Kafka Consumer Lag
Simulate consumer lag growth and recovery as produce and consume rates diverge.
Lag
0
Produce
30/s
Capacity
30/s
Status
Near capacity
Lag over time (s = sim seconds)
Near capacity Lag (behind) Produced Consumed
Lag = produced − consumed. Capacity is 3 consumers × 10/s = 30/s. When produce rate (30/s) exceeds capacity, the red area only grows. Raise consumers or per-consumer rate to drain it to zero.
How this simulator works
Consumer lag = messages produced but not yet consumed. Drive produce and consume rates apart and watch lag grow or recover.
Reading the curve
- Produce rate > consumer capacity → lag climbs without bound.
- Consume capacity > produce rate → lag drains toward zero.
- Capacity = consumers × per-consumer rate, so scale consumers to recover.
Why lag matters
Lag is the real-time backlog. A small steady lag is fine; a growing lag means downstream consumers cannot keep up and event-driven systems fall behind.