Cloud Migration Services

Cloud migration services start with one idea: there is no single best approach. Each application gets its own treatment. The industry commonly describes a set of "Rs", and the AWS Prescriptive Guidance (opens in a new tab) library and the Microsoft Cloud Adoption Framework for Azure (opens in a new tab) both document migration patterns along these lines.

Some frameworks add a seventh option, relocate, for moving whole virtualization platforms. Whatever the label, insist that every application is assigned one strategy and a reason.

Surprises during cutover almost always trace back to something missed in discovery. A sound assessment builds a dependency map, not just a server list. Typical reasons to move include a data center lease or hardware refresh, resilience needs, demand peaks and unsupported software.

• Inventory: applications, servers, databases, licenses and owners.
• Dependencies: which systems talk to which, over what ports and on what schedule, including batch jobs and file transfers nobody remembers.
• Performance baselines: how much CPU, memory, storage and network each system actually uses, so sizing in the cloud is based on measurement.
• Licensing: which software licenses allow cloud use and under what terms.
• Data profile: volumes, growth, sensitivity and how long a copy will take over your network.
• Business calendar: month-end, seasonal peaks and freeze periods that block cutovers.

Large estates are moved in waves: groups of related applications migrated together. Early waves contain low-risk systems so the team builds the foundation, tooling and confidence before the critical applications arrive.

1. Build the landing zone with identity, networking, logging and guardrails in place.
2. Pilot wave: move one or two modest systems end to end and record what you learn.
3. Replicate data continuously so the final switch only needs to move the last small changes.
4. Test in the new environment: functional, performance, security and failure testing before cutover, not after.
5. Rehearse the cutover with a written runbook, owners for each step and a clock.
6. Switch traffic at a quiet time, often by gradually shifting DNS or load balancer weights.
7. Keep the old environment available for a defined period with a tested way back.
8. Hypercare: extra monitoring and rapid support for the first days or weeks.

Rollback is a design requirement. Decide before cutover what conditions trigger it, who makes the call and how long it takes. Downtime then becomes a plan rather than a hope. For data-heavy moves, see also data migration services.

• Hidden dependencies: a forgotten integration breaks after cutover. Reduce with dependency mapping and traffic observation.
• Data loss or corruption: reduce with checksums, reconciliation counts and rehearsed restores.
• Performance surprises: an application written for a fast local network becomes chatty and slow across locations. Reduce with load testing and placing tightly coupled systems together.
• Security gaps: a rushed move leaves storage open or permissions too wide. Reduce with a hardened landing zone and automated configuration checks.
• Cost shock: servers sized like the old hardware and left running continuously. Reduce with right-sizing and budgets from the first wave.
• Skills gaps: the team can build but not operate. Reduce with training and runbooks during the program.

Aligning the program with the reliability, security and cost principles in the AWS Well-Architected Framework (opens in a new tab), the Azure Well-Architected Framework (opens in a new tab) or the Google Cloud Well-Architected Framework (opens in a new tab) gives reviewers a neutral checklist for each wave.

Migration widens exposure temporarily: data is copied, networks are bridged and old and new environments run side by side. Protect that period explicitly.

• Encrypt data in transit during transfer and at rest in the target.
• Use temporary, least-privilege migration credentials and revoke them afterward.
• Scan and patch systems before moving them, not after.
• Securely wipe or decommission old storage and keep evidence of it.
• Preserve audit logs and retention obligations across the move.

The Cloud Security Alliance guidance (opens in a new tab) and the AWS Shared Responsibility Model (opens in a new tab) help confirm which controls move with you and which are now your team's job. Pair the program with cloud security services when internal capacity is thin.

Migration is the moment to avoid carrying waste forward. Retire idle servers, size to measured use rather than old hardware, and pick regions with attention to the energy sources each provider reports. After the move, schedule non-production environments to power down and review utilization regularly.

Replacing a fleet of lightly used physical servers with shared, well-utilized cloud capacity can reduce waste, but only if workloads are sized and managed with care. The Principles of Green Software Engineering (opens in a new tab) offer a practical framing.

• Healthcare: a practice-management system replatformed onto a managed database, with strict access logging and a tested restore before cutover.
• Education: a student portal rehosted ahead of enrollment season, with refactoring of the busiest components scheduled for the following term.
• Logistics: a tracking application with heavy batch jobs moved in a wave after its dependencies, with parallel running during peak shipping weeks avoided.
• Professional services: file servers and email repurchased as software-as-a-service while a specialized billing system is retained on site for now.

These are illustrative, not Kramate client results.

Data location and cross-border transfer rules shape target-region choices. Confirm details with legal counsel.

• USA: sector rules such as HIPAA for health data, financial regulator expectations and state privacy laws; public-sector work may need specific authorization programs.
• UK: UK GDPR and Data Protection Act 2018, including international transfer rules; regulated financial firms face outsourcing and resilience expectations.
• Australia: Privacy Act 1988 and Australian Privacy Principles, with extra obligations for finance and critical infrastructure.
• Singapore: Personal Data Protection Act and sector regulator guidance on technology risk and outsourcing.

Cutovers are scheduled around local business hours, which is where time zones matter. Agree who is on call in each region for the cutover window.

Cloud migration services carry a one-time cost and a running cost. Plan for both.

• Scope: number of applications, servers and databases, and their complexity.
• Strategy mix: rehosting is faster to execute, refactoring costs more upfront.
• Data volume and transfer method.
• Parallel running: paying for old and new environments during the transition.
• Testing depth and rehearsal cycles.
• Licensing changes and any software replacement.
• Training and operating-model changes.
• Target-environment running costs: compute, storage, network traffic, managed services and support.

Fixed-price fits a well-defined wave, a dedicated team fits a multi-wave program with changing priorities, and hourly fits assessments or tuning. Keep a reserve for discovered dependencies, and plan cloud cost optimization for after the move.

1. A discovery phase that produces a dependency map before any fixed quote.
2. Per-application strategy with reasons, not one approach for everything.
3. A rehearsed cutover and rollback plan for each critical system.
4. Security built in: landing zone, scanning and credential hygiene.
5. Post-migration support and knowledge transfer to your team.
6. Provider neutrality or clear disclosure of partnerships.
7. Visible progress through demos and wave reports.

A dedicated project manager coordinates each wave, with daily updates on Slack or Teams and a demo or progress review at the end of every two-week round. An NDA comes first, and all intellectual property, including runbooks and automation scripts, is transferred to you. See how we run a project for the full process.

Work happens under least-privilege access on encrypted devices, with peer review and regular security testing. Four to six hours of US Eastern overlap and full working-day overlap with the UK, Australia and Singapore help with cutover scheduling.

• AWS Prescriptive Guidance (opens in a new tab)Amazon Web Services
• Microsoft Cloud Adoption Framework for Azure (opens in a new tab)Microsoft
• AWS Well-Architected Framework (opens in a new tab)Amazon Web Services
• Microsoft Azure Well-Architected Framework (opens in a new tab)Microsoft
• Google Cloud Well-Architected Framework (opens in a new tab)Google Cloud
• CSA Security Guidance for Cloud Computing (opens in a new tab)Cloud Security Alliance
• AWS Shared Responsibility Model (opens in a new tab)Amazon Web Services
• Principles of Green Software Engineering (opens in a new tab)Green Software Foundation