Accenture enables real-time response at scale for an Australian federal agency

As digital interactions increased in volume and complexity, an Australian federal agency faced challenges in accessing operational data from legacy mainframe systems, limiting how quickly it could respond to critical events. To address this, Accenture designed and delivered a data replication capability on Amazon Web Services (AWS), creating a scalable foundation for continuous data access across systems. Today, the platform processes over 22 billion data records.

For an Australian federal agency delivering a wide range of digital services, responding to time-sensitive events depends on timely access to operational data. As digital interactions increased in volume and complexity, the agency faced growing challenges in acting on data as changes occurred.

Working closely as a partner to the agency, Accenture saw that much of this data remained tied to legacy mainframe systems and was processed in batch cycles, limiting visibility across systems and slowing response times. This constrained the agency’s ability to support low-latency use cases such as real-time alerts and user notifications, while tightly coupled systems reduced flexibility as digital services continued to expand.

To address this, operational data needed to be more accessible beyond the mainframe environment. This required establishing continuous data synchronization, enabling event-driven data consumption, and creating a scalable foundation to support microservices-ready architectures while maintaining performance, reliability, and security. 

Accenture led the solution strategy, architecture design, and end-to-end delivery of a data replication capability to reduce reliance on batch-based processing. The approach established a scalable and secure data foundation that continuously synchronizes data between legacy mainframe systems and a cloud-based environment. Sagar Anand, managing director at Accenture, says, “Establishing real-time access to mainframe data was critical to moving from reactive operations to a more proactive model. Designing this as an enterprise capability created a foundation for multiple use cases across the agency.”

At the core of the solution is a data replication layer that captures and streams changes from mainframe systems into a cloud data platform on AWS. This enables low-latency data propagation, with changes processed within seconds to support time-sensitive use cases.

Replicated data is made available through an event-driven design, allowing downstream applications to consume data in real time across analytics and operational systems. This supports a shift toward domain-driven, microservices-ready architectures while reducing dependency on tightly coupled legacy systems. “Real-time data replication was fundamental to decoupling legacy systems and supporting an event-driven architecture while maintaining performance at scale,” adds Anand.

The architecture uses Amazon Aurora as the cloud data store and Amazon Kinesis Data Streams for real-time streaming. Amazon Simple Storage Service and Amazon Data Firehose support data ingestion and storage, while AWS Lambda supports processing and business logic. These services support scalable, secure integration across systems.

Accenture coordinated a multi-vendor delivery model, working closely with AWS to implement the solution. AWS supported architecture validation, performance optimization, and load testing to ensure the platform could handle large-scale data volumes and real-time processing requirements.

The implementation of the data replication capability marked a shift toward real-time access and use of data across systems. With improved visibility into data changes, the agency can respond more quickly to time-sensitive events, enhancing response across its digital services.

Since implementation, the platform is operating at scale, “By making data available as events occur, the Australian federal agency can respond in the moment rather than after the fact. This has been critical in improving response and reducing potential impact,” says Sagar Anand.

The architecture continues to process large volumes of data in real time, with more than 22 billion rows replicated from mainframe systems into AWS and synchronized continuously across environments. This provides a consistent and up-to-date view of data across applications.

Operationally, the shift away from batch-based processing has reduced dependency on tightly coupled legacy systems and lowered the load on mainframe infrastructure over time. At the same time, the architecture provides a scalable foundation to support additional use cases across analytics and operational systems. Anand adds, “This establishes a strong foundation for future capabilities, where data can support more advanced monitoring, decisioning, and data-driven services across the agency.”

Accenture is a global professional services company specializing in digital, cloud, and security. It combines deep industry expertise with advanced technology capabilities to help organizations transform operations and deliver value at scale.