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The batch start told the seed which LiteLLM_SpendLogs rows were its own, but using it as a hard cutoff also dropped rows another pod had already persisted. Those rows are only repaid by that pod's own increment, so if it died first the window row stayed permanently under the recorded spend. The seed now reads both sums in one scan and takes off this batch's own spend, flooring at the pre-batch total for the case where its log rows have not landed yet. Redis payloads keep an empty request_ids so a leader from before the field was dropped can still merge what it pops during a rolling deploy. Claude-Session: https://claude.ai/code/session_01QvQzYztinxj8ZuD5YxbVdL |
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| .. | ||
| base_update_queue.py | ||
| daily_spend_update_queue.py | ||
| pod_lock_manager.py | ||
| redis_update_buffer.py | ||
| spend_log_cleanup.py | ||
| spend_log_cleanup_metrics.py | ||
| spend_logs_partition_manager.py | ||
| spend_update_queue.py | ||
| tool_discovery_queue.py | ||
| window_spend_update_queue.py | ||