Cloud Migration: How to Move to AWS, Azure, or GCP Without Downtime
Most businesses don’t fear cloud migration. They fear the downtime, the data loss, and the Monday morning call explaining why the application isn’t working.
Those fears are legitimate. Cloud migration done without a proper strategy produces exactly those outcomes. But cloud migration done correctly – with the right sequencing, the right architecture decisions, and the right rollback planning – produces zero downtime, zero data loss, and a significantly better infrastructure position than the one you started with.
This guide covers how to get there.
Why Businesses Migrate to the Cloud
Before the how, the why matters. Cloud migration is not inherently valuable. It’s valuable when it solves a specific problem your current infrastructure creates.
The most common legitimate reasons:
→ Scaling limitations.
On-premise infrastructure has a ceiling. When your traffic doubles, you buy more hardware. In the cloud, you configure autoscaling. The difference in operational agility is significant – especially for businesses with seasonal or unpredictable traffic patterns.
→ Operational overhead.
Managing physical servers, handling hardware failures, patching operating systems, maintaining data centres – this is expensive engineering time that produces no product value. Moving to managed cloud services converts capital expenditure into operational expenditure and redirects engineering effort toward what actually matters.
→ Disaster recovery.
Replicating data across geographic regions in the cloud is a configuration, not an infrastructure project. Multi-region disaster recovery that would cost months and significant resources on-premise is available as a managed service on every major cloud platform.
→ Developer velocity.
Managed databases, serverless functions, container orchestration, CI/CD integration – cloud platforms provide infrastructure primitives that accelerate development significantly when used well.
If your reason for migrating doesn’t map to one of these, revisit whether migration is actually the right move before starting.
The Five Migration Strategies (And Which One Fits Your Situation)
The industry uses a framework called the 5 Rs to classify cloud migration approaches. Knowing which one applies to each workload is the most important early decision.
1. Rehost (Lift and Shift).
Move your application to the cloud with no architectural changes. Same OS, same application stack, just running on cloud VMs instead of physical servers. Fastest migration path. Doesn’t capture the full value of cloud-native services but gets you off on-premise infrastructure quickly. Right for: legacy applications that can’t be easily refactored, initial migrations where speed matters more than optimisation.
2. Replatform (Lift, Tinker, and Shift).
Move to the cloud with minor optimisations – switching from self-managed MySQL to Amazon RDS, moving from a managed server to a PaaS application runtime. You’re not changing the core architecture, just swapping specific components for managed equivalents. Right for: applications where eliminating database or runtime management overhead has clear value without requiring a full rebuild.
3. Refactor (Re-architect).
Redesign the application to be cloud-native – breaking a monolith into microservices, moving to serverless functions, implementing event-driven architecture. The highest effort and the highest long-term value. Right for: applications where current architecture is genuinely limiting performance or scalability, and where the business case for a rebuild is clear.
4. Repurchase.
Replace the current application with a SaaS solution. Move from a self-hosted CRM to Salesforce. Move from on-premise email to Microsoft 365. Right for: commodity workloads where a SaaS solution covers the requirements without meaningful trade-offs.
5. Retire.
Decommission applications that are no longer needed. A cloud migration audit almost always reveals workloads nobody is actively using. Shutting them down before migration reduces scope and eliminates ongoing cloud spend on unnecessary workloads.
Most enterprise cloud migrations use all five strategies across different workloads. The mistake is applying one strategy to everything.
AWS vs. Azure vs. GCP: Choosing the Right Platform
The three major cloud platforms are broadly comparable in capability at this point. The choice between them should be driven by your specific context, not by marketing material.
→ Choose AWS if: your team already has AWS experience, your application ecosystem uses services with strong AWS integration (many open-source tools default to AWS), or you need the broadest global region coverage. AWS has the largest global infrastructure footprint and the deepest service catalogue.
→ Choose Azure if: your organisation is deeply invested in Microsoft technologies – Active Directory, .NET applications, Microsoft 365, Dynamics 365. Azure’s integration with the Microsoft ecosystem is significantly tighter than AWS or GCP. Azure is also the strongest choice for hybrid cloud scenarios where you’re maintaining some on-premise infrastructure alongside cloud.
→ Choose GCP if: your workloads are data-heavy and AI/ML-intensive. GCP’s BigQuery, Dataflow, and Vertex AI services are best-in-class for analytical workloads. GCP also has a strong Kubernetes story – Kubernetes was originally developed at Google, and GKE (Google Kubernetes Engine) is widely considered the most mature managed Kubernetes service.
Multi-cloud – using more than one platform – is a legitimate strategy for large enterprises with specific workload requirements across platforms. It’s not the right starting point for most organisations; it adds operational complexity that only makes sense when the benefits of platform-specific services clearly outweigh that overhead.
The Cloud Migration Process: Phase by Phase
Phase 1: Discovery and Assessment (Weeks 1–3)
Before moving anything, map what you have. Every application, every database, every integration, every dependency. This sounds obvious. It’s consistently underdone, and the gaps surface at the worst possible time – during migration.
Document for each workload:
- What the application does and who uses it
- Its technical stack (OS, runtime, database, dependencies)
- Its traffic patterns and peak load requirements
- Its integration dependencies (what it calls and what calls it)
- Its recovery requirements (how much downtime is acceptable, how much data loss is acceptable)
- Which of the 5 Rs applies to it
Classify workloads by migration complexity: simple (stateless applications, no complex dependencies), medium (stateful applications, some integrations), complex (high-availability requirements, complex data dependencies, real-time integrations).
Phase 2: Foundation and Landing Zone (Weeks 3–6)
Before migrating a single workload, build the cloud foundation it will land on. This includes:
→ Network architecture.
