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Application Modernisation

Transform Legacy Applications Into Cloud-Native Systems - Without Disrupting Your Business

We help enterprise organisations migrate complex legacy applications to modern, cloud-native architectures using proven patterns including monolith-to-microservices decomposition, the strangler fig pattern, and incremental re-platforming. Every engagement is grounded in a rigorous risk assessment and a phased migration plan that keeps production running throughout.

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500+
Enterprise Clients
10,000+
Engineers Deployed
50+
Countries Served
99.4%
CSAT Score
48h
Team Assembly

The Challenge

Legacy Applications Are Holding Your Business Back

Monolithic architectures built for a different era of computing now impose compounding constraints on every team in your organisation. Deployment cycles measured in months, inability to scale individual capabilities independently, mounting security vulnerabilities in unsupported frameworks, and a shrinking pool of engineers willing to maintain ageing technology stacks are symptoms of a structural problem that cannot be solved by adding more developers to the existing codebase.

73%
of enterprise IT budgets spent maintaining legacy systems rather than innovation
6x
longer feature delivery cycles in monolithic versus microservices architectures
$3.8T
annual global cost of technical debt from legacy application maintenance
4x
higher cloud infrastructure cost running legacy apps without re-platforming

Why QuickHire

Why Enterprises Choose QuickHire

01

Portfolio-Level Assessment

We evaluate every application in your estate against modernisation ROI, business criticality, and technical risk before a single line of code is changed. This prevents the common failure mode of modernising the wrong applications first.

02

Domain-Driven Decomposition

Our architects use event-storming and bounded-context mapping to identify the correct service boundaries in your domain, producing microservice architectures that are stable, independently deployable, and aligned with your team structure.

03

Incremental Migration - No Big Bangs

We use the strangler fig pattern, feature flags, and blue-green deployments to migrate production systems incrementally, eliminating the risk of extended downtime and allowing rollback at every stage.

04

Risk-Managed at Every Stage

Each migration increment is preceded by a risk assessment that identifies data integrity, performance, and availability risks and defines mitigation actions and rollback procedures before work begins.

05

DevOps and Observability Built In

Modernisation engagements include full CI/CD pipeline construction, infrastructure-as-code, and observability stack deployment so the modernised application is fully operable from day one of production cutover.

06

Compliance and Governance Continuity

We map every regulatory obligation from the legacy system to the target architecture before migration begins, ensuring that data residency, audit logging, and access control requirements are satisfied at every stage of the transition.

Challenges

Common Enterprise Pain Points

01

Tight Data Coupling Across Modules

Legacy monoliths frequently share a single database schema across hundreds of modules, making clean service extraction appear impossible. We specialise in database decomposition techniques - including shared database patterns, database per service migration, and event-sourcing for data ownership transfer - that resolve coupling without requiring a full rewrite.

02

Knowledge Loss From System Age

Applications built over ten to twenty years often have no surviving engineers who understand the original design intent, and documentation is absent or incorrect. Our reverse-engineering capability uses static analysis, runtime instrumentation, and stakeholder interviews to reconstruct a domain model that safely guides the migration.

03

Integration Dependency Proliferation

Enterprise monoliths accumulate hundreds of point-to-point integrations with other internal and external systems over their lifetime. We conduct integration mapping and introduce an event-driven integration layer or API gateway before decomposition begins, preventing integration chaos during service extraction.

04

Inadequate Test Coverage

Systems with low automated test coverage cannot be safely refactored because there is no reliable way to confirm that behaviour has been preserved. Our pre-migration work includes characterisation testing to establish a safety net of tests that document current behaviour, giving engineers confidence to make structural changes.

05

Organisational Resistance to Change

Application modernisation programmes frequently stall not because of technical challenges but because of organisational inertia - teams accustomed to the current architecture resist the process changes that microservices require. We include change management, team topology consulting, and developer enablement workshops as integral components of every engagement.

Our Approach

A Structured, Incremental Modernisation Programme That Delivers Value at Every Stage

Our application modernisation methodology combines rigorous upfront assessment with incremental delivery to ensure that every sprint of the programme produces a usable, production-ready outcome. We do not require a programme completion date before you see value - each extraction, re-platform, or containerisation increment delivers independently deployable capabilities that reduce operational risk and increase business velocity from the moment they are released.

