Lift-and-shift, re-platforming, or full cloud-native — with blue-green cutover, continuous data replication, and rollback plans at every stage. We don't cut over until the data validates.
<5 min
Cutover window
Blue-green DNS switch
0
Data loss tolerance
Checksum-validated cutover
72h
Post-migration watch
Active incident response
4 ways
Migration strategies
Matched to your workload
Migration Strategies
Not every service needs the same approach. We pick strategy per workload — not per project.
Fastest path to cloud
Move existing workloads as-is. Minimal refactoring, maximum speed. Use this to exit datacenter commitments while a re-architecture plan is developed in parallel.
Managed services swap
Move the application but replace self-managed databases, caches, and queues with managed cloud equivalents — RDS over self-managed PostgreSQL, ElastiCache over self-managed Redis.
Maximum cloud benefit
Re-architect to use containers (ECS/EKS), serverless (Lambda/Cloud Run), and fully managed services. Higher upfront effort — dramatically lower operational overhead long-term.
Sometimes the right answer
Identify workloads replaceable by SaaS — no more self-managed CMS, email servers, or build systems. We'll tell you when migrating isn't worth the effort.
Scope
Databases, app servers, storage, and networking — all handled, not just compute.
PostgreSQL, MySQL, MongoDB, Redis — migrated to managed cloud equivalents with zero data loss validation, continuous replication, and minimal cutover window.
Containerized and deployed to ECS, EKS, Cloud Run, or Azure Container Apps — with load balancing, auto-scaling, and health checks configured from day one.
On-prem NFS, SMB, or S3-compatible storage migrated to cloud object storage with versioning, lifecycle policies, and CDN integration for global performance.
VPC architecture, security groups, IAM policies, and VPN tunnels designed to match or exceed your current security posture from the first deployment.
The most costly cloud migration failures are preventable. Here's how we handle each one.
Choosing lift-and-shift for a workload that needs containers — or re-architecting something simple into microservices — are the two ways teams waste six months. The right strategy depends on your timeline, your team, and your actual performance requirements, not what sounds most modern.
Our approach
We map every workload against four criteria: team capacity, downtime tolerance, performance requirements, and timeline. Strategy chosen per workload, not per project.
Every step has a defined output and a rollback path. We don't move to the next phase until the current one passes.
Inventory every service, dependency, and integration. Identify what can move independently and what has coupling constraints. Output: full application dependency graph with migration order.
Workloads grouped into migration waves by dependency and risk profile. Strategy assigned per workload. Lowest-risk services migrate first to build team confidence.
Cloud environment built and run in parallel with existing. Continuous data replication active. Functional testing, performance benchmarks, and data integrity validation all pass before any cutover is scheduled.
Scheduled cutover window with documented rollback plan ready. Blue-green DNS switch. 72-hour post-migration monitoring. Legacy environment decommissioned after validation period.
Cloud Platforms
Platform chosen based on your requirements, not our preference.
EC2, EKS, RDS, S3, Lambda, CloudFront, Route 53
AKS, Azure SQL, Blob Storage, Functions, Front Door
GKE, Cloud SQL, GCS, Cloud Run, Cloud Armor
For startups and cost-sensitive workloads
If yours is not here, reach out. We respond within 24 hours with a real answer from an engineer — not a sales pitch.

We use blue-green cutover — the cloud environment runs alongside your existing infrastructure with continuous data sync. When both environments are verified identical, DNS cutover switches traffic in under 5 minutes. The old environment remains on standby for 72 hours for immediate rollback.
Data integrity is the primary concern in any migration. We use database replication (logical replication for PostgreSQL, binlog replication for MySQL) to sync data continuously. Before cutover, we validate row counts, checksums, and application-level integrity checks. We don't cut over until data validation passes. Data loss tolerance: zero.
A simple web application with one database takes 4–8 weeks. A complex multi-tier application with many services, databases, and integrations takes 3–6 months. We phase migrations to reduce risk — you don't have to move everything at once.
Initially, often yes — we overprovision slightly during parallel run to de-risk the cutover. But at 30 and 90 days post-migration, we do a FinOps review: right-sizing, Reserved Instance analysis, and Savings Plan recommendations. Most teams end up 30–50% cheaper than their original on-prem costs once the environment is right-sized.
Yes. We migrate from on-prem to AWS/Azure/GCP, and between cloud providers. Cloud-to-cloud migrations (e.g. AWS to GCP) follow the same parallel-run approach — we build the target environment and validate before cutting over.
It depends on the workload, not the project. We lift-and-shift when you need to exit a datacenter fast or the app is stable and well-behaved. We re-platform (managed RDS, ElastiCache) when self-managed databases are an operational burden, and we refactor to containers or serverless only when the long-term savings justify the upfront effort. We assign a strategy per workload during discovery — most migrations end up using two or three approaches.
A single web application with one database is typically a fixed fee in the low-to-mid five figures over a 4-8 week engagement. Complex multi-service migrations are scoped by wave after the discovery and dependency-mapping phase. We give you a firm price and timeline before any cutover work begins. Factor in that most teams land 30-50% below their original on-prem costs after the 90-day FinOps right-sizing review.
“They built our SaaS from scratch — auth, billing, dashboards, the works. Running 14 months with 99.97% uptime. When we needed features, the code was so clean changes were fast.”
James Morton
CEO · Docket Analytics · Vancouver, Canada
Tell us what you're running and where. We'll design a migration plan with timeline, risk assessment, and cost projections.
