Cloud migrations earn their bad reputation when they're rushed, under-tested, or done by a team that doesn't know your business. We plan for the boring parts — DNS cutovers, license edge cases, that one app nobody documented — and run the cutover after hours so staff arrive Monday to a working environment.
Staff arrived to a half-working environment. Productivity lost, trust eroded.
Lift-and-shift moved your inefficient on-prem setup to the cloud and kept it inefficient.
Discovered mid-migration that it has hard-coded internal IPs. Six weeks of work missed it.
Migrated the workload, forgot the backup config. Now you have a cloud server with no recovery path.
Same rhythm every project. No surprises in the cutover window.
Inventory every workload. Dependency mapping. Decide lift-and-shift vs. replatform vs. refactor for each. Cost model built.
Target architecture documented. Networking, identity, security, backup all designed first. Diagrams reviewed by client.
Migrate a small, low-risk workload. Find the gotchas in a safe blast radius. Update the playbook.
Move in waves. Each wave has a defined window (usually Friday evening). Test, verify, monitor through the weekend.
Right-size instances, switch to reserved or savings plans, tag for cost allocation, set up alerts. The 'after the migration' part most firms skip.
Each has its time. We pick per workload, not per project.
| Lift-and-shift | Replatform | Refactor | |
|---|---|---|---|
| What it means | Move as-is to a cloud VM | Move + use a managed service | Rewrite for the cloud |
| Speed | Fast (days–weeks) | Medium (weeks–months) | Slow (months–quarters) |
| Cost in the cloud | Usually highest | Usually best balance | Usually lowest long-term |
| Risk in the move | Low | Medium | High |
| Best for | Tight deadlines, legacy systems | Databases, web apps with effort budget | Strategic apps with engineering team available |
Real numbers from a recent migration. Your mileage will vary; we model yours during assessment.
| On-prem (monthly) | Optimized cloud (monthly) | |
|---|---|---|
| Server hardware + lease | $8,400 | $0 |
| Power + cooling + colo | $1,800 | $0 |
| Backup hardware + tape | $1,200 | $340 (S3 Glacier) |
| Licensing (Windows Server CALs etc.) | $3,200 | $1,900 |
| Cloud compute (right-sized) | $0 | $5,100 |
| Cloud storage + bandwidth | $0 | $1,400 |
| DR site (second location) | $2,800 | $0 (built-in multi-AZ) |
| Total monthly run-rate | $17,400 | $8,740 |
Of migration waves completed in their declared window.
Due to a problem found post-cutover. We don't aim for zero — we aim for fast detection.
Typical after optimization phase, vs. naïve lift-and-shift.
Across all migrations in the last 5 years. We don't lose data.
“We migrated 18 servers and 6 databases to Azure in 11 weeks. Senator worked overnight on the cutover. Staff came in Monday morning, signed in to everything as usual, and never knew it was different infrastructure underneath.”
8–16 weeks for most 25–150 user firms. Larger or more complex environments can run 4–9 months. The assessment phase tells you which yours is.
For each workload, yes — usually a 2–4 hour cutover window. We schedule for Friday evenings and complete by Sunday so staff arrives Monday to a working environment.
We test each one in the cloud target before cutover. Apps with hard-coded assumptions get refactored or moved last with their own runbook.
After optimization, yes — typically 30–50% lower than equivalent on-prem total cost. Naive lift-and-shift can actually go up. Optimization is the difference.
Common and fine. We design hybrid setups regularly — some workloads cloud, some on-prem, connected through site-to-site VPN or ExpressRoute.
Tell us what you're running. We tell you a realistic timeline, cost band, and the gotchas we'd watch for in your environment.