01
Application Portfolio Assessment
A structured evaluation of your entire application portfolio producing a risk-scored modernisation roadmap with ROI projections, sequencing recommendations, and a total cost of ownership comparison between maintaining the status quo and modernising each application.
02
Architecture Design and Decomposition Planning
Domain-driven design workshops, bounded context mapping, and architecture decision record production that define the target microservices architecture and the incremental extraction sequence before implementation begins.
03
Incremental Migration Delivery
Phased delivery of migration increments using the strangler fig pattern, blue-green deployments, and feature flags to maintain production continuity while progressively replacing legacy components with modernised equivalents.
04
DevOps, Observability, and Knowledge Transfer
Concurrent construction of CI/CD pipelines, infrastructure-as-code, and observability infrastructure, with structured knowledge transfer sessions that leave client engineering teams fully capable of operating and extending the modernised application.

Delivery Models

How We Deliver

Assessment and Roadmap

A focused discovery engagement that produces a prioritised modernisation roadmap, risk register, and investment case without committing to a full delivery programme.

Timeline
4-6 weeks
Team Size
2-3 architects
Managed Modernisation Programme

A fully managed end-to-end programme with a dedicated delivery team responsible for architecture, migration, DevOps, and knowledge transfer throughout the engagement.

Timeline
12-36 weeks
Team Size
4-10 engineers
Embedded Modernisation Squad

A specialist modernisation team embedded alongside your existing engineering organisation, accelerating internal capability while delivering migration increments.

Timeline
8-24 weeks
Team Size
3-6 engineers

Capabilities

Technical Capability Matrix

Architecture Patterns
Monolith-to-MicroservicesStrangler Fig PatternEvent-Driven ArchitectureCQRS and Event SourcingAPI Gateway Design
Cloud Re-Platforming
AWS Re-PlatformingAzure MigrationGoogle Cloud AdoptionMulti-Cloud ArchitectureServerless Migration
Containerisation and Orchestration
Docker ContainerisationKubernetes DeploymentHelm Chart AuthoringService Mesh ImplementationContainer Security Hardening
Database Modernisation
Schema DecompositionChange-Data-Capture PipelinesNoSQL MigrationCloud-Managed Database AdoptionZero-Downtime Cutover
DevOps and Observability
CI/CD Pipeline ConstructionInfrastructure as CodeDistributed TracingCentralised LoggingSLO and Alerting Design

Engagement Models

How We Engage

Choose the model that fits your programme governance, budget cycle, and team structure.

01

Staff Augmentation

Engineers embed directly under your management.

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02

Dedicated Developers

Full-time team aligned to your product roadmap.

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03

Managed Teams

End-to-end delivery with SLA-backed outcomes.

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04

Engineering Pods

Autonomous cross-functional pods per domain.

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05

Offshore Dev Centre

Permanent engineering base in India. Full IP ownership.

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06

Build-Operate-Transfer

We build and run it. You take ownership on schedule.

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Our Process

From Discovery to Delivery

1

Portfolio Discovery

Week 1

We inventory your application portfolio, conduct stakeholder interviews, and run automated code analysis to produce a baseline assessment of each system's modernisation complexity, business value, and risk profile.

2

Architecture Design

Weeks 2-3

Domain-driven design workshops and bounded context mapping produce the target microservices architecture, integration strategy, and data ownership model. Architecture decision records are produced for all major design choices.

3

Migration Roadmap and Risk Register

Week 4

A sequenced, phased migration roadmap is produced with effort estimates, dependency mapping, rollback procedures, and success criteria for each increment. The risk register identifies and mitigates all identified programme risks.

4

Incremental Migration Delivery

Weeks 5 onward

Delivery squads execute migration increments in two-week sprints, with each increment producing a production-ready, deployable output. Blue-green deployments and feature flags maintain production continuity throughout.

5

Stabilisation and Knowledge Transfer

Final 4 weeks

A structured stabilisation period validates performance, reliability, and compliance of the modernised application under real production load. Knowledge transfer sessions ensure client teams are fully capable of independent operation.

