Application platform
Amazon EKS can host containerized services with autoscaling and workload isolation. Helm packages deployment configuration. Capacity and scaling policies should be validated against representative traffic before cutover.
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Architecture walkthrough
E-commerce AWS Migration Architecture
Article updated
A reference approach for moving an e-commerce workload from on-premise infrastructure to AWS. It explains the decisions behind container orchestration, database resilience, delivery automation and observability.
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The problem
A retail workload can face variable traffic, tightly coupled deployments and uncertain recovery procedures. Migration planning must account for those constraints before selecting services. This walkthrough describes a design approach; it does not represent a verified customer result.
Responsibility and scope
WebNasr’s role in this walkthrough is to explain the architecture, migration sequence and operational responsibilities. No customer identity, project team size, delivery timeline or achieved performance improvement is asserted.
Engineering decisions
Architecture and tradeoffs
Move in controlled stages. Establish workload dependencies and a rollback route, separate application deployment from database migration, and test recovery before switching traffic. Kubernetes is useful when the workload and operating team justify its complexity; it should not be the default for every application.
Data and delivery
Amazon RDS PostgreSQL provides managed database operations and backup options. ArgoCD reconciles reviewed deployment definitions from Git, giving the team a clear record of the intended application state.
Edge and operations
CloudFront and S3 separate static delivery from application traffic. WAF, least-privilege IAM and managed secrets provide security layers. Prometheus and Grafana make application and infrastructure behavior visible during migration.
What the work establishes
Outcome and evidence
The result is a reviewable reference design that connects an EKS application platform, managed database, GitOps workflow and monitoring. Actual cost, availability, recovery and latency outcomes depend on the workload, implementation and measured baseline. They require validation during a real engagement.
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