01
200+
VMs migrated
Datacenter exit
Existing on-prem estate (VMware, OpenStack, hosted bare-metal) migrating to AWS / Azure / GCP. Wave-by-wave migration with documented dependencies, dual-running windows, and explicit rollback per wave.
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Platform & Cloud · FOUNDATION + SKYWAY
Cloud Migration.
Strangler-fig migrations from on-prem and legacy clouds — staged in 5–15% increments with documented rollback at every cutover. Lift-and-shift where the workload warrants it, replatform where it doesn’t, and rearchitect where the existing substrate is unsalvageable.
- Practice
- Platform & Cloud
- Department
- FOUNDATION + SKYWAY
The problem
Most cloud migrations are a re-hosting bill with a transformation slide deck.
The familiar pattern: a discovery phase that becomes an estimation gauntlet; a wave plan that's optimistic on dependencies and pessimistic on rollback; a cutover that spends a weekend running parallel writes nobody validated; a post-migration cost shape that's higher than the on-prem baseline because lift-and-shift preserved the worst architectural decisions; and three years of accreted technical debt before someone proposes a re-migration. The cloud isn't the failure — the migration discipline is.
We migrate the way bridges are inspected and replaced — increment by increment, with documented rollback at every stage. Discovery produces an honest workload-by-workload disposition (lift, replatform, rearchitect, retire). Cutover happens through dual-writes and traffic shadowing, with explicit go / no-go gates. The result is a migration that lands without incident — and a post-migration architecture that compounds value rather than continuing the on-prem failure modes in a more expensive cloud.
Where it ships
5 use cases, in production.
Specific applications we’ve built and operated. Not speculative — every example below is grounded in a real shipped engagement.
- 02
Cloud-to-cloud migration
AWS → Azure / GCP, or consolidation across acquisitions. Database replication, IAM remap, network re-architecture, and observability re-platforming with named cutover windows.
- 03
Replatform vs rearchitect assessment
Workload-by-workload disposition. We tell you which workloads benefit from replatforming (containerization, managed services), which need rearchitecting (monolith decomposition, async patterns), and which are fine as-is.
- 04
0
data loss across 240+ migrations
Database migration
Oracle → Postgres, SQL Server → Aurora, on-prem MongoDB → Atlas. Schema conversion, dual-write windows, query-pattern remediation, and cutover under documented rollback.
- 05
Mainframe and legacy modernization
Phased extraction from mainframe and proprietary application platforms. Strangler-fig pattern with side-by-side execution and gradual workload migration. We tell you when retirement is the right answer.
How we engage
4 phases, named in the SOW.
Each phase has a deliverable, an owner, and an acceptance criterion. Not slogans — operating rules.
- 01
Discovery and disposition
Workload inventory with explicit disposition: lift, replatform, rearchitect, or retire. Cost projections for each path, dependency graph, and the wave plan that sequences risk reduction. Output is a defensible migration roadmap, not a pitch deck.
- 02
Wave design with rollback paths
Migration waves of 5–15% scope each, with explicit cutover windows, dual-running periods, and rollback procedures. Each wave has named acceptance criteria and a go / no-go decision point. No big-bang cutovers unless the substrate is unsalvageable.
- 03
Cutover with shadow traffic and dual writes
Traffic shadowing to validate the new path under real load. Dual writes during the migration window. Database replication with conflict resolution semantics. Observability calibrated to migration failure modes, not just steady-state.
- 04
Stabilize and optimize
Post-migration architecture review. Cost-shape optimization (right-sizing, Reserved Instance / Savings Plan strategy, autoscaling tuning). Continued FinOps cadence for the next two quarters until the cloud cost stabilizes.
Capabilities
What’s in scope.
- Datacenter exit and cloud-to-cloud migration programs
- Workload disposition: lift, replatform, rearchitect, retire — assessed in writing
- Database migration: Oracle, SQL Server, DB2, on-prem Postgres / MySQL / Mongo
- Application replatforming: containerization, managed services, async patterns
- Network and identity re-architecture for the destination cloud
- Observability and runbook re-platforming alongside workload migration
- Post-migration FinOps optimization and architectural review
Stack
Tools we use in production.
- Migration tooling
- AWS Application Migration ServiceAzure MigrateGCP MigrateCloudEndure
- Database migration
- AWS DMSAzure DMSStriimDebeziumGoldengate
- Containers
- KubernetesEKSAKSGKEAnthos
- Traffic management
- IstioEnvoyAWS App MeshHAProxyNGINX
- Data replication
- DebeziumKafka ConnectConfluentAWS DataSyncAzure Data Factory
Selected work
Quantified outcomes, not adjectives.
Common questions
Asked before the first call.
- 01
Lift-and-shift, replatform, or rearchitect — how do you decide?
Workload by workload, with a written disposition. Lift-and-shift makes sense for stable workloads with predictable load and short migration windows. Replatform (containerization, managed services) wins for workloads with operational pain. Rearchitect (decomposition, async patterns) wins when the existing substrate is unsalvageable. We tell you which is which, in writing, before you commit.
- 02
Can you keep our existing application code?
Usually, yes. Replatforming preserves application logic; we change the substrate around it (managed databases, container runtimes, identity, observability). When the application code itself is the failure mode, we'll tell you — and recommend the rearchitect path with explicit cost projections.
- 03
How do you handle data migration without downtime?
Dual writes during the migration window with replication backfill, traffic shadowing to validate the new path, and explicit cutover with documented rollback. Database migration tooling (AWS DMS, Striim, Debezium) for replication; we engineer conflict resolution semantics per workload. Most migrations land with under 30 minutes total downtime; most stateless workloads land with zero.
- 04
What about cost? Will the cloud actually be cheaper?
Sometimes; sometimes not. Lift-and-shift typically increases cost in the first year (you're paying for cloud convenience without using cloud-native economies). Replatform and rearchitect compound cost benefit over time. We model both paths in discovery and tell you what the cost shape will look like under realistic load — not under a vendor's TCO calculator.
- 05
Can you migrate while we keep shipping features?
Yes — that's actually the only way most migrations succeed. We design wave plans that interleave migration work with feature delivery, and we run the platform engineering and feature engineering cadences side by side rather than freezing the product.
- 06
What does a cloud migration engagement cost?
Discovery and disposition: 4–8 weeks, $80K–$250K. Wave-based migration program: 6–18 months, $1M–$5M+ depending on scope. Database-only migrations: $200K–$800K. Post-migration optimization: $150K–$400K standalone. Brackets published honestly so visitors self-qualify before the first call.
Within Platform & Cloud
Other capabilities in this practice.
Talk to us
Bring a cloud migration problem. We’ll bring a senior engineer.
A senior engineer plus the FOUNDATION + SKYWAY department lead joins the first call. No discovery gauntlet, no junior reps.