Client Success Story

Cloud-Based System Modernization Reduces Data Processing Time by 87%

The client

A Marketing Consulting Firm with a Data Analytics Platform

Our client has over two decades of experience working with companies in the food & beverage, hospitality, and financial services industries. Their existing solution is an analytics platform that allows end users (their clients) to transform their business data (point-of-sale transactions) into easy-to-understand insights for decision-making.

The REQUIREMENTS

Legacy Solution Modernization

The client’s existing solution was outdated and dependent on legacy hardware. It was hampering their operations while not allowing them to scale. Complex system maintenance also led to unjustified operational costs. Additionally, the platform was struggling to meet performance demands, with a month's worth of POS (point-of-sale) data taking over two days to process.

To address these challenges, they came to us seeking legacy system modernization and

  • A scalable technology stack to handle increasing data volumes efficiently
  • Reduced system maintenance complexities and lower operational costs
  • Faster processing of point-of-sale data
  • Cloud migration for advanced capabilities and improved overall platform reliability
The CHALLENGES

Complications with their Legacy Analytics Platform

After analyzing their technology infrastructure and the platform, we came across the following difficulties:

  • As their system was over 20 years old, there was insufficient documentation with inconsistent code structures, embedded business logic, and legacy programming languages
  • Legacy customizations on the platform restricted our architectural design options
  • Huge volume of data with outdated and inconsistent formats and duplicate entries
OUR PROPOSAL

A Cloud-First System Upgrade

Given the primary challenge of obsolete technology, infrequent data processing timelines, and reliance on legacy hardware, we proposed a comprehensive reverse engineering solution. This plan included deciphering the codebase, mapping implementation and configuration, designing a cloud architecture, migrating data with ETL pipelines, and deploying the entire system on the cloud using CI/CD pipelines for uninterrupted business operations.

The SOLUTION

End-to-End Cloud Migration and Modernization

1

Deciphering the Codebase

  • We analyzed the existing source code using tools like SonarQube for in-depth analysis and to understand the platform's structure
  • Our team identified key components, dependencies, vulnerabilities, and their interactions within the codebase
  • Our cloud migration experts mapped out the logic flows to document current processes and data paths
2

Mapping Implementation & Configuration

  • To understand their purposes and interactions, we mapped all implemented functionalities using UML and architecture diagrams
  • All files were reviewed for environment-specific settings, with all configurations meticulously documented
  • We created a comprehensive list of external libraries, APIs, and services used by the current system
  • Detailed documentation of our findings was prepared to ensure a comprehensive understanding
3

Designing Cloud Architecture

  • As a part of our cloud migration services, we designed a scalable architecture using Amazon S3 for storage, AWS Glue for ETL processes, and Amazon Redshift for data warehousing
  • With the selected appropriate AWS services, we were able to meet performance and scalability requirements
  • Implemented robust security measures through AWS IAM and encryption protocols
  • Designed redundancy and failover mechanisms to maintain high availability
4

Migrating the Data with ETL Pipelines

  • We extracted data from the legacy system with minimal disruption and zero data loss
  • Developed transformation rules to clean and normalize the data
  • Our experts implemented ETL processes using AWS Glue and Apache NiFi for efficient data processing
  • Lastly, we loaded the transformed data into Amazon Redshift, ensuring data integrity and accuracy
5

Deploying on the Cloud

  • We created and configured AWS environments for custom development, testing, and production
  • Automated the deployment process by setting up CI/CD pipelines for seamless transitions using AWS CodePipeline and Jenkins
  • Load and stress tests were also conducted to ensure system stability and performance
  • Lastly, we also implemented automated monitoring and logging solutions for a hassle-free deployment process using Amazon CloudWatch and AWS CloudTrails

Project Outcomes

We completed the project by delivering a cloud-agnostic, modern analytics platform that delivers highly accurate results. It has a user-friendly interface with easy navigation and custom data visualization options, allowing all end users to securely derive actionable insights.

Data processing pipelines now run in 6 hours (instead of 2 days)

87% reduction in the data processing timelines

70% reduced physical footprint and dependence on legacy hardware

60% reduced operational costs due to automated updates

CONTACT US

Upgrade your Systems for Improved Performance with Legacy Software Modernization

By modernizing the client’s analytics platform and moving it to the AWS cloud, we delivered exceptional performance improvements through reduced dependency on legacy hardware. You can achieve similar results for your business with our legacy software modernization services.