VPC/VNet design, subnet strategy, security groups, private connectivity back to any remaining on-premise infrastructure (VPN or dedicated circuit). Getting this wrong means re-architecting under live traffic later.
→ Identity and access management.
Who can access what in the cloud environment. Role-based access control, service accounts, secrets management. Security architecture defined before anything is deployed.
→ Monitoring and observability.
Logging, metrics, and alerting configured before workloads migrate. You want visibility from day one, not after something breaks.
→ Cost management.
Budgets, cost allocation tags, and spend monitoring set up before the meter starts running. Cloud costs without governance escalate quickly.
Phase 3: Pilot Migration (Weeks 6–9)
Migrate the lowest-risk, lowest-complexity workload first. Not because it’s the most valuable, but because it validates your migration process against reality before you apply it to workloads that matter.
What you learn in the pilot: gaps in your network configuration, dependencies you didn’t document in the assessment, monitoring blind spots, the actual time your migration process takes versus your estimate. Fix all of these before moving higher-risk workloads.
Phase 4: Wave Migration (Weeks 9–24, depending on scope)
Migrate workloads in waves, sequenced by dependency order. Don’t migrate an application before the database it depends on. Don’t migrate a service before the authentication service it calls.
Each wave follows the same pattern: migrate, validate, monitor for a stability period, then begin the next wave. Don’t compress the stability period. Issues that manifest 48 hours after migration are more common than issues that manifest immediately.
Phase 5: Cutover and Decommission
For stateful applications, the cutover is the highest-risk moment. A well-planned cloud migration uses blue-green deployment for cutover: run the old and new environments in parallel, shift traffic gradually (10%, 25%, 50%, 100%), and maintain the ability to roll back to the old environment until you’re confident the new one is stable.
Once a workload is fully migrated and stable, decommission the old infrastructure. Running both environments in parallel indefinitely doubles your infrastructure spend.
The Zero-Downtime Toolkit
These are the specific techniques that eliminate downtime during cloud migration:
→ Blue-green deployment. Two identical environments. Traffic shifts from old (blue) to new (green) incrementally. Instant rollback available at any point.
→ Database replication. Replicate your database to the cloud target in real time before cutover. At cutover, you’re switching the application connection string, not copying data under live traffic.
→ Feature flags. Route specific user segments or traffic percentages to the cloud environment before full cutover. Validate real-world behaviour with real traffic before committing.
→ DNS-based traffic shifting. Gradually shift DNS resolution from the old environment to the new one. Combined with a short TTL, this allows controlled, reversible traffic migration.
→ Strangler fig pattern. For large monolithic applications, migrate functionality piece by piece – routing specific endpoints to the new cloud infrastructure while the rest continues to serve from the old environment. The monolith shrinks gradually as the cloud version grows.
The Failure Points Nobody Warns You About
→ Dependency mapping gaps. The application you thought was standalone calls a service that wasn’t documented. That service isn’t migrated yet. The application breaks. Thorough discovery in Phase 1 prevents this.
→ Data migration underestimation. Moving terabytes of data takes time, and that time has to be accounted for in your cutover plan. Database replication handles this for production data. Don’t forget test data, configuration data, and blob storage.
→ Network latency between hybrid environments. During migration, some components are on-premise and some are in the cloud. Cross-environment calls add latency. If your application is latency-sensitive, sequence your migration to minimise the window where components are split.
→ Cloud cost surprises. Data egress fees, unexpected service costs, over-provisioned instances. Implement cost monitoring before migration starts, not after your first cloud bill arrives.
→ Skills gap. The team that knows your application may not know cloud infrastructure. The team that knows cloud infrastructure may not know your application. Build both capabilities before cutover, not during it.
Frequently Asked Questions (FAQs)
How long does a cloud migration take?
A simple workload (single application, no complex dependencies) can migrate in 2–4 weeks. A medium-complexity migration (multiple applications, database migrations, some integrations) typically takes 3–6 months. A large enterprise cloud migration covering dozens of workloads and complex dependencies can run 12–18 months. The primary variables are the number of workloads, dependency complexity, data volume, and how much refactoring is required.
What is the difference between lift and shift and cloud-native migration?
Lift and shift (rehost) moves your application to cloud VMs with no architectural changes. It’s fast but doesn’t leverage cloud-native services. Cloud-native migration (refactor) redesigns the application to use managed cloud services, serverless, or microservices architecture. It takes longer but delivers better scalability, resilience, and operational efficiency.
Can you migrate to the cloud without any downtime?
Yes, for most workloads. Blue-green deployment, database replication, DNS-based traffic shifting, and the strangler fig pattern are proven techniques for zero-downtime cloud migration. The critical requirements are a well-planned cutover process, parallel environment operation during transition, and tested rollback capability.
How do I choose between AWS, Azure, and GCP?
Choose AWS for broadest service coverage and global reach. Choose Azure if your organisation is invested in Microsoft technologies (Active Directory, .NET, Microsoft 365, Dynamics). Choose GCP if your workloads are data-intensive or ML-heavy. Base the decision on your existing technology ecosystem and team expertise, not on which platform markets itself most aggressively.
What is a cloud migration landing zone?
A landing zone is the pre-configured cloud environment your workloads migrate into – network architecture, identity and access management, security controls, monitoring, and cost management all set up before any workload moves. A well-designed landing zone prevents the most common cloud migration problems: security gaps, network misconfiguration, and cost surprises.
At Evolution Infosystem, our cloud migration practice covers the full lifecycle: assessment, landing zone design, wave migration, and post-migration optimisation on AWS, Azure, and GCP. We’ve migrated applications ranging from single-tier web apps to complex enterprise platforms with real-time integrations. If you’re planning a cloud migration and want an honest assessment of your approach, let’s talk.