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Security & Compliance

Enterprise-Grade Security by Default

✓ISO 27001 Certified✓SOC 2 Type II Ready✓GDPR Compliant✓DPDP Act Ready✓NDA on Day 1✓MSA Available✓IP Assignment Clauses✓Escrow Options

Governance

Programme Governance

✓

Architecture Review Board

A weekly architecture review board includes client technical leadership and our solution architects, reviewing all significant design decisions and ensuring alignment with the agreed target architecture throughout the programme.

✓

Risk and Issue Management

A live risk register is maintained and reviewed at each programme governance checkpoint, with every identified risk tracked through to resolution or acceptance with documented mitigations.

✓

Compliance Traceability Matrix

For regulated industries, a compliance traceability matrix maps every regulatory obligation to its implementation in the target architecture, providing audit evidence for internal and external compliance reviews.

✓

Increment Acceptance Criteria

Each migration increment has documented acceptance criteria covering functional correctness, performance benchmarks, security scanning results, and observability coverage that must be satisfied before production promotion.

Team Structure

Your Enterprise Team

Our application modernisation teams are assembled from specialists with deep experience in both legacy system archaeology and modern cloud-native engineering. Each team is structured to cover the full technical stack required for a modernisation programme - from architecture design through delivery and DevOps - so that no capability gap blocks the programme at any stage.

✓Solution Architect
✓Domain-Driven Design Specialist
✓Senior Back-End Engineer
✓Database Migration Specialist
✓DevOps and Platform Engineer
✓Front-End Modernisation Engineer
✓QA and Test Automation Engineer
✓Delivery Manager

Project Lifecycle

From Kickoff to Production

01
3-4 weeks

Discovery and Assessment

Application portfolio analysis, modernisation scoring matrix, dependency maps, total cost of ownership comparison, preliminary risk register.

02
2-4 weeks

Architecture and Design

Target architecture documentation, bounded context map, data ownership model, integration strategy, architecture decision records, sequenced migration roadmap.

03
2-3 weeks

Foundation Sprint

CI/CD pipeline, infrastructure-as-code templates, container registry, observability stack, staging environment, characterisation test suite.

04
8-28 weeks

Incremental Migration

Production-deployed microservices or re-platformed modules, updated integration layer, database migration scripts, updated runbooks, increment completion reports.

05
Ongoing

Stabilisation and Handover

Performance validation report, compliance traceability matrix, operations runbooks, knowledge transfer completion, technical debt backlog, programme completion report.

Case Studies

Enterprise Outcomes

Financial Services

A retail bank needed to decompose a fifteen-year-old monolithic core banking application to enable faster product launches and reduce infrastructure costs.

We applied domain-driven design to identify eight bounded contexts and used the strangler fig pattern to extract each as an independent microservice over eighteen months, with zero planned downtime during migration.

65%reduction in new product time-to-market
Healthcare

A hospital network was operating patient record software on end-of-life infrastructure with growing compliance risk and no path to cloud adoption under the existing architecture.

We re-platformed the application to a containerised Kubernetes deployment on a HIPAA-compliant cloud environment, modernising the database tier with zero-downtime cutover and delivering a new responsive UI.

$2.4Mannual infrastructure cost reduction
Retail and E-Commerce

A national retailer's monolithic e-commerce platform could not scale to handle peak season traffic without costly over-provisioning across the entire application.

We decomposed the product catalogue, inventory, and checkout services into independently scalable microservices, enabling targeted auto-scaling that absorbed peak traffic without full-system over-provisioning.

