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Legacy Modernization Services

Pharos Production specializes in Legacy System Modernization - transforming outdated software into modern, maintainable and scalable platforms without disrupting your business operations.

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Reviewed and updated
Last reviewed July 6, 2026 by Dmytro Nasyrov, Founder and CTO. Content reflects Pharos Production delivery data as of the review date. Editorial policy.
Dmytro Nasyrov - Founder and CTO of Pharos Production

Reviewed by Dmytro Nasyrov

Founder and CTO

23+ years in custom software development. Led 110+ projects across FinTech, healthcare, Web3 and enterprise, ISO 27001-aligned team.

What is legacy system modernization?

Legacy modernization is the engineering discipline of replacing or wrapping old systems (green-screen mainframes, 15-year-old PHP monoliths, Oracle Forms, AS/400, early Java EE) without breaking the business that depends on them. It covers strangler-fig migrations (extract services incrementally), API wrappers over unchanged cores, database migrations with dual-write validation, UI refresh on top of legacy backends and the operational discipline to run the old and new systems in parallel long enough to catch regressions before cutover. Pharos modernizations avoid big-bang rewrites by design - we have seen too many fail.
Authoritative citations 12 sources
  1. DORA State of DevOps Report The Google DORA State of DevOps annual report defines the four key software delivery metrics (deployment frequency, lead time for changes, mean time to restore, change failure rate) that we instrument on every production engagement to benchmark delivery performance. dora.dev
  2. Stack Overflow Developer Survey The Stack Overflow Developer Survey documents language, framework, database and tooling adoption across tens of thousands of engineers annually, and we use the trend lines to validate stack choices against hiring pool depth for each client. survey.stackoverflow.co
  3. ThoughtWorks Technology Radar The ThoughtWorks Technology Radar tracks tools, platforms, techniques and languages across adopt, trial, assess and hold rings twice yearly, and is a cross-check we use to validate architectural recommendations against industry consensus. thoughtworks.com
  4. Google SRE Book The Google SRE book codifies service-level objectives, error budgets, incident response and postmortem culture that our production readiness gates adopt directly when handing over a platform to a client operations team. sre.google
  5. Martin Fowler bliki Martin Fowler's bliki is the most cited reference for enterprise architecture patterns including microservices, strangler fig, CQRS, event sourcing and refactoring, which shapes how we describe and implement architecture decisions in ADRs on every client engagement. martinfowler.com
  6. Gartner Custom Application Services Magic Quadrant Gartner publishes multiple Magic Quadrant reports covering custom application services, digital engineering and outsourced development that identify market leaders, completeness of vision and niche specialists across the global software services industry. gartner.com
  7. ISO 27001 Information Security Standard ISO 27001:2022 defines the internationally recognized information security management system requirements that Pharos Production operates under, shaping the control framework we inherit and extend for client software engagements. iso.org
  8. OWASP Top 10 The OWASP Top 10 ranks the highest-impact web application security risks and is the single most cited threat reference for application security programs, which every Pharos build is reviewed against before production release. owasp.org
  9. NIST Secure Software Development Framework NIST SSDF SP 800-218 defines secure development practices including threat modelling, SBOM generation, vulnerability disclosure and supply chain controls, which we treat as the baseline Software Development Lifecycle checklist on every client engagement. csrc.nist.gov
  10. CNCF Cloud Native Landscape The CNCF Cloud Native Landscape maps the full cloud-native ecosystem across orchestration, runtime, observability, security and database categories, useful reference material we consult when validating platform choices for client Kubernetes and service mesh engagements. landscape.cncf.io
  11. Accelerate by Forsgren, Humble, Kim Accelerate distills the multi-year DORA research program into the book-length case for DevOps practices correlated with high-performance software delivery, and is the single most cited academic reference for the delivery metrics we ship inside every client engagement. itrevolution.com
  12. IEEE SWEBOK The IEEE Software Engineering Body of Knowledge codifies the professional knowledge areas covering requirements, design, construction, testing, maintenance, configuration management and engineering economics that underpin every professional software services engagement. computer.org
What we do not do
  • Big-bang rewrites (we decline these almost categorically)
  • Modernization without a clear target architecture
  • Projects where the legacy vendor will not allow data export or integration
  • Modernization motivated by "the old tech is uncool" rather than a measured operational problem

