Shadow Mode Architecture and Traffic Flow

Shadow Architecture: A traffic mirroring setup where production requests are duplicated to the shadow model. The production path serves users normally while the shadow path processes the same requests in parallel, logging results without affecting user experience.
Traffic Mirroring Patterns
Synchronous mirroring: Request arrives, load balancer duplicates it to both production and shadow, waits for production response, returns to user (shadow response discarded). Shadow latency does not affect user experience but increases load balancer complexity. Asynchronous mirroring: Request logged to a queue (Kafka, SQS), shadow model consumes from queue. Decouples shadow processing from request path, but introduces delay between request and shadow evaluation. Choose synchronous for latency validation, asynchronous for pure prediction comparison.
Isolation Requirements
Shadow model failures must not affect production. Isolation mechanisms: separate infrastructure (different pods, different nodes), resource limits (CPU/memory caps prevent shadow from starving production), circuit breakers (disable shadow if it starts failing), and network isolation (shadow cannot make calls that modify state). The principle: shadow can observe but never mutate. If shadow mode can crash production or corrupt data, it defeats the purpose of risk-free validation.
Logging and Comparison
Log both predictions with matching request IDs for later analysis. Essential fields: request ID (to join production and shadow), timestamp, input features (for debugging divergences), production prediction, shadow prediction, and latency for both. Store logs in a queryable system (data warehouse, time-series database) for analysis. Dashboard should show: prediction agreement rate, latency comparison, error rate comparison, and feature coverage (what percentage of production requests shadow successfully processed).
Implementation Choice: Start with asynchronous mirroring (simpler, lower risk), graduate to synchronous when you need accurate latency measurement.

💡 Key Takeaways

✓Synchronous mirroring validates latency; asynchronous decouples shadow from request path

✓Shadow must be isolated: separate resources, circuit breakers, no state mutations

✓Log both predictions with matching request IDs for comparison analysis

📌 Interview Tips

1Synchronous: load balancer duplicates to both, returns production response only

2Dashboard shows agreement rate, latency comparison, error rates

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