There were a few challenges that CleanSlate initially faced when determining the best strategy for the migration. These include:

1. Compressed Timeline and Datacenter Exit
KSM was required to exit their on-premises data center within a short and inflexible timeline. They were also entering their busy season and could not afford any business disruption. This created a high-pressure environment where all stages needed coordinated and executed to maintain business.

2. Complex Azure Workloads and Interdependencies
KSM had many interconnected workloads which introduced dependency mapping and sequencing challenges requiring deep understanding of both Azure and AWS architectures. This required careful planning, automation, and robust monitoring to ensure reliability and operational efficiency.

3. Modernization Required Beyond “Lift and Shift”
Early assessments revealed that with the datacenter and Azure migration, modernization was needed to achieve the business goals. With workloads being tightly coupled and legacy configurations limited scalability. To meet the goals (performance, cost, and resiliency), CleanSlate helped KSM re-architect their Azure environment and portions of on-premise to a modern, cloud-native design optimized for AWS.

4. Small Internal IT Team with Limited Bandwidth
The team was strong but small and willing to learn, but had limited exposure to all the services AWS could provide. The challenge became focused on ensuring migration proceeded efficiently while preparing the internal team to ensure they could manage the new environment post-migration. This meant built-in automation with controls and governance was important.

The scope of the environment consisted of migrating:

• 50 Windows Servers
• 12 SQL Servers (All Standard)
• 22 Azure Functions
• 28 Azure App Service Plans
• 24 Azure Storage Accounts

The goal was to finalize the migration before the data center lease expired, giving CleanSlate just 10 weeks to complete the project.

With KSM and CleanSlate in agreement on the right plan, CleanSlate’s team began designing and implementing an AWS-first architecture. CleanSlate conducted batch migrations using a migration waves concept. This divided the large-scale migration project into smaller, more manageable phases in order to reduce risk and minimize disruptions. Here are a few of the solutions the CleanSlate team implemented:

1. Accelerated Assessment and Migration Planning

This was completed by the CleanSlate team utilizing a Cloud Optimization Blueprint powered by AWS OneOLA and the CleanSlate MAP++ solution with AWS MAP. The Migration Acceleration Engine is engineered to compress migration timelines, drive value faster, and fully leverage AWS programs to accelerate cloud consumption. During the engagement, the CleanSlate team rapidly evaluated KSM’s environment using the AWS OneOLA framework. CleanSlate delivered a data-backed business case for migration and modernization, uncovering cost savings, license impact and the art of the possible to accelerate entry into the MAP ++ program.

2. Migration of On-Premise and Azure to AWS

CleanSlate completed the migration using Infrastructure-as-code (IaC) with Hashicorp Terraform to create consistency, repeatable, and faster deployments—ensuring KSM’s workloads were optimized for AWS scale and performance. This rapid engagement to automate AWS infrastructure using Terraform delivered repeatable, scalable, and governed deployments.

3. Azure to AWS Application Re-architecture and Modernization

CleanSlate ensured Legacy Azure configurations were moved to AWS native services by transitioning SQL workloads to RDS and serverless functions to Lambda. This was a strategic effort by CleanSlate to transform the applications themselves to better leverage the cloud-native capabilities of AWS. This involved:

• Refactoring: Modifying the application’s code to take advantage of cloud-native services like serverless functions (AWS Lambda) and managed databases (Amazon RDS).
• Microservices adoption: Breaking down monolithic applications into smaller, independent services that can be developed, deployed, and scaled independently.
• Leveraging AWS-specific services: Integrating with AWS services for analytics, machine learning, security, and more, to enhance application functionality and performance.
• Optimizing for cost, scalability, and resilience: Designing the applications to be more efficient, automatically scale to handle varying workloads, and be resilient to failures.

4. Enablement and Knowledge Transfer

CleanSlate consultants trained the KSM team on how to effectively use AWS and ensured that they were positioned to utilize all the features available to them. Through a proven crawl, walk, run approach, CleanSlate started by training staff on foundational AWS services, then moved to more complex, workload-specific topics as the migration progressed.

5. Collaboration with AWS

CleanSlate wanted to maximize the value that KSM would receive through the migration and modernization. Therefore, a collaboration with AWS was necessary to achieve maximum business value through programs like OLA and MAP. CleanSlate wanted to ensure KSM could achieve measurable results such as:

• Cost savings: Reducing total infrastructure costs and optimizing licensing expenditures.
• Agility: Quickly provisioning resources to build new applications and respond to changing market demands.
• Resilience: Improving operational resilience against failures and disasters.

Technologies & Services Used

• AWS
• HashiCorp Terraform
• GitHub
• Migration Services
• CI/CD Automation

With limited internal bandwidth and a pressing timeline, CleanSlate delivered a scalable, AWS-native architecture that improved performance, reduced operational overhead, and paved the way for KSM’s future innovation. A few key results include: 

• Completed migration within the deadline.
• Reduced risk by exiting legacy infrastructure.
• Improved performance and scalability.
• Freed internal resources for higher-value initiatives.

Additionally, KSM is poised to achieve 30% or more in cost savings with rightsizing and optimization after the project is complete.