About the Client
A leading financial technology provider delivers secure and scalable analytics solutions to banking and financial services organizations, supporting data-intensive workloads in a highly regulated industry.
As business demand grew, its SAS Viya analytics platform was operating on an on-premises infrastructure that required significant manual provisioning and operational effort. The environment made it difficult to scale efficiently, maintain consistent deployments, and respond quickly to evolving business requirements.
The organization partnered with Lauren Group to migrate its SAS Viya platform to AWS while transforming the underlying deployment and infrastructure model - creating a more scalable, automated, and repeatable foundation for future growth.
The Problem
The existing SAS Viya environment had become increasingly complex to manage, with infrastructure and platform operations relying heavily on manual processes.
Key challenges included:
- Manual infrastructure provisioning causing deployment delays and operational dependency
- Complex management across multiple infrastructure components
- Limited scalability for growing analytics workloads
- Inconsistent deployment processes across environments
- High operational overhead for infrastructure administration
- Difficulty establishing a standardized and repeatable deployment model
- Need to strengthen security, governance, and compliance
- Requirement to migrate and transform the platform without disrupting business operations
Our Approach
Lauren Group followed a structured Assess → Mobilize → Migrate & Modernize approach, combining the migration of the existing SAS Viya platform with targeted platform and infrastructure modernization.
1. Assessment
We assessed the existing environment to determine migration readiness, platform dependencies, and the right AWS target architecture.
- Conducted infrastructure discovery and workload assessment
- Analyzed application and platform dependencies
- Assessed the existing SAS Viya environment
- Evaluated Kubernetes readiness and containerization requirements
- Reviewed networking, security, storage, and data migration requirements
- Planned the AWS landing zone and target architecture
- Conducted AWS cost assessment using AWS Pricing Calculator
- Developed migration waves and production cutover plans
2. Mobilization
We established the AWS foundation and prepared the target environment for migration.
- Provisioned the AWS environment and Amazon VPC
- Deployed the Amazon EKS cluster
- Developed Terraform-based Infrastructure as Code
- Configured Amazon ECR for container image management
- Implemented IAM and security policies
- Designed persistent and shared storage using Amazon EBS and Amazon EFS
- Configured monitoring and logging
- Prepared migration runbooks, testing plans, and production cutover procedures
3. Migration & Modernization
Lauren Group migrated the SAS Viya workloads from the on-premises environment to SAS Viya 4 on Amazon EKS, using a replatform + refactor approach.
The transformation included:
- Migrated SAS Viya workloads from on-premises infrastructure to AWS
- Replatformed the environment onto Amazon EKS
- Refactored deployment practices around Kubernetes
- Automated infrastructure provisioning using Terraform
- Implemented Kubernetes-based application deployment
- Migrated application data and persistent storage
- Established centralized monitoring and logging
- Implemented AWS-native security and governance controls
- Conducted functional, performance, and user acceptance testing
- Executed production cutover and validation
- Transferred operational knowledge to customer teams
Tech Stacks Used
Amazon EKS
Amazon EC2
Amazon ECR
Amazon EFS
Amazon EBS
Terraform
Amazon CloudWatch
The Result
The engagement successfully migrated the SAS Viya analytics platform from on-premises infrastructure to AWS while transforming how the platform was deployed, provisioned, secured, and operated.
The organization achieved:
- Successful migration to Amazon EKS, moving SAS Viya workloads from on-premises infrastructure to AWS
- Automated infrastructure provisioning through Terraform
- Standardized Kubernetes-based deployments across environments
- Improved platform scalability through Amazon EKS Managed Node Groups
- Reduced infrastructure management overhead through Infrastructure as Code
- Strengthened security and governance through AWS-native services
- Centralized monitoring and visibility through Amazon CloudWatch
- A repeatable cloud-native deployment framework supporting future application and analytics workloads
The result was a successful AWS migration that also established a more scalable, automated, and consistent operating model for the organization's analytics platform.