Legacy modernization at Pharos Production at a glance

  • Modernization projects: 18+ modernization engagements since 2018 across insurance, logistics, SaaS, mid-market enterprise
  • Stack: Node.js, Python, Go, Java, TypeScript, PostgreSQL, Kafka, AWS, Kubernetes + legacy wrappers (DB2, Oracle Forms, AS/400, SOAP)
  • Pattern: Strangler-fig incremental extraction; never big-bang rewrites; dual-write validation; parallel runs before cutover
  • Pricing: Architecture audit from $10,000; modernization projects $80,000-$400,000+; long-running programs month-to-month
  • Timeline: Audit 2-4 weeks; modernization 4-14 months with incremental cutovers; full decommissioning 6-18 months
  • Downtime target: Zero downtime during cutover via parallel runs + dual-write; if downtime is acceptable, cheaper paths exist
  • Data migration: Schema migration with validation, reconciliation on both systems during parallel run, automated diff alerts
  • Honest scope: We decline big-bang rewrites and legacy-is-uncool projects

Strangler-fig migrations done right

Modernization follows an incremental strangler-fig pattern: discovery maps the current system and proposes an extraction order; build runs new services in parallel with the legacy system, dual-writing for validation; production readiness includes a cutover runbook with rollback; support includes the decommissioning plan for the legacy system.

Pharos Verified Delivery 4-phase methodology with typical durations and deliverables
  1. Phase 01 / 04

    Paid Discovery

    2-4 weeks
    • Technical validation
    • Architecture proposal
    • Scope refined estimate
    82% on-schedule with discovery
  2. Phase 02 / 04

    Iterative Build

    2-week sprints
    • Working demos every sprint
    • CTO review at milestones
    • ADRs documented
    Transparent progress tracking
  3. Phase 03 / 04

    Production Readiness

    • Monitoring and alerting
    • Security audit Pen test
    • Runbooks and rollback
    ISO 27001 aligned
  4. Phase 04 / 04

    Support

    Ongoing
    • Security patches
    • Performance tuning
    • 4h SLA response
    Continuous improvement

Pharos Verified Delivery applied to 110+ production applications since 2013

Modernizations we shipped without downtime

Three modernization engagements that avoided the classic big-bang rewrite trap by migrating service by service with parallel runs.

Insurance claims system

Q1 2025 · Mid-market insurer, US
Before

15-year-old claims platform on Oracle Forms. 9-hour batch window. New features took 4-6 months to ship. Three senior engineers left in 18 months due to the stack.

After

New Node.js + PostgreSQL + Kafka platform replacing the core. Batch window eliminated, claims processed in real time. New feature cycle down to 2-4 weeks. Legacy system decommissioned in 11 months with zero data-loss incidents.

We ran the new platform in parallel with the legacy system for 4 months, dual-writing to both before the cutover. The switch was a boring Sunday, not a launch event - by design.

Monolith modernization

Q3 2024 · SaaS platform, EU
Before

12-year-old PHP monolith. Deployments took 4 hours and required weekend windows. Engineering team afraid to touch core modules.

After

Strangler-fig migration to Node.js microservices. Deployments now under 12 minutes via CI/CD. Feature velocity increased 4x. Zero downtime during 8-month migration.

We extracted services one bounded context at a time, kept the monolith as the source of truth until each new service had been running clean for two weeks, then flipped the read path.

Mainframe wrapper

Q4 2024 · Logistics enterprise, US
Before

IBM AS/400 running order management since 1996. Every new channel (mobile, API partners, B2B portal) required custom DB2 integration work.

After

REST API wrapper layer with event bus. New channel onboarding down from 14 weeks to 6 days. AS/400 still runs as the system of record, but no client system touches it directly anymore.

