of legacy migration projects blow the budget or timeline. We are the other 27%.
Legacy System MigrationYour legacy system is slowing your team down. We fix that. On schedule. Without downtime.
We migrate legacy monoliths to cloud-native architecture, ship zero-downtime cutovers, and build CI/CD pipelines that let your team release the same day code is ready. Every engagement starts with a two-week assessment — no code moves without a signed-off architecture plan.
Most legacy migrations fail before the first cutover. The patterns are predictable. So are the fixes.
The gap between your current system and what it should be — made visible in one drag.
This is a representative sample of the architecture and deployment pipeline we deliver. Drag left to see where most teams start. Drag right to see where they finish.
Four migration types. One consistent approach: no code moves without a signed-off architecture plan.
Break the monolith. Keep the business running.
We use the strangler fig pattern: extract the highest-value service domain first, run it alongside the monolith, then shift traffic incrementally. We never attempt a full rewrite. We migrate service by service. At no phase does a user see downtime. Your team ships new features into the new architecture while the old system is still serving traffic.
Move to the cloud first. Cut infrastructure costs second.
Lift-and-shift gets you to the cloud. Cloud-native refactoring cuts your monthly infrastructure bill. We do both in the right order: move first, optimize second. We write your target architecture, provision infrastructure as code, and migrate workloads in stages. Each stage has a tested rollback gate.
PHP 5. Rails 3. .NET Framework. We have seen them all.
PHP 5 to PHP 8. Rails 3 to Rails 7. .NET Framework to .NET 8. We replace deprecated libraries, refactor anti-patterns, and add automated test coverage. Then we ship CI/CD pipelines so your team can release on the same day code is ready — not after a two-week manual QA cycle.
Platform and data migration
E-commerce platform switches, database engine changes, CMS replacements. We write migration scripts with dry-run mode, run parallel validation against both systems, and define a hard cutover point with a verified rollback path. We test the rollback before we schedule the cutover. No exceptions.
From weekly deploys to 8x per day: legacy monolith to cloud-native microservices on AWS. 20 weeks. Zero downtime.
Other migrations fail mid-build. Here is why ours do not.
No undocumented surprises. Every dependency mapped before Sprint 1.
Every migration starts with a 2-week assessment: codebase audit, dependency map, integration inventory, and target architecture sign-off. Most migrations blow the budget because hidden dependencies surface mid-build. Our assessment removes that specific risk before any code moves.
Legacy modernization →Sprint 1 ships to production. You see results in weeks, not months.
We use the strangler fig pattern for application migration and incremental traffic routing for cutover. Each phase puts something real into production and maintains a tested rollback path. You are not waiting 6 months for a big-bang launch. Sprint 1 ships to production.
Software migration services →We test the rollback before we schedule the cutover
Every data migration script has a dry-run mode and a verified rollback. Every traffic routing phase is validated against the rollback path before the next phase starts. The cutover weekend is not the moment you discover whether rollback works. By that point, it is already tested and boring.
Monolith to microservices →The questions CTOs and engineering leads ask before they sign off on a migration.
We handle legacy application modernization, monolith to microservices migration, cloud migration, database migration, and platform re-architecture. For the full service list, see software migration services and monolith to microservices migration.
We use the strangler fig pattern for most migrations: build the new system alongside the old one, route traffic incrementally, and remove legacy components only after the new system handles 100% of traffic without errors. We enforce zero-downtime deployments through blue-green or rolling update strategies from the first production release — meaning your users never see a maintenance window.
A legacy application modernization typically takes 3 to 6 months depending on codebase size, integration count, and data complexity. A monolith to microservices migration typically runs 4 to 8 months. We scope the timeline against your actual codebase during the assessment before quoting, and deliver value in every sprint rather than at the end.
We treat data migration as a separate workstream from application migration. We write migration scripts with a dry-run mode and a verified rollback path, run parallel validation against both the old and new systems, and define a hard cutover point with zero data loss. We do not begin a data migration without a tested rollback plan. If a dry run reveals data integrity issues, we fix them before the production run — not during it.
Yes, over 12 to 18 months. Developer productivity on legacy codebases drops 10 to 30 percent per year as technical debt builds. Unplanned outages on monolithic systems cost 3 to 8 times more to recover from than failures in distributed architectures. Most clients recover their full migration investment within 12 to 18 months through lower ops overhead and faster release cadence. The cost of staying on legacy compounds. The cost of migration is finite.
Your legacy system is a known risk. A two-week assessment tells you the exact cost to fix it.
You get a full migration readiness report. We respond within two business days. No commitment until you see the plan.
Your team spends 3 to 5 hours per sprint on review and sign-off. We own the migration architecture, write the data migration scripts, run the parallel validation, and manage the cutover.
Send brief today. Call within 48 hours. Migration readiness assessment in 3 days. Sprint 1 starts week 2.
