Industry: Communications, Media and Entertainment | Services: Cloud, Intelligent Automation
Client Overview
The client is one of the largest prepaid wireless service providers in the United States, serving over 20 million subscribers and generating $10 billion in annual revenue. Operating in a highly competitive market, the company sought to enhance its technological capabilities to maintain its market position and support continued growth.
The Challenge
Legacy Infrastructure and Operational Inefficiencies Limiting Growth Trajectory
Despite strong market traction and a customer base of over 20 million, the client was increasingly constrained by its outdated, on-premise IT infrastructure. Years of technical debt had resulted in fragile systems, rigid architectures, and unsustainable operational expenditures. Prior capital investments to modernize its data center had failed to yield transformative gains, leaving the company vulnerable in an aggressively competitive and price-sensitive telecom landscape.
Several critical challenges had emerged:
- System Fragility and Latency: A complex and brittle technology stack made it difficult to manage spikes in demand, particularly during promotional campaigns and seasonal sales – periods when website traffic could increase by up to 20x. This led to inconsistent digital experiences and revenue leakage due to customer abandonment.
- High Cost Structure: The client’s infrastructure required substantial ongoing investment to simply maintain performance parity, limiting resources available for innovation and customer experience improvement.
- Operational Inflexibility: Without a modern DevOps framework, development teams were unable to deploy or iterate independently, slowing time-to-market and reducing responsiveness to business needs.
- Lack of Scalable Insights: The absence of an enterprise-wide data strategy restricted the company’s ability to leverage customer data for personalization, predictive insights, or process optimization.
To remain competitive, the client needed a bold, end-to-end digital transformation that would reduce costs, increase resilience, enable rapid innovation, and support a scalable digital-first customer engagement strategy.
Sutherland Solution
Sutherland was selected as the customer’s strategic transformation partner to lead a multi-year digital modernization initiative aimed at stabilizing existing systems while architecting a future-ready, cloud-native enterprise on Amazon Web Services (AWS). The program encompassed the end-to-end migration of Oracle E-Business Suite (EBS) workloads, databases, and integrations from on-premises HP-UX infrastructure to AWS, while upgrading Oracle EBS from 12.1.3 to 12.2.10 and the Oracle Database from 11g to 19c.
The transformation began with stabilization and optimization of legacy environments to ensure application consistency and continuity during migration. Sutherland’s engineering teams modernized configuration baselines, tuned performance bottlenecks, and prepared data for cloud transition. The upgraded application and database stack were deployed on Amazon EC2 instances across multiple Availability Zones for high availability and disaster recovery, using Oracle Data Guard replication and EBS NFS shared storage for synchronization and resilience.
A 100% cloud migration to AWS was completed using an automated deployment framework built on Terraform and Jenkins. Infrastructure provisioning, environment creation, and validation workflows were codified in Terraform, with continuous integration and delivery managed through Jenkins pipelines. This automation ensured consistent, repeatable deployments and shortened provisioning cycles from days to hours. In parallel, over 1,000 containerized microservices were deployed on Amazon Elastic Kubernetes Service (Amazon EKS) to deliver scalable, modular functionality, improving elasticity, fault isolation, and release agility.
Sutherland also implemented a DevOps-led delivery model, introducing automated CI/CD pipelines that enabled development teams to perform continuous integration, vulnerability scanning, and deployment orchestration without downtime. Operational testing leveraged CloudTestr, automating over 500 regression test cases across finance, supply chain, and HR modules to ensure functional continuity post-migration.
To enable data-driven decisioning, the team designed and deployed a cloud-based data lake on AWS, integrating analytics and machine learning capabilities. Optimized big data pipelines processed customer interactions and operational metrics, enabling predictive insights such as next-best offers and behavior-based targeting. The integrated data ecosystem now powers real-time reporting and analytics across the organization.
Through this full-stack digital transformation, combining cloud migration, DevOps automation, and intelligent data enablement, Sutherland helped the customer achieve greater cost efficiency, operational agility, and innovation velocity, establishing a scalable foundation for long-term digital maturity.
The Outcome
The modernization initiative delivered transformative, measurable impact across financial, operational, and technology domains. The complete migration of Oracle E-Business Suite and database environments to AWS eliminated dependence on legacy HP-UX infrastructure and reduced annual operating expenditure by approximately $30 million, through infrastructure consolidation, automation, and license optimization.
With the deployment of automated CI/CD pipelines on Jenkins and Infrastructure-as-Code using Terraform, environment provisioning and release cycles were shortened from weeks to hours. Development and operations teams achieved full pipeline automation, enhancing deployment reliability and enabling continuous delivery across all critical business modules.
System availability and performance improved significantly after moving to AWS’s multi-Availability Zone architecture, which leveraged Oracle Data Guard replication and EBS NFS shared storage for high availability and rapid recovery. Automated regression and integration testing through CloudTestr cut validation time by nearly 80 percent, allowing additional test coverage and faster release approvals.
The new cloud-based data lake and analytics platform on AWS provided a unified foundation for data ingestion and insight generation, powering predictive and machine-learning-driven use cases such as next-best offers and customer-behavior modeling. These improvements enabled the enterprise to innovate rapidly, scale on demand, and maintain uninterrupted customer experiences.
Collectively, the migration positioned the organization with a modern, AI-enabled, cloud-native ecosystem, driving cost efficiency, operational agility, and technology resilience that supported its successful transition into a major U.S. telecom group.
AWS Resources at play:
- AWS Control Tower + Landing Zone Deployment
- R5b Memory Optimized Instances for Large DB workloads
- RAID on Io2 Block Express Volumes to achieve 200K+ IOPS
- Jenkins CI + CD & Terraform for Application & Database deployment
- AWS EFS for High Availability
- AWS GuardDuty, CloudWatch & Inspector along with customer’s integrated security tools
- AWS Control Tower + Landing Zone Deployment
About Sutherland
Sutherland is a global leader in digital transformation, combining deep expertise in cloud engineering, automation, and AI-driven analytics to help enterprises modernize complex technology landscapes. As an AWS Partner with proven capabilities in migration, modernization, and intelligent automation, Sutherland brings together technical excellence and domain experience to deliver measurable business outcomes. Its integrated approach, blending cloud strategy, DevOps automation, and data-driven intelligence was central to the success of this engagement. By leveraging AWS best practices and Sutherland’s proprietary automation frameworks, the customer achieved a seamless migration, accelerated innovation cycles, and long-term operational resilience in the cloud.
KEY OUTCOMES
In aggregated OpEx savings
Automation of deployment pipelines
Workload modernization with AWS Cloud
