Refactor monolithic legacy codebases, transition to serverless cloud microservices, and eliminate high-cost technical debt.
We believe that legacy systems are a business asset, not just technical debt. Our approach is surgical. We construct integration layers (strangler pattern) that gradually branch users off old monolith endpoints into modern microservices, validating each step before shutting down the legacy code.
Whether you need to containerize (Docker, Kubernetes) an on-prem codebase, refactor database schema queries, or migrate database servers from Oracle to Postgres/MySQL, we deliver with no business downtime.
Isolate complex domain features from monolithic applications into single-purpose modern Node or Go API microservices.
Migrate legacy databases to serverless, scalable SQL or NoSQL databases with zero data loss or synchronization latency.
Streamline development feedback cycles with automated GitHub actions testing, linting, and Docker container packaging.
Refactor computational background jobs to run as Lambda or Cloud Functions, cutting operational idle server costs.
Rewriting legacy codebases carries operational risk. We apply structured architectural guardrails to guarantee zero downtime and zero data loss.
We do not perform high-risk cutovers. We deploy an API gateway to gradually route specific functional paths to new microservices, leaving the monolith running in parallel.
We run read-queries through both old and new systems simultaneously, validating that the new microservice matches monolithic outputs exactly before changing write paths.
Every microservice extraction is guarded by feature flags. If any system latency peaks occur, we route traffic back to the legacy host in under 1 second.
Maintained across all migration stages.
By refactoring idle background processes to serverless hosts.
Reducing pipeline build times from hours to minutes.
Confirmed via external dependency audits post-refactoring.