Your AWS migration runs in production. Not just in a slide deck.
Engineering teams moving off on-premises or legacy cloud hire us for AWS cloud migration services that ship. We build a governed Landing Zone before workload 1 touches AWS. Every resource is Terraform-managed. Cutovers run parallel to your live system, with a tested rollback in place before traffic shifts. EKS, RDS, S3, Lambda, and CloudFront — chosen for your workload profile, documented in an architecture decision record before provisioning.
This is what your infrastructure looks like now — and what it looks like after we move it to AWS.
Not a theoretical diagram. Every item on this card is a pattern we migrate away from and a result we deliver. Flip it to see both sides.
Your workloads reach production on AWS in 12 to 16 weeks. Here is exactly how.
Every project follows the same five-phase process. Each phase delivers a concrete output in your AWS account before the next one starts. Select a phase below to see what you receive.
We catalog every workload: OS, runtime, dependency graph, network flows, data volumes, compliance requirements, and performance baselines. Every integration point gets documented. You receive a workload migration profile and a prioritized migration backlog before we write a single line of Terraform. Mid-project surprises start here.
We build a governed multi-account AWS environment before workload 1 moves. VPC design, subnet layout, IAM permission boundaries, security groups, CloudTrail logging, GuardDuty, and AWS Config rules are all version-controlled in Terraform before migration begins. Your AWS environment is governed on day one, not patched six months later.
Workloads move in wave order. Each one runs in parallel on both environments while we validate. Route 53 weighted routing shifts 5%, then 25%, 50%, then 100% of traffic. A tested rollback is in place before any traffic moves. Data migrations run dry-run first with byte-for-byte validation before the real cut.
After 30 days in production, AWS Cost Explorer and CloudWatch reveal the real utilization profile. We right-size EC2 and RDS instances, buy Reserved Instances for baseline load, configure spot for burst workloads, and set up AWS Budgets with spend alerts. Most teams see 40 to 50% cost reduction here.
Your team receives a complete Terraform codebase, architecture decision record, CloudWatch dashboard configuration, and on-call runbook with incident playbooks. We stay active for 30 days after go-live. That stabilization window catches edge cases your team never saw during testing — before they become 3am incidents.
The right AWS service for your workload. Not the one we know best.
Value stack · cloud engineer reviewing AWS console with EKS cluster map on large monitor
Your containerized applications run on EKS or ECS based on workload requirements and your team's Kubernetes depth. EKS handles complex multi-service architectures where you need full control. ECS handles simpler container workloads without the overhead of managing Kubernetes. Docker, Horizontal Pod Autoscaler, and Helm are standard.
You stop managing database infrastructure. Automated backups, Multi-AZ failover, read replicas, and point-in-time recovery are built in. RDS fits standard workloads. Aurora fits high-throughput apps that need MySQL or PostgreSQL at cloud scale, where Aurora's replication speed matters.
S3 stores files with durability so high that losing an object is statistically rarer than a hardware failure hitting 11 data centers at once. CloudFront puts your content at AWS edge locations globally, cutting latency to under 10ms. Static assets, user uploads, and media move to S3 first, before compute workloads.
Background jobs, scheduled tasks, and event-driven processes move to Lambda. You pay per execution — no servers sitting idle between jobs. SQS decouples services so a spike in one queue does not cascade into a system-wide failure.
Any environment on this stack can be rebuilt from the Terraform repository in under 15 minutes. No manual console changes in production — ever. CodePipeline and CodeBuild handle CI/CD with rolling deployments and automated health-check rollbacks.
A SaaS platform shipped from monolith to microservices on AWS EKS. Zero unplanned downtime after go-live.
Proof · SaaS product team reviewing AWS EKS monitoring post-migration, all-green metrics
The platform's engineering team carried a monolithic application that had outgrown itself. Releases required a full maintenance window. Outages happened at the database layer and cascaded across the whole product. Scaling any one service meant scaling everything. The team needed a path to independent services, faster deploys, and a database layer that did not become a single point of failure.
We re-architected the application into microservices, containerized each service with Docker, and ran orchestration on AWS EKS. Each service team got its own CI/CD pipeline in CodePipeline with rolling deployments and automated rollback on health check failure. Core APIs, authentication, and databases moved to independent services. RDS Multi-AZ replaced the single database. The platform now ships multiple times a day with no maintenance window.
Three things every AWS migration requires that most partners skip.
What engineering leads ask before starting an AWS cloud migration.
Tell us about your project. We will scope your AWS migration in three days.
No commitment, no pitch. You receive a written migration scope, a workload inventory framework, and a proposed timeline — all within three business days of our call.
Submit brief → call within 48 hours → migration assessment in 3 days → Sprint 1, week 2
Pre-footer · cloud infrastructure team reviewing AWS CloudWatch all-green dashboard post-migration
