Design a Real-Time Gaming Stream Metrics Aggregator

Shows a scalable distributed message broker or ingestion buffer capable of absorbing high-throughput streaming telemetry without dropping events during bursts.

Demonstrates a clear stream processing topology that handles stateful rolling aggregations and window calculations accurately under high event volumes.

Selects appropriate storage engines for real-time low-latency reads versus long-term historical cold storage, explaining trade-offs in consistency and query performance.

Accurately converts monthly totals and peak ratios into peak throughput rates, using those figures to size the ingestion and compute layers.

Addresses how the pipeline handles upstream telemetry floods, network partitions, and downstream consumer lag without systemic failure.

Every functional requirement in the brief is visibly served by something on the board, and the non-functional targets are addressed rather than ignored.

Components are labelled, data flows are drawn as connections between them, and the direction of each flow is unambiguous.