We did not replace the mainframe - we abstracted it. The wrapper handles translation to AS/400 batch semantics on one side and real-time REST on the other. The mainframe team kept their world; the product team got modern tooling.

Client names anonymized under NDA. Full case studies at /cases/.

When modernization is not the answer

Legacy is not the problem by itself. We decline modernization work when there is no measured operational cost to the current system. Here is the filter we use:

Projects we decline
  • Systems that are boring and working; "old tech" is not a business problem
  • Modernization without a measured cost, reliability or hiring problem
  • Projects where the vendor will not permit data export or integration
  • Big-bang rewrites without a parallel-run strategy
  • Modernizations where the business process itself is the actual legacy
We recommend leaving it alone

Many legacy systems are boring and working - those should be left alone. Modernization makes sense when the legacy system has a measured cost: slow feature velocity, reliability problems, hiring blockers, compliance gaps or vendor lock-in. "It is old" is not a business case.

Pharos Production legacy modernisation portfolio observations

Observations from 22 modernisation engagements delivered 2019-2026 across FinTech, logistics, insurance and healthcare.

  • Strangler-fig projects delivered in under 18 months were 4.2x more likely to meet budget than big-bang rewrites in our sample.

  • 90-day parallel-run caught reconciliation defects in 82 percent of engagements; projects that skipped it hit rollback in 3 of 5 cases.

  • Teams of 5 to 10 engineers paired with 2 customer-side domain SMEs consistently outperformed 15-plus engineer teams without domain continuity.

  • Approval tests (capturing legacy behaviour before touching code) cut cutover defects by 67 percent on average across 11 projects that used them.

Observations reflect the Pharos Production legacy modernisation portfolio 2019-2026 and do not generalise beyond surveyed engagements.

Legacy modernisation outlook 2026-2027

Legacy modernisation in 2026 is dominated by three forces: data-gravity constraints (databases older than the applications), regulatory deadlines on mainframe sunset and the talent cliff around COBOL, Delphi, Flex and early .NET stacks. Big-bang rewrites continue to fail; strangler-fig, bounded-context and data-first extraction patterns deliver.

  • Martin Fowler's strangler-fig pattern remains the canonical approach for modernisation of living systems[5].

  • ThoughtWorks Radar 2024 keeps event-interception and parallel-run strategies in "Adopt" for legacy extraction[3].

  • Gartner 2024 estimates 60 percent of enterprises still run at least one mission-critical workload on platforms over 10 years old, with an average replatform cost of $4.2M[6].

  • NIST SSDF plus ISO 27001:2022 increasingly require documented dependency posture, forcing modernisation of unpatched legacy runtimes[9].

How to evaluate a modernisation plan before committing

Before approving a legacy replacement, run this 8-point plan audit. Anything below 6 passing is a plan that will overrun by 2x or more in our experience.

  1. Bounded context map

    Existing system decomposed into 3 to 9 bounded contexts with documented write ownership.

  2. Strangler-fig increments

    Migration delivered in fewer than 12 production-visible increments, not as big-bang cutover[5].

  3. Parallel run duration

    Minimum 90 days of dual-run with reconciliation reports on business-critical flows.

  4. Data contract coverage

    100 percent of extracted data shapes covered by schema contracts and drift detection.

  5. Rollback plan

    Every increment has a documented rollback path executable within 1 hour.

  6. Test coverage

    Legacy behaviour characterised with approval tests before extraction begins[3].

  7. Security posture

    Modernised system meets ISO 27001 plus OWASP Top 10 mitigations[7].

  8. Knowledge transfer

    Documented architecture decision records plus runbooks handed to customer team before final cutover.

A modernisation with fewer than 6 of 8 targets met is a rewrite project in disguise, not a modernisation.

Lesson from production: the hidden batch contract

A FinTech customer ran a 2001-era Delphi core with a C# reporting layer and 72 scheduled batch jobs. We extracted the customer-facing API into a Go service in 2023, ran dual-run for 60 days, then cut over. On day 71 the monthly regulator report failed because it depended on a nightly batch job that read uncommitted Delphi temp tables (never documented). Root cause: contract discovery focused on synchronous APIs, missed batch data flows. We paused cutover, instrumented all batch jobs for 30 days, rebuilt 3 silent dependencies as explicit events and resumed migration. The lesson: legacy systems have three contract surfaces (sync API, batch, shared database); cut over only after all three are mapped.

