Implementing a smaller subset of the production data for testing purposes to simulate load conditions.

Continuously monitoring pipeline metrics such as latency, throughput, and error rates, and configuring alerts for when these metrics exceed predefined thresholds.

Dynamically adjusting the number of processing nodes based on current load to optimize resource utilization and cost.

Eliminating all logging and monitoring features to reduce overhead and improve processing speed.

Both B and C are effective strategies for maintaining pipeline performance under varying load conditions.