Problems / Scaling, medium
A distributed job scheduler runs 150 jobs a second on average, but every 10 seconds the cron schedules line up and 5× as many fire at once.
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Success ≥ 99%, p99 ≤ 2 s.
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 3; 1 of them are hidden until then.
150 requests a second, with 5× bursts every 10 s for 30 seconds: 100% reads.
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 Scheduler.Layer 4 balancers route by IP and port; layer 7 balancers read HTTP and can route by path or header. | – |
| SchedulerApp service | Load balancer forwards to it.Calls Job runners.Little's law: throughput ≈ concurrency ÷ latency. 200 slots at 50 ms serve about 4,000 req/s. | 3 replicas × 200 slots · timeout 4.0 s |
| Job runnersBatch job runner | Scheduler calls it.Batch jobs process large data sets on a schedule rather than per request. | 60 slots |