A note on legacy vendor dependencies
Pharos Production handles modernization of legacy systems. Outcomes depend on the target architecture, data migration complexity and client change-management capacity. Decommissioning timelines depend on parallel-run validation, not just engineering work.

Published record

Published Pharos research

Technical articles, comparison guides and methodology deep-dives we write from our own delivery experience.

Platforms we work with

Trusted by Coinbase, Consensys, Core Scientific, MicroStrategy, Gate.io and 10+ more Web3 and enterprise platforms

16+ partners

Our 16 technology partners include:

  • Consensys
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  • MicroStrategy
  • Nubank
  • Okx
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  • Leeway Hertz
  • Consensys
  • Gate Io
  • Coinbase
  • Core Scientific
  • Debut Infotech
  • Axoni
  • Alchemy
  • Starkware
  • Mara Holdings
  • MicroStrategy
  • Nubank
  • Okx
  • Uniswap
  • Riot
  • Leeway Hertz

About the founder and CTO

Dmytro Nasyrov

Dmytro Nasyrov

Founder and CTO Pharos Production

Ask the founder a question

I design and build reliable software solutions - from lightweight apps to high-load distributed systems and blockchain platforms.

PhD in Artificial Intelligence, MSc in Computer Science (with honors), MSc in Electronics & Precision Mechanics.

  • 13 years in architecture of great software solutions tailored to customer needs for startups and enterprises

  • 23 years of practical enterprise customized software production experience

  • Lecturer at the National Kyiv Polytechnic University

  • Doctor of Philosophy in Artificial Intelligence

  • Master's degree in Computer Science, completed with excellence

  • Master's degree in Electronics and precision mechanics engineering

Choose your cooperation model

Pharos Production offers three project models, MVP, Full-fledged Production and Full-cycle Development, priced from $10,000 to $80,000. An MVP prototype takes about 3 months.

MVP
MVP sprint

Scoped MVP with core user flows, clean codebase and production-ready deployment.

$9,000 - $23,000
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Production
Production release

Full-feature build, QA, CI/CD and post-launch stabilization with SLA-backed support.

$29,000 - $55,000
Full-cycle
Full-cycle platform

End-to-end engagement: discovery, architecture, build, DevOps, QA and long-term evolution.

$50,000 - $95,000

Prices vary based on project scope, complexity, timeline and requirements. Hourly rates range from $35 to $75 depending on role and seniority. Contact us for a personalized estimate.

Interaction models for staff augmentation, dedicated teams and outsourcing

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Need extra hands on your software project? Our developers can jump in at any stage - from architecture to auditing - and integrate seamlessly with your team to fill any technical gaps.

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Hire dedicated experts

Whether you're building from scratch or scaling fast, our engineers are ready to step in. You stay in control, and we handle the code.

Outsource your project

From first line to final audit, we handle the entire development process. We will deliver secure, production-ready software, while you can focus on your business.

187+ technologies

Technologies, tools and frameworks we use

Our engineers work with 187+ technologies across blockchain, backend, frontend, mobile and DevOps - chosen for production reliability and performance.

Our engineers work with 187+ technologies across 10 categories: Frameworks, AI, Blockchains, DevOps, Clouds, Databases, Brokers, Tests, Programming, UI/UX.

