Cloud migration — how to hire the right team
Most cloud migrations don't fail because the cloud is hard. They fail because the team scoped the move wrong, hired the wrong roles, or skipped the assessment and went straight to lifting servers. This guide walks through why companies migrate, how to pick a migration strategy for each application, what AWS, Azure, and GCP actually mean for your project, a phased rollout plan that won't blow up production, real cost numbers, the risks worth planning for, and exactly who to hire to run it.
In This Guide
- 1. Why companies migrate to the cloud now
- 2. The 6 Rs of cloud migration
- 3. AWS vs Azure vs GCP — which cloud fits your migration?
- 4. Assessment and landing zone: build this before you move anything
- 5. A phased migration plan: pilot, then waves
- 6. Cost and FinOps: what migration actually costs
- 7. Risks — and how to de-risk each one
- 8. The roles you actually need to hire
- 9. How to hire and vet cloud migration talent
- 10. Why an India-based team fits cloud migration work
- 11. Frequently asked questions
1. Why companies migrate to the cloud now
Three pressures push most migrations onto the roadmap at the same time: cost, scale, and an on-premise footprint that's aging out from under you.
Cost. Running your own data center means paying for peak capacity every day of the year, even though most workloads spend the majority of their time well under that peak. Cloud lets you pay for what you use and scale down overnight or on weekends. It also converts a large upfront hardware purchase (capex) into a monthly operating cost (opex), which finance teams generally prefer because it's easier to forecast and doesn't tie up cash in servers that depreciate.
Scale. Provisioning a new server on-prem can take weeks: order the hardware, wait for it to arrive, rack it, configure it, patch it. In the cloud, the same capacity is available in minutes. For any business with seasonal traffic, a product launch, or growth that isn't perfectly predictable, that difference in provisioning time is the difference between meeting demand and losing customers to a slow site.
Reliability. A single data center is a single point of failure. Major cloud providers run multiple availability zones per region and dozens of regions worldwide, so a well-architected application can survive a data center outage without users noticing. Building that kind of redundancy yourself costs far more than renting it.
On-premise end of life. A lot of migrations get forced by a calendar date, not a strategy meeting. Windows Server and SQL Server versions fall out of extended support on a schedule, VMware's licensing changes under Broadcom pushed monthly costs up sharply for a lot of companies, and aging hardware eventually needs a refresh that costs nearly as much as three years of cloud spend. When the choice is "replace the servers" or "move to the cloud," the cloud usually wins on both cost and long-term flexibility.
2. The 6 Rs of cloud migration
Not every application should move to the cloud the same way. The "6 Rs" framework gives you six strategies, and picking the right one per application (not per project) is what keeps a migration on budget.
Rehost (lift and shift)
Move the application to cloud virtual machines with little or no code change. Fastest and cheapest way to get out of a data center. Good for applications you don't plan to invest more engineering time in, or for a first wave that proves the migration process works before you tackle harder applications.
Replatform (lift, tinker, and shift)
Move the application but swap a handful of components for managed cloud services, most commonly moving a self-hosted database to a managed one like Amazon RDS or Azure SQL Database. You keep the application logic largely intact but cut the operational burden of patching and backing up the database yourself.
Refactor (re-architect)
Rebuild the application to take advantage of cloud-native patterns: breaking a monolith into services, moving to containers, using managed queues and event buses instead of a single database as the integration point. Costs the most up front and takes the longest, but it's the strategy that unlocks real elasticity and usually the lowest run-rate cost over a few years.
Repurchase (replace with SaaS)
Some applications aren't worth migrating at all, they're worth replacing. A self-hosted CRM or ticketing system is a common candidate for repurchasing with a SaaS product instead of migrating the old one. This removes the application from your infrastructure entirely.
Retire
Discovery almost always turns up applications nobody uses anymore, or that duplicate another system. Retiring them before migration is free money: no compute cost, no migration effort, one less thing to secure and patch. It's common for 10 to 20% of an application portfolio to be retirement candidates once someone actually looks.