4xpeak traffic handled without cost increase

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Hiring Models

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Frequently Asked Questions

Application modernisation is a structured programme that transforms legacy software systems into architectures aligned with current business and technology demands. It encompasses technical interventions such as monolith decomposition, cloud re-platforming, containerisation, and database migration, as well as organisational change management to ensure teams can operate and maintain the resulting systems. Each engagement begins with a thorough portfolio assessment to identify which applications deliver the greatest return on modernisation investment. The outcome is a phased, risk-managed roadmap that balances continuity of business operations with the pace of transformation.
The choice of modernisation strategy depends on the business value of the application, the complexity of its existing codebase, the degree of technical debt, and the organisation's tolerance for risk and cost. Re-hosting (lift-and-shift) delivers the lowest risk and fastest time-to-cloud but preserves existing constraints. Re-platforming adjusts the application to leverage managed cloud services without changing core architecture, offering a middle ground. Re-architecting - such as decomposing a monolith into microservices - delivers the greatest long-term agility but requires the most investment. Rebuilding is reserved for systems so degraded that incremental modernisation is more expensive than a greenfield replacement. Our assessment framework scores each application against these dimensions to produce a defensible recommendation.
The strangler fig pattern is an incremental modernisation technique in which new functionality is built as standalone services that progressively replace equivalent capabilities in a legacy system, until the legacy system can be decommissioned entirely. It is named after a fig species that grows around and eventually replaces its host tree. This pattern is appropriate when the legacy system must remain fully operational throughout the migration, when the risk of a big-bang cutover is unacceptable, or when the organisation needs to deliver business value continuously during the transformation. It is particularly effective for large monolithic applications serving high transaction volumes, as it allows individual capabilities to be extracted and validated independently before the next increment begins.
The duration of a monolith-to-microservices migration varies significantly based on the size and complexity of the codebase, the quality of existing tests, the number of integrations, and the team capacity available. A focused extraction of three to five bounded domains from a mid-sized monolith typically takes twelve to twenty weeks for the technical migration, followed by a stabilisation period. Larger enterprise systems with hundreds of modules, extensive data coupling, or limited automated test coverage may require eighteen to thirty-six months for a full decomposition. Our approach uses domain-driven design to identify natural seams in the application and sequences the extraction to minimise inter-service dependencies at each stage, reducing risk and delivering usable increments continuously.
Database modernisation carries risks including data loss during migration, extended downtime during cutover, degraded query performance on the target platform, and application compatibility issues with new schema designs or query syntax. Our mitigation strategy begins with a complete data audit and schema analysis to identify all consumers of each table, view, and stored procedure. We implement dual-write patterns or change-data-capture pipelines to synchronise the legacy and target databases during the transition, enabling rollback at any point. Performance benchmarking of critical query paths occurs before cutover, and a shadow-traffic testing phase validates the target database under realistic load. Zero-downtime cutovers are achieved through blue-green deployment patterns combined with traffic shifting.
Containerising applications built for traditional VM or bare-metal environments requires addressing several categories of issues: stateful storage that assumes local disk, configuration that is embedded rather than externalised, startup dependencies on other services, and logging that writes to local files rather than stdout. Our containerisation process begins with a compatibility assessment that identifies each of these anti-patterns in the target application. We then apply the twelve-factor application principles to externalise configuration, redirect logs, and refactor local state to use persistent volumes or managed storage services. Container image hardening, vulnerability scanning, and right-sizing of resource requests and limits are completed before images are promoted to production registries.
Yes. Our engagement model is designed to maintain continuous production operations throughout the modernisation programme. We use techniques such as feature flags to control the rollout of modernised components, blue-green deployments to switch traffic between old and new versions with instant rollback capability, and canary releases to expose a small percentage of production traffic to new services before full rollout. For database migrations, we employ online schema change tools and change-data-capture replication to eliminate downtime. Maintenance windows, where required at all, are typically measured in minutes rather than hours, and are scheduled outside peak business periods with rollback plans tested in advance.
Domain-driven design (DDD) provides the conceptual framework for identifying the correct boundaries of microservices, which is the most consequential decision in a decomposition programme. By mapping the business domain into bounded contexts - areas of the business with consistent language, rules, and data ownership - DDD prevents the common failure mode of creating microservices that are too fine-grained, leading to excessive network calls and distributed data management complexity. Our architects conduct event-storming workshops with business and technical stakeholders to surface the domain model, identify aggregates and domain events, and define the context map that governs how services interact. This business-grounded approach produces service boundaries that are stable over time and aligned with organisational team structures.
