resource limitations, logging, and monitoring
Resilience and Reliability
Robust handling of network disruptions, ensuring no data loss and maintaining continuous data flow.
“Over the past three years, our team at Zinkworks has had the privilege of collaborating closely with Amdocs. We have been deeply involved in delivering new features, resolving critical issues, and optimizing system performance using technologies such as Kafka, Kubernetes, and Java. Throughout this partnership, we’ve maintained a high level of professionalism and technical excellence, ensuring seamless communication and consistently meeting project goals. Our work with Amdocs has strengthened our expertise and ability to deliver quality software solutions, and we value this ongoing collaboration.”