  • Frameworks: Spring Boot, Erlang OTP, NodeJS, Phoenix, NestJS, Django, FastAPI, Express.js, React, Next.JS, Svelte, Angular, Vue.js, Remix, Astro, Nuxt.js, iOS, Android, Flutter, React Native, Capacitors, Ionic, Swift, Kotlin, Java, Dart
  • AI: OpenAI GPT, Anthropic Claude, Google Gemini, Meta Llama, Mistral AI, Cohere, Ollama, xAI Grok, LangChain, LangGraph, CrewAI, AutoGen, Hugging Face, PyTorch, TensorFlow, scikit-learn, LlamaIndex, Keras, XGBoost, LightGBM, OpenCV, spaCy, ONNX Runtime, Pinecone, Weaviate, Qdrant, Chroma, pgvector, Milvus, FAISS, MLflow, Weights & Biases, DVC, Kubeflow, AWS SageMaker, Azure ML, Google Vertex AI, NVIDIA Triton, Airflow, Ray Serve, vLLM, OpenAI Agents SDK, Claude MCP, Semantic Kernel, Haystack
  • Blockchains: Ethereum, TON, Corda, Tron, Hedera, Stellar, Consensys GoQuorum, Solana, Arbitrum, Binance Smart Chain (BSC), Sei, Celo, Hyperledger, MultiversX, IOTA, Polkadot, Aptos, Neo, Flow, Algorand, Avalanche, EOS, Optimism, Polygon, Cosmos, Sui, Tezos, Ontology, Fantom, NEAR Protocol, VeChain, Base, IPFS, Amazon Managed Blockchain, Amazon QLDB, IBM Blockchain, Oracle Blockchain
  • DevOps: Kubernetes, Terraform, Docker, Istio, Prometheus, Grafana, Jenkins, ArgoCD, Ansible, GitHub Actions, GitLab CI, Pulumi, Datadog, New Relic, Vault
  • Clouds: Amazon Web Services, Azure, Google Cloud, Cloudflare, Vercel, DigitalOcean
  • Databases: PostgreSQL, MySQL MariaDB, Redis, Cassandra, Neo4J, MongoDB, Elasticsearch, Solr, Ignite, ClickHouse, TimescaleDB, DynamoDB, Supabase, CockroachDB, ScyllaDB
  • Brokers: Kafka, RabbitMQ, Flink, Apache Pulsar, Amazon SQS, Amazon SNS, NATS
  • Tests: Postman, Appium, Cucumber, Selenium, JMeter, Cypress
  • Programming: Solidity, FunC, Rust, GoLang, Elixir, Erlang, C++, Java, JavaScript, TypeScript, Scala, Python, C#, .NET, PHP, Ruby, Dart, SQL
  • UI/UX: Figma, Zeplin, InVision, Sketch, Miro, Marvel, Balsamiq, Photoshop, Illustrator, XD, After Effects, Corel Draw

Frameworks

Backend Frameworks 8

Spring Boot
Spring Boot
Erlang OTP
Erlang OTP
NodeJS
NodeJS
Phoenix
Phoenix
NestJS
NestJS
Django
FastAPI
Express.js

Front End Frameworks 8

React
React
Next.JS
Next.JS
Svelte
Svelte
Angular
Angular
Vue.js
Remix
Astro
Nuxt.js

Mobile Apps Frameworks 10

iOS
iOS
Android
Android
Flutter
Flutter
React Native
React Native
Capacitors
Capacitors
Ionic
Ionic
Swift
Swift
Kotlin
Kotlin
Java
Java
Dart
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Partnerships and awards

Recognized on Clutch, GoodFirms and The Manifest for software engineering excellence

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An approach to the development cycle

The Pharos Delivery Framework divides every project into 2-week sprints. After each sprint we hold a retrospective, deliver a progress report and plan the next sprint. This methodology is why agile projects are 3x more likely to succeed than waterfall (Standish Group CHAOS Report, 2024).

  1. Team Assembly

    Our company starts and assembles an entire project specialists with the perfect blend of skills and experience to start the work.

  2. MVP

    We'll design, build and launch your MVP, ensuring it meets the core requirements of your software solution.

  3. Production

    We'll create a complete software solution that is custom-made to meet your exact specifications.

  4. Ongoing

    Continuous Support

    Our company will be right there with you, keeping your software solution running smoothly, fixing issues and rolling out updates.

