Migrations
Legacy platforms do not move over a weekend. They move in waves: a defined set of applications, integrations and data at a time, each wave running alongside the system it replaces until it has proved itself. Then the next one starts.
webMethods · TIBCO · MQ · DB2 · mainframe → cloud iPaaS
Architecture overview · 3 layers
Migrations architecture
Discovery and dependency mapping come first. Then the waves, each one running in parallel with the system it replaces.
Legacy assessment
Discovery and dependency mapping surface the risks and sort workloads into migration waves.
Validation & wave migration
We rewire the integrations, test them in a parallel run, and match performance against the legacy baseline before anyone cuts over.
Modern target
Workloads settle onto cloud iPaaS, microservices and event-driven infrastructure, and the legacy systems retire.
Key capabilities
What the programme covers
Migration strategy & planning
We inventory the estate, map dependencies and score risk across ESBs, middleware, databases, mainframes and file flows. The wave roadmap comes out of that inventory.
Target platform design
The target is cloud iPaaS with API gateways, Kafka and event mesh, containerised microservices and managed databases. Observability goes in at the same time, through Grafana, ELK and distributed traces.
Application migration
Lift and shift, refactor or replace, decided application by application. Legacy ESBs, mainframes and COBOL end up on cloud iPaaS, microservices, API gateways and Kafka.
Data migration
Extract, transform and load, with schema mapping and reconciliation. We compare old against new until the record counts agree.
Integration rewiring
Point-to-point and batch patterns move onto cloud iPaaS, API gateways, event streaming and microservices. Dependent systems stay live while it happens.
Validation & testing
Integration tests across the migrated flows, benchmarks against the production baseline, and a full cutover rehearsal. Traffic only switches once those pass.
Cutover & rollback
We rehearse the production cutover and write the rollback down before the window opens. Hypercare follows, and the legacy platform retires on a set date.
Infrastructure & modernisation
Kubernetes, Docker, Terraform, GitOps and CI/CD sit underneath the target platform, with cloud-native security and observability built into the same pipeline.
Technology stack
Tooling, target and delivery
We pick these against your existing cloud investment, the shape of the legacy estate and where you want to end up.
Migration tooling
AWS DMS
Azure MigrateGoogle Cloud MigrationIBM Cloud MigrationInformaticaFivetranHVRTarget platform
IBM webMethods
Apache Kafka
SnowflakeAWSAzure
KubernetesDockerDelivery and observability
Use case · Health care
Patient data and interfaces off on-premise EAI
A healthcare provider moved patient data and its integration interfaces off on-premise EAI, wave by wave, without breaking the compliance rules that apply to clinical records.
Read the case studies →Frequently asked questions
Phased is what we recommend, every time. Each wave takes a defined set of applications, integrations, data and APIs onto the target platform, with parallel runs keeping legacy and modern systems live together. A wave is self-contained: migrate, validate, stabilise, then start the next. Business operations carry on throughout, and risk stays inside one wave rather than spanning the whole platform.
Start with the four-week assessment
Tell us which legacy platforms are in scope and what depends on them. You get back an approach and an honest view of how long it takes.