windmill/benchmarks

Benchmarks

Deno/TS benchmark suite for measuring Windmill job and flow execution throughput.

Quick Start

# Install Deno
curl -fsSL https://deno.land/install.sh | sh

# Run a single benchmark
deno run -A benchmark_oneoff.ts --kind noop --jobs 10000

# Run the full suite
deno run -A benchmark_suite.ts -c suite_config.json

# Run WAC v2 benchmarks (workflow-as-code vs flow comparison)
deno run -A benchmark_suite.ts -c suite_wac.json

Benchmark Kinds

Script benchmarks

• noop — Empty jobs (measures pure scheduling overhead)
• deno, bun, python, go, bash — Language runtimes
• nativets — BunNative (no isolation)
• dedicated, dedicated_nativets — Dedicated worker mode

Flow benchmarks

• 2steps — 2-step flow (deno + identity)
• bigscriptinflow — Flow with large raw bash script
• flow_seq_2_bun — 2 sequential bun steps
• flow_par_2_bun — 2 parallel bun steps (branchall)
• flow_seq_3_bun — 3 sequential bun steps
• flow:<path> — Custom flow by path
• script:<path> — Custom script by path

WAC v2 benchmarks (workflow-as-code)

• wac_seq_2 — 2 sequential tasks
• wac_par_2 — 2 parallel tasks (Promise.all)
• wac_seq_3 — 3 sequential tasks
• wac_inline_2 — 2 inline steps (no child jobs)

Suite Configs

File	Description
suite_config.json	Main benchmark suite (noop, languages, flows)
suite_dedicated.json	Dedicated worker benchmarks
suite_dedicated_nativets.json	Dedicated NativeTS benchmarks
suite_wac.json	WAC v2 vs flow comparison benchmarks

Interactive Benchmark Tool

deno run -A main.ts -e admin@windmill.dev -p changeme --host http://localhost:8000

Options: --workers, --seconds, --maximum-throughput, --use-flows, --script-pattern, --export-json, --export-csv

Graph Generation

deno run -A benchmark_graphs.ts -c graphs_config.json

Generates SVG graphs from *_benchmark.json data files.

CI

The GitHub Actions workflow (.github/workflows/benchmark.yml) runs hourly with 1/4/8 worker configurations plus WAC benchmarks. Results are committed to the benchmarks branch.

Cluster benchmarks — sim mode

Provisioning + measuring throughput on a real multi-node Kubernetes cluster (minikube + helm + per-pod cgroup sampling + PG analysis) is a separate workflow on top of main.ts. See sim/README.md for:

• bringing up the cluster (wm_sim up)
• firing a phased or flood workload from workloads/
• the consolidated dashboard with throughput, queue depth, per-node CPU + oversaturation, PG latency / conn counts, OOM events, restart events
• the JSONL poller pipeline + reliability fixes (sampler host-log, rollout- complete readiness, procs_running oversaturation)

Quick path:

# Provision cluster + deploy Windmill (foreground; Ctrl-C tears down).
# Prints `[helm] API reachable at http://127.0.0.1:<port>` — note the port.
# Port-forward stays alive as a child of wm_sim, so keep this terminal open.
wm_sim up \
  --topology    sim/topologies/k8s-4node.json \
  --helm        ../windmill-helm-charts/charts/windmill \
  --helm-values sim/values/smoke.yaml \
  --helm-values sim/values/local.yaml

# In another shell — fire bench against the wm_sim-managed port:
deno run -A main.ts \
  --host http://127.0.0.1:<port> \
  --token <admin-token> \
  --workload-config workloads/io_150ms_flood.json \
  --minikube-profile wm-sim-k8s-4node \
  --wait-ready 60

# Report appears at reports/<timestamp>/dashboard.svg