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Parallel run is a migration and rollout technique where the new system operates alongside the legacy system for a defined period to validate functionality and data reconciliation. It reduces outage risk and provides controlled fallback options. Coordination effort and operational overhead increase with system complexity.
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A parallel run operates a new and an existing solution at the same time to compare results, behavior, and operational effects before a transition.
The approach arose from the need to reduce migration and modernization risk through controlled comparison. It is common in migration patterns such as Strangler Fig and gradual cloud transitions.
Both systems receive suitable business input. A comparison layer checks results and latency while one system remains authoritative. Teams classify differences, then switch traffic only after defined acceptance criteria are met.
Old and new systems run together with an aligned data and operating model.
Business results, errors, and latency are checked against shared expectations.
A controlled switch defines when the new system becomes authoritative and how to roll back.
Parallel runs reduce critical migration risk but add cost, reconciliation, and operational work. Representative data, idempotency, privacy, and a bounded duration need decisions in advance.
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