88% Faster Data Processing with an AWS-native Pipeline

Aziro migrated to a retail, fintech, and digital payments enterprise's billing and balance data pipeline from Azure to an AWS-native architecture, replacing linear processing with parallel execution, automated orchestration, and fault tolerance. The migration cut processing time by 88% and manual intervention by up to 80%, transforming reliability and cost efficiency across enterprise data workflows.

As data volumes grew, the enterprise's Azure-based pipeline couldn't process billing and balance datasets fast enough to meet growing business needs, creating bottlenecks that delayed downstream business reporting significantly.

• Legacy Pipeline Migration: Needed to migrate the existing Azure and API-based data pipeline to AWS without disrupting billing operations or delaying ongoing balance reconciliation processes across teams.

• Linear Processing Bottlenecks: Billing and balance datasets in JSON format were processed sequentially, creating pipeline-wide performance bottlenecks that slowed processing and delayed downstream business reporting significantly.

• Scalability Gaps in Workflow: The existing workflow lacked the speed and reliability to handle increasing data volumes without added latency, risking disruption as transaction volumes continued to grow. 

Aziro designed and implemented a new AWS-native pipeline, replacing linear processing with a parallel, automated, fault-tolerant architecture built using AWS Glue, S3, and workflow orchestration for sustained high performance.

• AWS-Native ETL Pipeline: Built using AWS Glue with Python scripts for ETL processing and Amazon S3 for scalable, durable data storage across the entire migrated pipeline architecture.

• Automated Workflow Orchestration: Used AWS Workflow Orchestration for scheduled, automated runs, with parallel processing eliminating the earlier bottlenecks that had slowed the linear pipeline down considerably.

• Resilient Data Handling: Engineered to process incomplete or inconsistent key-value pairs reliably, optimizing the entire pipeline for sustained high performance and long-term fault tolerance across workloads.

• AWS Glue
• Python (ETL Scripts)
• Amazon S3
• AWS Workflow Orchestration
• Azure (Source Environment)
• API Integrations 

The migration transformed processing speed, reliability, and cost efficiency across the enterprise's data workflows, reducing manual intervention while ensuring continuous, pay-as-you-go processing capacity for growing transaction volumes.

• 88% Reduction in Processing Time: Reduction in processing time, down from 25 minutes to under 3 minutes, dramatically accelerating billing and balance reporting cycles.

• 3-5x Performance Improvement: Performance improvement through parallel execution instead of linear processing, enabling the pipeline to handle significantly higher data volumes reliably.

• 70-80% Less Manual Intervention: Reduction in manual intervention through automated, scheduled pipelines, freeing teams to focus on higher-value data and business tasks.

• 100% Data Processing Continuity: Data processing continuity, with pay-as-you-go AWS infrastructure reducing compute overhead while maintaining consistent, reliable pipeline performance. 

Aziro helps enterprises modernize legacy data pipelines that can no longer keep pace with growing transaction volumes. Our teams redesign linear, sequential processing into parallel, fault-tolerant architectures built on AWS-native services like Glue, S3, and workflow orchestration. This eliminates the bottlenecks that slow down billing, reconciliation, and reporting processes. The result is dramatically faster processing without disrupting the business operations that depend on it.

Beyond raw speed, Aziro engineers pipelines to handle real-world data inconsistencies reliably, ensuring long-term fault tolerance as data volumes continue to grow. Automated, scheduled orchestration removes the need for manual intervention, freeing teams to focus on higher-value work. Combined with pay-as-you-go AWS infrastructure, this approach reduces both processing time and ongoing compute costs. Whether migrating from Azure or another platform, Aziro builds data pipelines designed for speed, resilience, and scale.