Scheduler Capacity Calculator
Estimate how many pods per second the Kubernetes scheduler can place on a cluster.
Inputs
Total worker nodes the scheduler evaluates.
Average time to schedule one pod (filter + score + bind).
Number of parallel scheduling workers.
percentageOfNodesToScore setting (default 50% for large clusters).
Scheduling Throughput
400.0pods/s
Pods per Minute
24,000pods/min
Nodes Scored per Pod
25nodes
Per-Thread Throughput
200.0pods/s
Step by step
Nodes scored per pod
50 × 50%
= 25
Pods/sec per thread
1000ms / 5ms
= 200.0
Total scheduling throughput
200.0 × 2
= 400.0 pods/s
How it works
The Kubernetes scheduler's throughput is bounded by scheduling latency and parallelism: throughput = (1000/latencyMs) × threads. The percentageOfNodesToScore setting limits how many nodes are evaluated per pod, trading placement quality for speed in large clusters.
Formula
Throughput
podsPerSec = (1000 / schedulingLatencyMs) × threads
- schedulingLatencyMs
- Average time to schedule one pod
- threads
- Parallel scheduling workers
Frequently Asked Questions
What increases scheduling latency?
Complex affinity/anti-affinity rules, many plugins, large numbers of nodes to score, and resource pressure on the control plane all increase per-pod scheduling time.
When does scheduler throughput become a bottleneck?
In clusters with rapid scaling (thousands of pods launching simultaneously, e.g. batch jobs or cluster-wide rolling updates), the scheduler can become a bottleneck if throughput is lower than the pod creation rate.