Retain
Not everything needs to move on the first pass, or ever. An application tied to specialized hardware, one facing a near-term end of life anyway, or one with a compliance requirement to stay on-premise, can sit in a "retain" bucket and get revisited later. Forcing every application into the cloud on the same timeline is how migrations run over budget.
Score every application in your portfolio against these six options during discovery, rather than deciding on a single strategy for the whole migration. A typical enterprise portfolio ends up 40 to 60% rehost, 20 to 30% replatform, and the rest split across refactor, repurchase, retire, and retain.
3. AWS vs Azure vs GCP — which cloud fits your migration?
The "best" cloud provider is the one that fits your existing licensing, your team's skills, and your workload type. Here's how the three major providers actually differ for a migration project:
| Provider | Strongest fit | Migration tooling | Watch out for |
|---|---|---|---|
| AWS | Broadest service catalog, largest talent pool, mature for almost any workload type | AWS Migration Hub, Application Migration Service, Database Migration Service | Pricing and service sprawl can get complex without disciplined tagging |
| Azure | Companies already deep in Microsoft licensing — Windows Server, SQL Server, Active Directory, Office 365 | Azure Migrate, hybrid benefit licensing that reuses existing Windows/SQL licenses | Hybrid-benefit savings only apply if your existing licensing is eligible |
| GCP | Data and analytics-heavy workloads, Kubernetes-native teams, machine-learning pipelines | Migrate to Virtual Machines, BigQuery Data Transfer Service | Smaller enterprise-support ecosystem and talent pool than AWS or Azure in most markets |
If you're already running mostly Windows and SQL Server on-premise, Azure's hybrid-benefit licensing alone can shift the total cost comparison in its favor. If you're starting closer to a blank slate, AWS gives you the widest range of managed services to pick from later without a second migration. If your workload is genuinely data-heavy, or your team already lives in Kubernetes, GCP is worth a serious look even though it has a smaller ecosystem. Multi-cloud is possible but adds real operational overhead, most companies are better off picking one primary provider for a migration and treating a second cloud as the exception, not the plan.
4. Assessment and landing zone: build this before you move anything
The single most common migration mistake is skipping assessment and going straight to moving servers. Two things need to happen first.
Discovery and dependency mapping. You need a real inventory of every application, server, and database, plus how they talk to each other. Tools like AWS Application Discovery Service, Azure Migrate, or agent-based tools like Device42 scan your environment and build this map automatically. Without it, teams routinely migrate an application only to discover in production that it silently depended on a database three racks over that never moved. Budget two to six weeks for discovery on a portfolio of any real size, and treat the output as the source of truth for wave planning, not a guess based on a spreadsheet someone made two years ago.
Landing zone design. A landing zone is the pre-built foundation your applications land on: the account or subscription structure, network layout (VPC or VNet), identity and access management roles, logging and monitoring baseline, and security guardrails like mandatory encryption and blocked public storage buckets. Building this properly before the first application moves means every subsequent wave lands on infrastructure that's already secure and already following your naming and tagging conventions, instead of every team improvising its own setup and creating a mess to clean up later. A solid landing zone typically takes three to six weeks to design and stand up, and it's worth every day of it.
Run a TCO calculation alongside discovery using your provider's cost calculator, fed with real usage data from your current environment rather than sales-brochure assumptions. This is what tells you whether the migration actually saves money on your specific workloads, and by how much, before you commit budget to the project.
5. A phased migration plan: pilot, then waves
Moving 80 applications at once is how migrations turn into outages. A phased plan spreads the risk and gives you a working process before you bet the whole portfolio on it.
Phase 0: Discovery and landing zone (weeks 1–6)
Application inventory, dependency mapping, 6 Rs scoring per application, and the landing zone build described above. No production workload moves during this phase.
Phase 1: Pilot (weeks 6–10)
Pick one or two applications that are low-risk (not customer-facing, or with a straightforward rollback) but representative of the harder ones still to come. The goal isn't to migrate something easy for the sake of it, it's to validate your process end to end: discovery accuracy, migration tooling, cutover runbook, and rollback plan, on something real.
