fix(dataplane): fix batch replay oom

[olamilekan000]

Change fixes a batch replay OOM risk where the handler defaulted to
a 2B(2000000000) page size and loaded all matching events into memory in one request.
It caps page size at 1000, paginates through results in
BatchReplayEventService, and applies pagination middleware to batch replay
routes.

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Note

Medium Risk
Changes event replay throughput and behavior on mid-run failures (partial replays may occur); memory risk is reduced but large replays still enqueue many queue jobs in one request.

Overview
Fixes batch replay OOM by stopping the handler from forcing an enormous single-page fetch (~2B events) and loading everything into memory at once.

NormalizeBatchReplayPageable (page size 1000, forward direction, cursors reset from the start) is applied in BatchReplayEvents and BatchReplayEventService, which now loops through LoadEventsPaged until there is no next page. Dashboard list-view cursors are ignored so replay starts from the full filtered set, not a UI page.

If a fetch fails after some replays, the API returns 500 with success/failure counts and an incomplete message instead of a generic error only.

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[mekilis]

This changes batch replay semantics when the caller includes list pagination params. The dashboard filter type already carries next_page_cursor, prev_page_cursor, and direction, and batchReplayEvent() sends the saved queryParams to /events/batchreplay. With this middleware, the replay starts from that cursor while /countbatchreplayevents still counts the full filter set, so the confirmation count can say N events but only the current page/window is replayed.

For a bulk replay endpoint, we should ignore caller cursors and use pagination only internally: start from the first cursor, force direction=next, cap perPage, and loop until done. Alternatively, do not attach middleware.Pagination to this route and let BatchReplayEventService build its own internal pageable.