How do you migrate a legacy platform without downtime?

We use a strangler fig pattern: new services run alongside the legacy system, gradually taking over traffic. Critical paths get migrated first with automated rollback. Database migrations happen through dual-write strategies where both old and new systems stay in sync during the transition. Zero downtime means zero downtime, not "just a few minutes."

Should we move to microservices or stay monolithic?

It depends on your team size and deployment frequency. If fewer than 20 engineers deploy weekly, a well-structured modular monolith is usually faster and cheaper to operate. Microservices make sense when independent teams need to deploy different components on different schedules. We assess your situation before recommending either path.

What cloud providers do you work with?

AWS, Google Cloud, and Azure. Most modernization projects land on AWS due to service breadth, but we architect for your specific requirements. Some clients use multi-cloud or hybrid setups, which we support with cloud-agnostic infrastructure-as-code using Terraform or Pulumi.

How long does a typical platform modernization take?

Most modernizations run 4 to 8 weeks. A short assessment and migration plan up front, then modular boundaries, database migration, and containerized deployment. The timeline moves with the number of integrations and how much data has to be migrated.

Platform Modernization

Modernizes a legacy platform without a feature freeze: modular boundaries first, then observability and cost controls, with dual-run validation for a zero-downtime cutover.

Timeline: 4-8 weeks
Team: Solution Architect · Backend Engineer · DevOps Lead · QA Engineer
Typical stack: Languages: Ruby/Rails, Node.js, Python/Django/Flask, Java/Spring Boot, .NET/C#. Cloud: AWS, Azure, GCP, on-prem/hybrid. Containers: Docker, Kubernetes, ECS, AKS, GKE. CI/CD: GitHub Actions, GitLab CI, Jenkins, CircleCI, Azure DevOps. Observability: Datadog, New Relic, Prometheus/Grafana, Sentry, CloudWatch. Databases: PostgreSQL, MySQL, MongoDB, Redis, DynamoDB. API Gateway: Kong, AWS API Gateway, Azure APIM, Nginx, custom.

What you get

Modernization blueprint with target architecture and migration phases
Dual-run infrastructure with blue-green/canary deployment capability
Observability stack: distributed tracing, structured logging, error budgets
API gateway and module boundaries with contracts and versioning
CI/CD pipeline with automated testing and rollback automation
Security baseline: SBOM generation, SAST/DAST scanning, CSP/HSTS headers, secret rotation via KMS
Cost plan: unit economics per request/service, autoscale policies, budget alerts and rightsizing recommendations
Performance report: p95 latency, throughput, cost analysis, error rates

Outcomes

Measurable p95 latency drop & infra cost reduction
Zero-downtime cutover, dual-run validation
Observability + error budget in place
Faster release cadence with lower risk

Selected work

p95 latency ↓46% in 6 weeks

p95 840ms → 450ms. Re-platformed hot paths, added tracing, tuned indices. No feature freeze. Infra spend down 21% ($42k → $33k/mo); 7 critical CVEs closed before go-live.

Rails · Postgres · Grafana

450K LOC migrated. Zero downtime.

Rails 3 to 7 for a top-10 telehealth provider: 450K LOC, 2.5M patient records, 14 months, and 15,000 daily clinical users never noticed. Test coverage 35% → 85% caught 847 regressions; passed SOC 2 Type II during the migration.

Rails · PostgreSQL · AWS · HIPAA

How we approach it

Modular Monolith

When:: Teams <50, Rails/Django/monorepo culture, gradual migration preferred
Tradeoffs:: Faster deployment (4-8 weeks), simpler ops, but limited independent scaling
Best for:: SMB, startups scaling to mid-market, risk-averse organizations

Microservices

When:: Large teams (50+), polyglot requirements, independent scaling critical
Tradeoffs:: Maximum flexibility and scale, but higher operational complexity and DevOps maturity required
Best for:: Enterprise, high-growth SaaS, multi-product platforms

Strangler Fig

When:: Legacy systems with high risk, phased migration over 12-24 months
Tradeoffs:: Lowest risk with continuous delivery, but longer timeline and dual-system maintenance
Best for:: Government, heavily regulated industries, mission-critical systems

Hybrid (Modular + Services)

When:: Mid-size teams, balance of governance and flexibility needed
Tradeoffs:: Pragmatic approach avoiding microservices sprawl, but requires strong architectural judgment
Best for:: Growing companies, B2B SaaS, platform teams

Where teams use it

Finance

Legacy core banking modernization

Migrated COBOL mainframe to Java microservices with zero-downtime, achieving 78% cost reduction and enabling real-time fraud detection

Retail

E-commerce platform scalability

Modernized monolithic e-commerce to API-first architecture, handling 12x Black Friday traffic with 82% latency reduction

Healthcare

HIPAA-compliant EHR integration

Modernized patient data platform with end-to-end encryption, achieving SOC 2 Type II and 95% faster API response times

What we need from you

Current architecture docs and pain points
Performance baselines (p95, throughput)
Target cost reduction %
Release cadence goals
Compliance/security requirements

Proof points

Before/after p95 latency chart
Infra cost comparison
Observability stack (traces, logs, metrics)
Rollback success rate

Built for procurement

Performance SLAs: p95 latency targets, throughput guarantees, error budget commitments
Cost projections: Infrastructure cost reduction estimates, ROI timeline, scaling cost models
Zero-downtime guarantee: Dual-run validation, rollback procedures, incident response SLAs
Observability deliverables: Distributed tracing, error budgets, custom dashboards, alert runbooks
Migration evidence: Before/after performance reports, architecture diagrams, cutover checklists
Compliance: SOC 2 Type II, HIPAA, PCI-DSS support for regulated environments
Support: Runbook handoff, 30-day post-launch support, escalation procedures