Data platform modernization with workload evidence and controlled cutover

Modernization starts with deployed workloads and the services they provide. The inventory connects sources, ingestion, transformation, orchestration, storage, semantic models, reports, data-science dependencies, users, roles, quality, lineage, service levels, incidents, performance, capacity, support effort, cost, upstream and downstream dependencies, and technical and business owners.

Each workload receives a documented treatment and reason. Object counts remain supporting evidence, while wave planning follows service and dependency boundaries.

• Retain temporarily or defer while evidence or ownership remains unresolved
• Retire unused or duplicated workload
• Move with minimal change
• Convert to a supported target pattern
• Refactor embedded business rules or orchestration
• Replace with a platform capability
• Rebuild when the current design cannot meet the target contract

The target architecture specifies the services workloads can depend on: onboarding and ingestion, batch and event patterns, storage zones and formats, transformation, orchestration, metadata, lineage, quality, identity and access, semantic definitions, serving, observability, recovery, deployment, capacity, unit cost, ownership, and service expectations.

Representative workloads test the target pattern with real sources, transformation logic, business meaning, access, quality, serving, performance, deployment, monitoring, cost, and operating ownership. The slice produces source-to-target mapping, converted implementation, reconciliation, performance and security evidence, deployment and rollback procedures, a runbook, and exceptions that refine later estimates.

Each wave records included workloads, dependency closure, owners, entry and exit criteria, freeze points, initial load, ongoing synchronization, conversion sequence, validation roles, consumer readiness, cutover window, rollback trigger, stabilization period, and retirement conditions.

Validation independently covers data equivalence, business and semantic equivalence, performance and service behavior, security and governance, operability, and cost.

The cutover runbook records freeze and synchronization, final delta, validation checkpoint, user approval, routing change, monitoring, rollback trigger, decision owner, and communication. Rollback remains executable until the agreed point of no return.

After cutover, the team monitors differences, failures, performance, capacity, security, adoption, and cost through stabilization. Source workloads retire only after dependencies are removed, retention needs are addressed, consumers are transferred, and the decision is recorded. Repositories, reconciliation evidence, runbooks, dashboards, support procedures, cost controls, and known exceptions transfer to named owners.