From Digital Ocean to AWS EKS

Executive summary

This case study details a successful cloud migration and modernization initiative, transitioning a critical application infrastructure from Digital Ocean to Amazon Web Services (AWS) Elastic Kubernetes Service (EKS). The project encompassed a phased rollout across staging, development, and production environments, leveraging Infrastructure as Code (IaC) for consistency and automation. Key technical implementations included advanced Continuous Integration/Continuous Delivery (CI/CD) pipelines for both application and infrastructure, robust backup and disaster recovery strategies, integration of AWS Web Application Firewall (WAF) for enhanced security, implementation of Review Apps for accelerated frontend development, a comprehensive Data Warehouse with Metabase for business intelligence.

Current state on Digital Ocean

The client’s existing infrastructure on Digital Ocean, while initially serving its purpose, began to exhibit critical limitations as the business scaled. This environment was characterized by manual management and a lack of advanced cloud-native capabilities. As the business grew and user traffic surged, DigitalOcean’s servers struggled to keep pace, resulting in significant slowdowns in response times during peak hours, frequent service interruptions, and higher latency. The platform’s limited auto-scaling capabilities made it difficult to dynamically meet demand, requiring manual intervention which proved to be an unsustainable temporary fix.

Driving factors for migration

The compelling need for a more scalable, reliable, and feature-rich platform led to the strategic decision to migrate to AWS. AWS offered a comprehensive suite of cloud services capable of addressing the identified limitations, providing access to a wealth of advanced cloud services, improved performance, enhanced scalability, and robust security features. Amazon EKS was chosen as the central pillar for the migration due to its managed Kubernetes service, which efficiently orchestrates containerized applications with automatic scaling and robust integration with other AWS services. EKS offloads the burden of managing the Kubernetes control plane, allowing the team to focus on applications rather than the underlying infrastructure. This selection reflected a deliberate choice to adopt cloud-native best practices, moving beyond mere infrastructure hosting to a fully managed, scalable, and secure container orchestration platform. This indicated a strategic shift towards a more resilient and agile operational model.

Strategic Phased Migration to AWS EKS

Multi-account and multi-Environment strategy

A foundational element of the migration was the implementation of a robust multi-account strategy within AWS, utilizing AWS Organizations. This approach involved setting up distinct AWS accounts for each environment: staging, development, and production. This architecture provides strong security isolation, preventing unintended access or impact between environments. It also simplifies cost tracking and billing, allowing for granular financial oversight per environment. Service Control Policies (SCPs) within AWS Organizations can further enforce consistent policies across accounts.

The adoption of a multi-account strategy signifies a mature cloud governance model, providing strong isolation, clear billing separation, and enhanced security boundaries between critical environments. This is a foundational best practice for enterprise cloud deployments. This architectural decision impacts not just technical deployment but also organizational processes around security, compliance, and financial management, demonstrating a holistic, enterprise-ready approach to cloud adoption.

Infrastructure as Code (IaC)

The entire AWS infrastructure, including Virtual Private Clouds (VPCs), subnets, security groups, and EKS clusters, was defined and managed using Infrastructure as Code (IaC) tools, primarily Terraform. This approach ensured consistent and repeatable deployments across all environments (staging, dev, production), significantly reducing the potential for human error and accelerating the provisioning process. By defining infrastructure in code, changes became version-controlled, collaborative, reviewable, and reversible, treating infrastructure with the same rigor as application code. This provided a clear audit trail for all infrastructure modifications.

Moving from manual provisioning, which was characteristic of the DigitalOcean environment, to IaC is a critical shift that underpins consistency, auditability, and rapid iteration across multiple environments. It transforms infrastructure management into a software development discipline. This directly addressed the issues of manual intervention and fragile infrastructure experienced on DigitalOcean. IaC is not merely a technical tool; it is a cultural enabler for DevOps, fostering collaboration, reducing risk, and improving the overall quality and speed of infrastructure delivery across the entire software development lifecycle.

Phased rollout and testing methodology

The migration followed a meticulous, phased approach: reviewing the current infrastructure, creating infrastructure on AWS for staging, then development, and finally production. This iterative process allowed for rigorous testing and validation at each stage, systematically minimizing risks before impacting live users.

Staging environment setup & validation

The initial step involved a thorough review of the existing Digital Ocean infrastructure to understand dependencies and configurations. Subsequently, AWS infrastructure for the staging account was created, mirroring the target production environment. All applications were deployed, run, and subjected to extensive testing on the staging account. Staging data was “flipped,” which involved migrating a copy of the staging data to the staging environment and then configuring applications in staging to connect to this new data source. This process allowed for comprehensive testing of data consistency, application connectivity, and performance under realistic data loads without affecting live production. This step effectively rehearsed the critical data cutover process. Comprehensive functional, performance, integration, and security testing were conducted to validate the new environment.

Development environment setup & validation

Following successful staging validation, AWS infrastructure was provisioned for the development account, providing developers with a cloud-native environment. Applications were deployed, and development data was “flipped” and tested. This ensured that developer workflows were integrated with the new AWS environment, allowing for early detection and resolution of environment-specific issues. This phase was crucial for refining deployment processes and application configurations in a non-production setting.