Phase 2: Wave planning
Group the remaining applications into waves based on dependencies (applications that talk to each other move together), business risk (lower-risk applications go earlier), and team capacity. A typical wave is 5 to 15 applications and runs 4 to 8 weeks from prep to cutover.
Phase 3: Execute waves
Each wave follows the same rhythm: prep and testing, a defined cutover window (often overnight or on a weekend), validation against the source system, and a monitoring period before you call it done. Cutover windows and rollback criteria get agreed and written down before the wave starts, not improvised during it.
Phase 4: Optimize and decommission
Once an application is stable in the cloud, right-size the instances against real usage, apply reserved pricing or savings plans, and formally decommission the old on-premise hardware. Skipping this phase is exactly how companies end up paying for a data center and a cloud bill at the same time for a year longer than necessary.
6. Cost and FinOps: what migration actually costs
Two cost lines matter here, and they're easy to mix up: the one-time cost of running the migration project, and the ongoing cost of the cloud environment afterward.
| Migration scope | Typical timeline | Team size |
|---|---|---|
| Single application, rehost | 4–8 weeks | 1–2 engineers |
| Mid-size portfolio (10–30 apps) | 4–8 months | 3–5 engineers + 1 architect |
| Full data center exit (50–150+ apps) | 9–18 months | 6–10 engineers + architect + DBA |
The hidden costs are what blow up budgets after the migration is technically "done." Data egress fees, what a provider charges to move data out of its cloud or between regions, add up fast on large data sets and are easy to underestimate during planning. Orphaned resources, servers, snapshots, and load balancers left running after a wave completes because nobody tore them down, quietly inflate the monthly bill for months. Licensing for software that wasn't designed for cloud pricing (some legacy enterprise software charges per-core in ways that don't map cleanly to virtual CPUs) can also surprise you.
FinOps practices keep the ongoing bill honest: tag every resource by team and project from day one so cost is traceable, review spend monthly and not just at renewal, and move stable workloads onto reserved instances or savings plans once usage patterns settle (this alone typically cuts compute cost 30 to 50% versus on-demand pricing). A cloud bill with no tagging discipline is a cloud bill nobody can explain six months later.
7. Risks — and how to de-risk each one
Downtime. Run the source and target systems in parallel through the cutover window, use a blue-green or canary pattern so traffic can shift back in minutes, and schedule cutovers for your lowest-traffic hours. Keep DNS time-to-live low in the weeks before cutover so a rollback actually propagates fast if you need it.
Data integrity. For any database migration, validate row counts and checksums between source and target before you cut traffic over, and use change-data-capture or dual-write during the transition period so no writes get lost between the last sync and the cutover moment. A freeze window on writes to the source system during the final sync removes the most common source of data-loss surprises.
Security misconfiguration. Cloud breaches are disproportionately caused by misconfigured storage buckets and over-broad IAM permissions, not exotic attacks. Bake least-privilege IAM roles, encryption at rest and in transit, and automated misconfiguration scanning into the landing zone from the start, and run a security review before each wave goes live, not after an incident.
No rollback plan. Every cutover needs a written, tested rollback runbook with clear go/no-go criteria decided in advance, not debated in the moment. Keep the source system running (not decommissioned) for a defined period after cutover, typically two to four weeks, so a rollback is a real option and not just a hope.
8. The roles you actually need to hire
A migration doesn't need a large team, it needs the right roles at the right moments. Most companies run this as a dedicated team for the length of the project rather than piecing it together from freelancers. Here's what each one actually does and when you need them.
- Solution architect — designs the target architecture, scores applications against the 6 Rs, and owns the landing zone design. Needed heaviest during discovery and assessment, then part-time through execution as a decision-maker for edge cases. See hire a solution architect.
- Cloud engineer (AWS/Azure) — builds the landing zone, sets up networking and IAM, and executes the actual migration of servers, storage, and applications. This is the core execution role for most of the project. See hire an AWS cloud engineer or hire an Azure cloud engineer.
- DevOps engineer — builds the CI/CD pipeline and infrastructure-as-code (Terraform, usually) so environments are reproducible and every future change goes through a pull request, not a manual console click. Needed from the landing zone build onward, and stays on after migration to keep deployment automated. See hire a DevOps engineer.
