Key Takeaways: From Batch to Real-Time: A Full Migration Project

Architecture and Design

Real-time does not eliminate batch — it reduces dependency on batch for time-sensitive operations. Reconciliation, monitoring reports, and archival processes remain batch. The goal is to move latency-sensitive processing to real-time while keeping everything else on the reliable batch path.
Use asynchronous messaging (MQ) for cross-system integration. MQ decouples producer and consumer, providing guaranteed delivery, buffering during outages, and natural flow control. Synchronous APIs create tight coupling that can cascade failures.
Design for idempotent processing. Every message should include a unique ID. The consumer must check for duplicates before processing. MQ's guaranteed delivery may result in duplicate messages after failures.
Use persistent messages for financial data. Non-persistent messages are lost if the queue manager restarts. For any transaction involving money, data integrity, or audit requirements, persistence is mandatory.

The "and" pattern enables safe migration. During parallel run, the producer does everything it did before AND sends MQ messages. Both paths process every transaction, allowing reconciliation to verify correctness.
Optimistic locking prevents lost updates. Instead of holding database locks between SELECT and UPDATE, check that the data has not changed at UPDATE time. This reduces lock contention in high-concurrency systems.
Dead-letter queues catch processing failures. Configure BOTHRESH and BOQNAME on every production queue. Messages that fail repeatedly are moved to the DLQ instead of blocking the main queue. Monitor DLQ depth — it should always be zero.
JSON GENERATE and JSON PARSE bridge COBOL and modern systems. Enterprise COBOL v6+ can produce and consume JSON natively, enabling COBOL programs to participate in modern API ecosystems without middleware.

The parallel run is the most important phase. Running both paths simultaneously and comparing results daily is the only reliable way to prove the real-time system is correct. Shortcutting the parallel run is the fastest way to a production disaster.
The merge-compare algorithm is the standard reconciliation technique. Sort both sources by the same key. Advance through both simultaneously, comparing at each step. It is O(n) and catches matches, mismatches, and source-only records.
Standardize timestamps to UTC for cross-system integration. Timezone differences between organizations cause subtle reconciliation failures that are nearly invisible to date-based comparisons.

Real-time systems require active monitoring. Unlike batch (where you check the results in the morning), real-time failures must be detected in minutes, not hours. Monitor queue depth, DLQ depth, processing rate, error rate, and message age.
Monitor the entire message path. Queue depth at the destination is not sufficient. Also monitor transmission queues, channel status, and the age of the oldest unprocessed message.
Build flow-control into consumers. A consumer that processes messages as fast as possible will overwhelm downstream systems under burst conditions. Configurable throttling prevents DB2 contention and CICS overload.

Every cutover step must have a defined rollback. The cutover plan is not complete until every step has a tested rollback procedure. The rollback should be rehearsed before the actual cutover.
Preserve the batch infrastructure for at least 30 days after cutover. The batch system is a safety net. If the real-time system fails, batch can be reactivated within minutes. Do not decommission batch until the real-time system has proven itself in production.
Cross-organizational trust is built, not assumed. When two organizations integrate their systems, technical architecture is necessary but not sufficient. Teams must cross-train, communicate continuously, and establish shared responsibility for the integrated system.