Software Modernization Services

Migration from outdated framework versions to current, actively maintained versions: Rails 4 to Rails 7 (intermediate upgrade path through 5 and 6, with dual-boot configuration using bootsnap to validate the upgrade before cutover), Node.js LTS upgrades (running ncu and depcheck to identify deprecated dependencies, Node 14 to 20 with CommonJS to ESM migration where applicable), Angular 8 to 17 (Nx migration executor with per-module upgrade validation), React class components to hooks (automated codemods via react-codemod for straightforward cases, manual migration for complex lifecycle patterns), PHP 7 to PHP 8 (Rector automated refactoring for deprecated constructs, strict type analysis with PHPStan), and Python 2 to Python 3 (2to3 automated conversion with manual review of encoding, integer division, and print function changes).

Security vulnerability remediation: OWASP Dependency-Check and Snyk run on the existing codebase to catalogue all dependencies with known CVEs before migration starts. The upgrade roadmap is prioritised by security severity, dependencies with critical CVEs are upgraded first, regardless of refactoring complexity. After migration, Dependabot or Renovate Bot is configured to propose automated dependency updates for future security patches so the codebase doesn't re-accumulate unsupported dependency debt.

Migration from on-premise infrastructure or end-of-life hosting to AWS, GCP, or Azure. Containerisation with Docker and Kubernetes, serverless architecture for appropriate workloads, and managed database services that eliminate server administration overhead. Infrastructure-as-code with Terraform so your cloud setup is reproducible and auditable.

Database engine upgrades (MySQL 5.7 to 8.0, PostgreSQL 12 to 16), NoSQL to relational migration where the data model warrants it, sharding strategies for databases that have outgrown single-instance capacity, and read replica configuration for reporting workloads. Zero-downtime migration strategies that keep the production system live during migration.

Incremental decomposition of monolithic applications into independently deployable services using the strangler-fig pattern, the monolith continues serving all traffic while new services are built alongside it, one domain at a time. Domain prioritisation: we map the monolith's bounded contexts using static analysis (call graph mapping, module coupling analysis with tools like Understand or CodeScene) and business impact assessment (which domains have the highest release frequency, the most team contention, or the most independent scaling requirements). The highest-value domains, the ones causing the most deployment coupling or the most scaling pain, are extracted first.

Service extraction mechanics: the API facade pattern routes specific URL paths to the new service while the monolith handles everything else. Feature flags control the percentage of traffic sent to the new service during validation (1% to 10% to 50% to 100% with automated rollback if error rates increase). The new service owns its data: dual-write migration (monolith and service both write during transition, service reads from its own database, monolith reads from its database) ensures zero downtime data migration. AWS App Mesh, Istio, or simple nginx routing handles traffic splitting without application code changes. The monolith's corresponding code is deprecated and removed after the new service passes 30-day production validation, the codebase shrinks measurably at the end of each migration phase.

Replacing proprietary SaaS dependencies that have become cost-prohibitive or are limiting your architecture, custom-built replacements for Salesforce functions you're using a fraction of, open-source alternatives to expensive analytics platforms, self-hosted replacements for third-party services that require data sovereignty. Vendor replacement is often the fastest path to reducing operating costs.

Refactoring accumulated technical debt that's slowing your team, removing dead code, standardising patterns, adding test coverage to untested legacy code, updating documentation, and restructuring the module boundaries so the codebase is navigable by someone who didn't write it. The codebase rehabilitation that takes new engineer onboarding from two weeks to two days.

Before recommending an approach, we assess the existing system, codebase structure, dependency audit, infrastructure inventory, and performance bottleneck identification. We tell you what needs modernizing, what can stay as-is, and which approach (modernize vs. rebuild) makes more sense. Honest assessment before any development commitment.

We scope modernization in phases, each delivering a defined outcome. The existing system stays operational throughout. Phase 1 might be framework upgrade and test suite update. Phase 2 might be cloud re-platforming. Phase 3 might be database migration. Each phase has a defined scope and fixed cost so you can approve and fund each phase independently.

Every modernization phase is validated against real production data before traffic cutover. We don't validate against synthetic test data that doesn't reflect your actual usage patterns. If the modernized system can't handle your production load, we catch it before your users do.

After modernization, your team needs to understand and maintain the new system. We document the architecture decisions, write runbooks for operational procedures, and conduct handoff sessions with your engineering team. Modernization that creates new dependency on us to maintain it has failed to solve the original problem.