Migration Factory
A repeatable operating model for delivering migration waves at scale.
Jiva Technologies designs and operates the migration factory that stands behind cloud programs — governance, migration pods, standardized playbooks, automated tracking and evidence-based change control — so successive waves ship at consistent quality and cadence.
Discovery, build, migrate, validate and cutover playbooks reused and refined wave after wave.
Migration pods sized to the wave backlog and workload complexity, with defined roles and steering cadence.
Runbooks, checklists, test results and cutover evidence captured for audit and continuous improvement.
What we deliver
Factory Governance & Delivery Model
Program-level governance covering intake criteria, RACI, steering cadence, risk register, decision log and evidence — the operating model that turns individual waves into a repeatable delivery capability.
Standardized Discovery & Wave Intake
Standard discovery templates, dependency capture and disposition confirmation feed a controlled migration backlog and wave pipeline, so each wave enters delivery with consistent inputs.
Migration Pods & Role Definition
Dedicated migration pods staffed with architect, cloud engineers, migration engineers, testers and delivery lead — with clear responsibilities across discovery, build, migration, cutover and hypercare.
Automated Tracking, Runbooks & Evidence
Wave dashboards, runbook templates, checklist automation and cutover evidence stored for audit — status, risks and dependencies visible to sponsors, engineers and change-control boards.
Testing, Cutover & Change Control
Standard test approach across smoke, integration, performance and rollback validation, aligned to change approval, communication plans and business-freeze calendars.
Hypercare, Handover & Continuous Improvement
Structured hypercare exit criteria, knowledge transfer, retrospective feedback into playbooks and enhancement of the factory model as complexity and wave volume grow.
Why teams call us
- Every wave delivered as a one-off project
Reinventing the plan, runbook and test approach per wave slows throughput and increases execution risk.
- No shared evidence trail across waves
Cutover decisions, test results and change approvals are scattered across email and shared drives, making audit and retrospective learning difficult.
- Pod capacity mismatched to backlog
Wave volume, workload complexity and dependency depth are not translated into a realistic delivery capacity plan.
- Hypercare exit that never quite completes
Waves stay in hypercare indefinitely because exit criteria, run-team readiness and defect handover were never defined up front.
Our approach
A factory lifecycle that industrializes wave delivery — from intake through cutover, hypercare exit and continuous improvement.
- Assess
Review the migration backlog, wave intake criteria, existing tooling and delivery capacity. Identify governance, automation and evidence gaps.
- Design
Define the factory operating model — pods, RACI, playbooks, runbook templates, tooling stack, dashboards and hypercare exit criteria.
- Operate
Run waves through the factory pipeline with automated tracking, change control, testing and cutover evidence captured against each workload.
- Improve
Retrospective feedback into playbooks, tooling and pod composition — scaling capacity and improving predictability as the program matures.
End-to-End IT Integration and Support
From assessment and solution design through implementation, remediation, ongoing support, and lifecycle optimization.
Fix What's Broken — Remediation Sprints
Migration stuck mid-wave, workloads over-provisioned in cloud, DevOps pipelines flaky, or FinOps spend running away? We run fixed-scope remediation sprints against a defined cloud outcome — no open-ended consulting hours.
- Landing-zone, IAM and network baseline fixes; migration wave unblocking
- Right-sizing, reserved/savings-plan coverage and FinOps waste elimination
- CI/CD pipeline hardening, IaC drift correction and release-process cleanup
Support & Maintenance — AMC-Backed
Keep cloud estates efficient and reliable after migration — cost governance, platform hygiene and vendor escalation under a Jiva managed cloud service.
- Managed cloud operations across AWS, Azure and Google Cloud with SLAs
- Continuous FinOps: budget alerts, right-sizing and commitment management
- Patching, backup verification, IaC/DevOps pipeline care and quarterly reviews
Continue exploring
Related services
- Cloud Assessment & TCO
Workload discovery, dependency mapping, 6R disposition, landing-zone readiness and TCO / ROI modeling to build a defensible migration business case.
- Cloud Migration Waves — Rehost & Replatform
Dependency-based move groups, landing-zone integration, replication, cutover, rollback and hypercare for staged rehost and replatform migrations.
- FinOps & Cost Optimization
Cost allocation, budgeting, rightsizing, commitment optimization, unit-economics reporting and continuous cloud-cost governance.
- DevOps & CI/CD Enablement
CI/CD pipelines, Infrastructure as Code, GitOps, container platforms, observability and DevSecOps to make software delivery repeatable and auditable.
- Digital & Cloud Transformation
Coordinated cloud, application, data, DevOps, low-code and FinOps delivery under a single integration, implementation and support engagement.
Migration Factory
Scale migration delivery with repeatable controls.
Design a migration factory with Jiva Technologies. The engagement defines governance, migration pods, playbooks, tooling and evidence so the program can absorb wave volume without losing control.