Modernization insights

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Skip glossary

Legacy Modernization Glossary 7

Strangler Fig Pattern
A modernization approach where new microservices replace individual features of a legacy monolith incrementally, with a routing layer directing traffic until the old system can be decommissioned safely.
COBOL Modernization
The process of migrating mainframe COBOL business logic to modern languages such as Java or Go, typically using automated transpilation tools combined with manual rewriting for performance-critical routines.
Monolith-to-Microservices
An architectural transformation that decomposes a single deployable application into independently deployable services, each owning its data store and communicating via defined APIs or events.
Re-platforming
Migrating a legacy application to a new runtime environment - such as moving from on-premise servers to AWS or from .NET Framework to .NET 8 - with minimal changes to application logic.
Zero-Downtime Migration
A database or system cutover strategy using techniques such as dual-write, read replicas or blue-green deployments to keep the application continuously available throughout the transition.
Database Modernization
Upgrading or replacing an aging database engine - for example migrating from Oracle 11g to PostgreSQL - including schema refactoring, query rewriting and data validation at scale.
API Strangler
A specific implementation of the strangler fig pattern where a new REST or GraphQL API layer is introduced in front of a legacy system, gradually absorbing endpoints until the old backend is retired.

Frequently asked questions about Legacy Modernization Services

Last updated:

  • Copy link Copies a direct link to this answer to your clipboard.

    Big-bang rewrites fail roughly 70% of the time because the legacy system contains years of undocumented business logic you do not know about. Strangler-fig migrations succeed ~85% of the time because you extract one bounded context at a time, run both systems in parallel, catch regressions before cutover and decommission the legacy system only after the new system has been running clean for weeks.

  • Copy link Copies a direct link to this answer to your clipboard.

    Dual-write during the parallel-run window. New features write to both the legacy system and the new system; we diff both daily and alert on mismatches.

    Read traffic shifts from legacy to new in stages (5% → 25% → 100%) once the dual-write window shows stable consistency. Cutover is a config change, not a migration event.

  • Copy link Copies a direct link to this answer to your clipboard.

    Architecture audit 2-4 weeks. First extracted service or API wrapper 6-12 weeks.

    Full modernization 4-14 months depending on how many bounded contexts exist in the legacy system. Full decommissioning of the old system 6-18 months. We prefer longer parallel-run windows - rushing the cutover is the main cause of modernization incidents.

  • Copy link Copies a direct link to this answer to your clipboard.

    Yes - we prefer that. The legacy team has years of undocumented knowledge about why the system works the way it does.

    We treat them as the domain experts and pair them with our engineers. Several of our most successful modernizations ended with the legacy team retained for ongoing legacy operations and maintenance while the modernization team handled the new stack.

  • Copy link Copies a direct link to this answer to your clipboard.

    We wrap them behind modern APIs. REST + JSON externally, legacy protocol internally.

    The wrapper is the only code that touches SOAP, EDI, COBOL or AS/400 RPG - everything else in the new stack talks to the wrapper. This isolates the legacy complexity from your product team and lets you decommission the wrapper later without touching product code.

  • Copy link Copies a direct link to this answer to your clipboard.

    Common failure modes: big-bang rewrites that deploy everything at once; skipping the parallel-run validation window; trying to modernize the business process and the technology at the same time; ignoring the legacy team's tribal knowledge; underestimating data migration complexity. We have seen all five fail; our process is designed to avoid them.

  • Copy link Copies a direct link to this answer to your clipboard.

    We decline big-bang rewrites (almost always), modernizations motivated by "the old tech is uncool" rather than a measured problem, projects where the legacy vendor will not permit data export and modernizations where the business process itself is the actual legacy. "Boring and working" is a good state; do not modernize away from it without a specific reason.

The Pharos takeaway on legacy modernization

Legacy modernisation in 2026 is measurable: bounded contexts, strangler-fig increments, parallel run and documented rollback. Pharos Production plans modernisations around business continuity, not cutover dates, so your revenue-critical flows never fall out of production during the transition.

Dmytro Nasyrov, Founder and CTO at Pharos Production
Dmytro Nasyrov Founder & CTO Let's work together!

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