Cloud migration is one of the most expensive, most disruptive, and most frequently botched initiatives in enterprise technology. The pattern is consistent: a business decides to move to the cloud, hires a team or agency, spins up the infrastructure, and six months later is paying three times the original cloud bill with systems that are less reliable than what they replaced.
The real cause: skipped discovery
Every failed migration we've been called in to rescue shared one common thread — the discovery phase was either skipped entirely or treated as a checkbox. Teams jumped straight to provisioning infrastructure without mapping their actual workloads, their dependencies, or their compliance requirements. You cannot design a migration strategy for a system you don't fully understand.
Lift-and-shift is not a strategy
Rehosting a legacy application into a VM in the cloud gives you the worst of both worlds: cloud pricing with on-premises performance. The economics only work when you re-architect to take advantage of managed services, auto-scaling, and serverless patterns. That requires upfront investment in understanding what the application actually does under load.
What a migration that works looks like
Every successful migration we've run starts with a six to eight week discovery phase. We map every service, every database dependency, every integration point, and every compliance boundary before a single resource is provisioned. We then build a phased migration plan with rollback checkpoints at each stage. Zero-downtime is a requirement, not an aspiration — and it's only achievable when the plan accounts for real traffic patterns, not just happy-path scenarios.
The metric that matters
Don't measure migration success by whether the systems are 'in the cloud.' Measure it by: Is the bill predictable? Are deployments faster? Can you scale during a traffic spike without human intervention? If the answer to any of those is no, the migration isn't finished.