Problems / Async and streaming, medium
Clickstream events pour into a topic that keeps 30 seconds of data. The analytics consumers process them slower than they arrive.
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No events lost to retention.
Like a coding problem, a solution has to pass every case, not just the one it was built for. Submit in the lab runs all 5; 2 of them are hidden until then.
2,000 requests a second for 45 seconds: 100% event (writes).
What each component does in this design, and what calls it. The simulator mimics each one from these settings.
| Component | Its job here | Settings |
|---|---|---|
| Load balancerLoad balancer | Traffic enters here.Calls Ingest API.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| Ingest APIApp service | Load balancer forwards to it.Calls Clickstream topic (publishes).Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s. | 2 replicas × 200 slots · timeout 1.0 s |
| Clickstream topicEvent stream | Ingest API publishes to it.Calls Analytics consumers.Kafka keeps order only within a partition, so the partition key decides what stays in sequence. | 6 partitions · retention 30 s |
| Analytics consumersWorker | Clickstream topic consumes from it.Queues deliver at least once, so a worker can see the same message twice. | 1 concurrent jobs |