- Site reliability engineer (SRE) — sets up monitoring, alerting, and on-call once workloads are live in the cloud, and owns the incident response process for the newly migrated systems. Most valuable in the optimize phase and for ongoing operations after migration. See hire a site reliability engineer.
- Database administrator (DBA) — handles schema conversion, replication setup, and data validation for database migrations. Often brought in on a fixed-term basis just for the database cutover window, since this is the highest-stakes part of most migrations and the hardest to reverse if it goes wrong.
Rate bands through a managed staffing partner, all-in with no separate recruitment or visa fee stacked on top:
| Level | Monthly (Managed) | Hourly Equivalent | US Market Equivalent |
|---|---|---|---|
| Associate cloud/DevOps engineer | from $1,800/mo | ~$18/hr | $6,000–$8,000/mo |
| Mid-level engineer | from $2,500/mo | ~$25/hr | $9,000–$12,000/mo |
| Senior cloud/DevOps engineer or SRE | from $3,200/mo | ~$35/hr | $12,500–$17,000/mo |
| Solution architect / lead | from $4,500/mo | ~$50/hr | $16,000–$22,000/mo |
A blended five-person migration team runs around $11,000/mo through TechTeamsOnline, against roughly $45,000/mo for an equivalent local team, about a 75% saving you can put toward more headcount or a longer runway.
9. How to hire and vet cloud migration talent
Cloud migration is one of the easiest technical skills to overstate on a resume, because "AWS experience" can mean anything from clicking through the console once to running a 100-application data-center exit. Here's how to tell the difference in an interview.
Ask for a specific migration story, not a general one. "Walk me through a migration you led, start to finish" surfaces far more than "do you have AWS experience?" Listen for specifics: what broke, how they found out, what they changed in the runbook afterward. A candidate who can only describe the happy path hasn't actually run a cutover under pressure.
Treat certifications as a floor, not proof. AWS Solutions Architect, Azure Administrator, and similar certifications show a candidate has studied the material. They don't show the candidate has debugged a failed replication job at 2 AM. Use certifications to filter a candidate pool, then vet the rest with real scenarios.
Run a live design exercise. Give the candidate a simplified version of your actual environment (a web app, a database, a handful of dependencies) and ask them to design the landing zone and pick a migration strategy for each component, out loud. Good candidates ask clarifying questions before proposing an architecture and can explain trade-offs when you change a constraint mid-conversation. Weak candidates jump straight to a solution without asking what the business actually needs.
Check references on completed migrations specifically. Ask a previous manager or client one direct question: "Did their migration go live on schedule, and if not, why?" This single question filters out a lot of talk-heavy, execution-light candidates fast.
Avoid hiring purely off a resume with a long list of cloud service names. The strongest signal is always a specific, detailed story about one migration that had a real complication in it.
10. Why an India-based team fits cloud migration work
India isn't just a cheaper place to hire cloud engineers, it's genuinely well suited to the shape of migration work specifically.
The cost math is real. A US senior cloud or DevOps engineer commonly runs $140,000 to $185,000 a year in base pay. An India-based senior engineer through a managed provider runs around $3,200 a month, roughly $38,400 a year, for comparable production experience, typically 60 to 75% less. A blended five-person migration team costs about $11,000 a month versus roughly $45,000 a month for an equivalent US team, a saving you can redirect into a longer runway or a bigger team.
The talent pool is deep, and it's proven at scale. India has 4.3 to 5.8 million software developers, and 174 of the Fortune Global 500 run more than 390 engineering centers there, employing over 950,000 professionals. Bengaluru and Hyderabad host AWS, Microsoft Azure, and Google Cloud engineering teams directly on the ground, so the cloud expertise you're hiring isn't secondhand, it's the same talent pool the providers themselves draw from. India also holds the world's highest concentration of CMMI Level 5 and ISO 27001 certified IT organizations, which matters for a project that touches your production infrastructure and security posture.