Managed AWS RDS for PostgreSQL and AWS RDS for MySQL

Our choice for the database engines was obvious. As the client has used PostgreSQL and MySQL enginess very heavily in the past, we’ve chosen AWS RDS managed databased services for all of clients transactional database needs. For the right sizing we’ve performed a diligent load and stress testing round on a lower environment and settled for the best db instance clases taking into account clients availability and durability requirements, as well as empirical data which we managed to gather duting our strees testing excersises. Extending the usual database backend setups, client has tasked us with creating a Data Warehouse based on AWS RDS for PostgreSQL with a live AWS DMS ( Database Migration Service ) replication from all main production db workloads.

Production environment setup & pre-launch testing

The final phase involved setting up the AWS infrastructure for the production account, built upon the validated IaC templates from staging and development. Extensive pre-launch testing was conducted, including running all applications and performing final validations to ensure readiness for the live launch.

The “flipping data” in staging and development environments served as a crucial de-risking strategy. It functioned as a rehearsal of the critical production cutover, allowing teams to identify and resolve data consistency, application connectivity, and performance issues in a controlled manner before impacting live users. This iterative testing of the cutover process was key to achieving zero-downtime migrations. For instance, database cutover strategies such as “flash-cut migration” (using continuous data replication) or “active/active database configuration” (with dual writes or bi-directional replication) were considered or employed to minimize downtime.

During a real-world migration to Amazon EKS, the production infrastructure hosted on DigitalOcean was deliberately shut down as part of the switchover process. Only after this shutdown was traffic shifted to the newly provisioned AWS environment—introducing a brief but intentional period of downtime. An automated DNS cutover was used to streamline the switchover, but unlike a zero-downtime scenario, there was a noticeable delay during the transition.

The term “flipping data” in this context refers to updating application configurations—such as changing database connection strings—to point to the freshly migrated AWS-hosted services. This usually followed the completion of data replication and synchronization between environments. Rehearsing this complex cutover process in staging and development environments was paramount to identify and mitigate potential issues (data consistency, network latency, application compatibility) in a controlled manner, thereby significantly de-risking the eventual production launch and aiming for zero downtime. This phased approach, coupled with iterative “data flipping” and comprehensive testing, embodied a robust risk mitigation strategy, ensuring that complex interdependencies were validated, performance bottlenecks identified, and operational procedures refined, leading to a high-confidence production launch and minimizing business disruption.

Outcomes, benefits, and lessons learned

The comprehensive migration and modernization initiative yielded significant improvements across various dimensions, directly addressing the limitations faced on DigitalOcean and positioning the organization for future growth.

Achieved business value

• Significant cost reductions were achieved through efficient resource utilization on AWS, leveraging EKS auto-scaling to dynamically provision nodes and utilize cost-effective.
• Applications exhibited improved response times and the ability to handle peak loads without slowdowns, ensuring a superior user experience.
• The meticulous phased migration strategy, coupled with advanced data cutover techniques, resulted in near-zero downtime during the migration process itself.
• Modernized CI/CD pipelines and the implementation of Review Apps dramatically accelerated deployment speeds.
• By offloading the burden of infrastructure management to AWS EKS and automating operational tasks, engineering teams were freed to focus on revenue-generating product development and innovation.

Technical efficiencies

• The dynamic scaling capabilities of Amazon EKS, combined with its native integration with other AWS services, ensured high availability and performance, capable of meeting fluctuating demands.
• The implementation of robust security features, including AWS WAF, granular IAM controls, end-to-end encryption (e.g., via AWS KMS), and secure secrets management, significantly enhanced the overall security posture and ensured adherence to compliance requirements like GDPR .
• The managed nature of the EKS control plane reduced operational overhead for the team. Infrastructure as Code provided consistent, repeatable, and auditable infrastructure deployments, moving away from manual, error-prone processes.

Challenges encountered and solutions

• Moving large volumes of sensitive data while maintaining consistency and ensuring business continuity was a significant hurdle. This was overcome through a phased migration approach, continuous data replication (CDC), and robust, rehearsed cutover strategies.
• The inherent learning curve and operational complexity of Kubernetes and EKS required dedicated effort. This was managed through comprehensive training, leveraging managed services (EKS control plane), and implementing IaC for consistent configurations.

Key learnings and best practices

• Begin with a single application or service to prove the concept and refine processes before scaling up the migration effort.
• Develop a detailed cloud migration strategy and roadmap that meticulously accounts for application dependencies, data volumes, business continuity requirements, and potential risks.
• Treat infrastructure as code from the outset. This is fundamental for achieving consistency, efficiency, auditability, and reducing human error across all environments.
• Implement thorough and automated testing at each stage of the migration (staging, development, production), including dedicated rehearsals for data cutovers and application traffic shifts. This systematically de-risks the entire process.
• For business-critical applications, prioritize and meticulously plan for zero or minimal downtime using advanced data replication and traffic shifting techniques (e.g., flash-cut migration, active/active configurations, automated DNS cutovers).
• Integrate security at every layer of the stack, from network security groups to application-level firewalls (AWS WAF), and leverage IAM for granular access control. This ensures a comprehensive defense posture.
• Adopt GitOps and dynamic ephemeral environments (Review Apps) to enable continuous delivery, rapid feedback loops, and accelerated development cycles.
• While IaC provides inherent documentation, supplementing it with clear explanations of architectural decisions, operational procedures, and troubleshooting guides is vital for long-term maintainability and knowledge transfer.