At a glance

Legacy sources: On-prem monoliths · Windows Services · IIS apps · Legacy SQL stacks · BizTalk
Modern targets: AWS · Azure · Kubernetes · Microservices · CQRS / Event-sourcing
Typical timeline: 3 months to 2 years for large estates
Project range: $50,000 to $500,000+
U.S. delivery: 100% U.S. citizen workforce, U.S.-soil delivery

What to know before you modernize

Modernize Your Legacy Applications

Cloud-native is not the right answer for every legacy system. When it is, the right reasons are usually variable load that benefits from elasticity, audit and observability needs that legacy stacks cannot satisfy, or a deployment model that demands automation. The founder has worked with AWS and Azure as primary targets across multiple prior career roles and designs around the boundaries that make sense for the specific system, not a one-size-fits-all reference architecture.

Overcoming Legacy System Limitations

Legacy systems hit real walls in the cloud era: hardware that no longer scales linearly, deployment processes that take weeks instead of minutes, and observability that requires reading log files manually. Cloud-native fixes these specific problems when the application is suited for it. When it isn't, hybrid or virtualization is often the better answer.

What Cloud-Native Actually Delivers

Done well, cloud-native delivers three things legacy systems struggle with: elastic capacity that follows real load, deep observability of the running system, and deployment automation that turns releases from events into a routine. Done badly, it just relocates the original problem to a more expensive environment. The difference is design discipline at the boundaries: where data lives, where state is held, and where the system can fail without taking everything else down.

Comprehensive Cloud Transformation Solutions

We deliver full cloud-native transformations, from domain decomposition and microservice design through CI/CD, observability, and production cutover. Our architectures use CQRS and event-sourcing where audit and real-time insights matter, serverless where workloads are spiky, and managed data stores (DynamoDB, Cosmos DB, Aurora) for operational simplicity. Infrastructure is defined as code. Deployments are automated with progressive rollout and rollback. You get not just a modernized app, but a platform your team can build on.

Deliverables

Microservice architecture on AWS or Azure
Infrastructure as code (Terraform / Bicep)
CI/CD pipelines with automated rollback
Observability: logs, metrics, traces, SLOs
Real-time insights via event-driven patterns