Cutover windows fit the time-zone gap instead of fighting it. India sits 9.5 to 10.5 hours ahead of US time zones. A migration cutover, which you'd normally schedule for a low-traffic overnight window anyway, lands naturally inside a normal working day for an India-based team. Instead of asking your own engineers to run a 2 AM cutover, you hand it to a team that's awake, alert, and at their desk during that exact window, then get a status update and a clean handoff when your own team logs on the next morning. On a shifted schedule (roughly 11 AM to 8 PM IST), you still get about 2.5 hours of daily live overlap with US-East for standups and unblocking, and around 4.5 hours with the UK.
English and IP protection aren't afterthoughts. English is the working language of engineering education and the Indian IT industry by default, so architecture discussions, runbooks, and code reviews happen in plain English, not through a translation layer. On the legal side, standard work-for-hire contracts with IP-assignment clauses mean every Terraform module, pipeline, and runbook built during your migration belongs to you from the first commit, backed by India's Digital Personal Data Protection Act 2023.
The honest objection worth addressing directly: quality varies by provider, not by geography. The rate reflects India's cost of living, not a lower engineering bar, but that's only true if you hire through a provider that vets for real migration experience rather than resume keywords. That's exactly the vetting process covered above, and it's what a managed partner should be doing on your behalf before a candidate ever reaches your interview. If you're weighing India against building the team locally or through another destination, build your team in India walks through the full picture.
11. Frequently asked questions
How long does a cloud migration usually take?
A single application rehost can close in 4 to 8 weeks. A full data-center exit with 50 to 150 applications typically runs 9 to 18 months once you include discovery, pilot, waves, and decommissioning. The biggest driver of a longer timeline is how tangled your application dependencies are, not the cloud work itself.
What is the difference between rehosting and refactoring?
Rehosting moves an application to the cloud with little or no code change, usually a lift-and-shift onto virtual machines. Refactoring rebuilds the application to use cloud-native services. Rehosting is faster and cheaper up front; refactoring costs more now but usually costs less to run for years afterward.
Should I hire a cloud engineer, a DevOps engineer, or a solution architect first?
Start with a solution architect for the assessment and landing zone design, even on a short engagement. Once the target architecture is set, bring in cloud and DevOps engineers to build the landing zone and execute the waves. Hiring execution talent before the architecture is decided usually means redoing the work.
How much does it cost to hire a cloud migration team in India?
Through TechTeamsOnline, an associate cloud engineer starts around $1,800/mo, mid-level around $2,500, a senior cloud or DevOps engineer around $3,200, and a solution architect or lead around $4,500. A blended five-person migration team runs about $11,000/mo, against roughly $45,000/mo for an equivalent US team.
Which cloud provider is best for migration: AWS, Azure, or GCP?
There's no universal answer. Azure is usually easiest if you're deep in Microsoft licensing already. AWS has the broadest service catalog and the largest migration-tooling ecosystem. GCP tends to win for data and analytics-heavy workloads and Kubernetes-native teams.
How do I avoid downtime during a cloud migration cutover?
Run source and target systems in parallel during a defined cutover window, keep DNS time-to-live short beforehand, and use a blue-green or canary pattern so you can shift traffic back in minutes if something breaks. Schedule the cutover for your lowest-traffic window.
What's the biggest hidden cost in a cloud migration budget?
Data egress fees and orphaned resources. Moving large data sets out of a provider gets billed per gigabyte, and servers, snapshots, and load balancers left running after a wave completes quietly inflate the monthly bill for months before anyone notices.
Can an India-based team run our cloud migration cutover overnight?
Yes. India sits 9.5 to 10.5 hours ahead of US time zones, so a normal workday in Bengaluru or Hyderabad covers the entire US night. Cutovers, usually scheduled for low-traffic hours anyway, land naturally inside an India team's working day instead of forcing your own engineers into a 2 AM shift.
Do I need a database administrator for a cloud migration?
If you're moving a production database of any real size, yes, at least for the migration window. Schema conversion, replication setup, and data validation are specialist work, and a mistake here is the hardest kind to reverse. Many teams bring in a DBA on a fixed-term basis just for the database cutover.
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