UI/UX uplift within an application modernisation programme goes beyond visual redesign to address the structural issues that make legacy interfaces difficult to maintain and extend. Our approach begins with a usability audit that identifies the highest-friction workflows for end users, followed by a technical assessment of the existing front-end architecture - whether it is a server-rendered monolith, a jQuery-based SPA, or a mix of both. We then design a migration path to a modern component-based framework such as React or Vue, using micro-frontend patterns where appropriate to allow incremental replacement of legacy screens. Accessibility compliance, responsive design, and integration with the modernised back-end APIs are validated through user testing before each increment goes live.
Governance and compliance requirements must be mapped to the modernised architecture before migration begins, not retrofitted afterward. Our compliance integration process identifies all regulatory obligations - such as data residency, audit logging, encryption at rest and in transit, and access control - that apply to each application and ensures the target architecture satisfies them equivalently or with improvement. For regulated industries including financial services, healthcare, and government, we produce architecture decision records and compliance traceability matrices that demonstrate how each requirement is met in the new environment. Change advisory board processes and audit trails are maintained throughout the programme so that every architectural decision and migration step is documented and reviewable.
Performance validation after modernisation uses a combination of synthetic load testing, production traffic shadowing, and real-user monitoring to confirm that the modernised application meets or exceeds the performance characteristics of the system it replaces. Prior to cutover, we establish baseline performance metrics from the legacy system covering response time percentiles, throughput, and resource utilisation under representative load profiles. The modernised application is subjected to the same load profiles in a pre-production environment, and any regressions are resolved before promotion. After cutover, real-user monitoring dashboards track latency, error rates, and throughput continuously, with alerting thresholds set to detect any degradation within minutes of it occurring.
A well-structured modernisation engagement requires a multi-disciplinary team rather than a pool of generic developers. At the leadership layer, a solution architect defines the target architecture and manages technical risk, while a delivery manager coordinates programme governance and stakeholder communication. The delivery team includes back-end engineers specialising in the source and target technology stacks, a DevOps engineer responsible for CI/CD pipeline construction and infrastructure-as-code, a database specialist for schema migration and data pipeline work, and a front-end engineer for UI/UX modernisation. A QA engineer maintains test coverage throughout each increment, and depending on the scale of the programme, multiple delivery squads may operate in parallel against different application domains.
Technical debt discovered during modernisation is catalogued in a prioritised backlog with each item classified by impact severity, remediation effort, and relationship to the migration critical path. Items that block the modernisation - such as tightly coupled modules that cannot be extracted without refactoring - are addressed within the programme. Items that represent quality improvements but do not block migration are documented and handed over as a structured remediation backlog for the client engineering team, complete with effort estimates and recommended sequencing. We do not attempt to eliminate all technical debt within a modernisation programme, as this extends timelines and budgets unnecessarily; instead, we ensure the modernised application has a lower net debt position than the system it replaces.
Application modernisation is an opportunity to establish or significantly upgrade the CI/CD and DevOps capabilities that support the modernised application long after the engagement ends. Our DevOps deliverables include a fully automated build and test pipeline for each microservice, infrastructure-as-code definitions for all cloud resources using tools such as Terraform or Pulumi, containerised deployment pipelines using Kubernetes or a managed container service, and automated security scanning integrated into the pipeline. We also establish observability infrastructure including centralised logging, distributed tracing, and metrics dashboards, and conduct knowledge transfer sessions to ensure client engineering teams can operate and extend these capabilities independently.
Application modernisation engagements are typically structured in two phases: a discovery and assessment phase, and a delivery phase. The discovery phase is time-and-materials priced and produces the migration roadmap, risk register, and total cost of ownership analysis that informs the delivery phase budget. The delivery phase can be structured as a fixed-scope contract for well-defined work packages, a time-and-materials arrangement with monthly governance checkpoints, or a managed service model where we maintain accountability for outcomes rather than activity. We recommend against fixed-price contracts for the full programme scope, as the complexity of legacy codebases consistently produces unforeseen findings that create adversarial contract dynamics.
A successful modernisation programme delivers a measurable improvement across four dimensions: business agility, operational efficiency, technical resilience, and developer experience. Business agility is evidenced by a reduction in the time required to deliver new features from months to weeks or days. Operational efficiency is demonstrated through lower infrastructure costs, typically twenty to forty percent below the legacy environment, and reduced manual operational toil through automation. Technical resilience is confirmed by improved availability metrics, faster recovery from failures, and elimination of single points of failure. Developer experience improvements are measured through reduced onboarding time for new engineers, faster local development cycles, and increased deployment frequency.
Industries
Financial ServicesHealthcareRetail and E-CommerceTelecommunicationsGovernment and Public Sector