Mainframe Offload
Moving read traffic and selected processing off a mainframe onto modern platforms, reducing cost and unblocking new development without replacing the core.
Full mainframe replacement is expensive, multi-year and historically prone to failure. Offload delivers most of the practical benefit incrementally, and is the pragmatic default.
The mechanism: change data capture from the transaction log — not polling, because a query against a mainframe database consumes MIPS, which is billed and is the constraint — streamed into a modern data store that serves read traffic. Queries, reporting, APIs and new applications hit that store, never the mainframe.
What it achieves: cost reduction, since mainframe capacity is charged by consumption and read traffic is usually the majority; latency improvement for consumers; and — most importantly — new development becomes possible without mainframe change, which removes the specialist-skills bottleneck that constrains everything.
What it does not achieve: the mainframe remains the system of record for writes, and the core transaction processing stays where it is. That is an acceptable outcome and should be stated at the start, so the programme is judged on the benefit rather than on reaching zero.
The design requirements: an anti-corruption layer so the mainframe's data model does not become the new contract; explicit staleness bounds, since the read store lags by seconds; and reconciliation against the mainframe, because CDC has failure modes and the batch extract you already have is a free correctness check.