CLOUD MIGRATION
Move to the Cloud Without
Breaking What Works
Structured, low-disruption migration of your workloads, data and applications to AWS, Azure or Google Cloud, with a plan built around your systems, your timelines and your risk tolerance.
Our Decade long experience, validated in numbers
Enterprise Customers
OVERVIEW
Migration is a transition, not a cutover
Most cloud migrations fail not because of technology but because of planning. Workloads are lifted without being assessed, dependencies are missed, and data migrations run without a rollback strategy. We run cloud migrations as structured engineering engagements, starting with a thorough assessment of your current environment, followed by a phased migration plan that moves workloads progressively, validates at each stage, and keeps your business running throughout.
Trusted by Leading Enterprises
HOW WE MIGRATE
Our Migration approach
Assess
Assess Full inventory of your current environment: applications, dependencies, data volumes, compliance requirements, and integration points.
Plan
Plan Migration strategy per workload (rehost, replatform, refactor, retire or retain), timeline, rollback procedures, and success criteria defined upfront. No surprises mid-migration.
Migrate
Migrate Workloads moved in phases, starting with lower-risk systems. Each migration is validated against performance and availability baselines before the next phase begins.
Optimize
Optimize and Stabilize Post-migration performance tuning, cost optimization, security hardening and monitoring setup. We do not hand over and walk away.
MIGRATION TYPES WE HANDLE
What we migrate
- On-premise to cloud (lift and shift, replatform, refactor)
- Data center exit and consolidation
- Cross-cloud migration (AWS to Azure, GCP to AWS, etc.)
- Legacy application re-hosting to cloud-native infrastructure
- Database migration (on-premise SQL, Oracle, legacy NoSQL to managed cloud databases)
- SaaS platform migration and environment consolidation
PLATFORMS AND TOOLS
Our Migration approach
Cloud Platforms:
AWS (including AWS Migration Hub, DMS, SMS)
Microsoft Azure (Azure Migrate, Azure Database Migration Service)
Google Cloud (Migrate for Compute Engine)
Infrastructure as Code:
Terraform
AWS CDK
Database Migration:
AWS DMS
Azure Database Migration Service
pgloader
Striim
Assessment and Planning:
AWS Migration Evaluator
Azure Migrate
Custom dependency mapping tooling
Everything you need to know
Most cloud migrations fail because of planning gaps rather than technology limitations: workloads get lifted without a proper assessment, dependencies between systems are missed, and data migrations run without a rollback strategy. A structured migration starts with a full assessment of the current environment before any workload is moved, so dependencies and risks are known upfront instead of discovered mid-migration.
Rehost ("lift and shift") moves a workload to the cloud with minimal changes, replatform makes targeted optimizations during the move (such as switching to a managed database), and refactor rearchitects the application to be cloud-native. The right strategy is chosen per workload rather than applied uniformly, since a legacy system with tight timelines might get rehosted first while a core application earmarked for long-term investment gets refactored.
A cloud migration assessment covers a full inventory of the current environment: applications, dependencies between systems, data volumes, compliance requirements, and integration points. This assessment is what determines the migration strategy per workload (rehost, replatform, refactor, retire, or retain) and surfaces risks before they turn into mid-migration surprises.
Workloads are migrated in phases, starting with lower-risk systems, with each phase validated against performance and availability baselines before the next one begins. Rollback procedures and success criteria are defined upfront during the planning stage, so if a phase doesn't meet its baseline, there's a clear path back rather than a forced continuation.
Yes, cross-cloud migration between providers such as AWS, Azure, and Google Cloud follows the same assessment and phased migration approach used for on-premise to cloud moves. It also applies to data center exits and consolidations, and to SaaS platform migrations where multiple environments need to be consolidated.
After migration, the process includes performance tuning, cost optimization, security hardening, and monitoring setup rather than ending at cutover. This stabilization phase is treated as part of the migration itself, since a workload that's technically "moved" but not tuned for its new environment tends to run inefficiently or insecurely.
Where these capabilities apply