steady-100k.yaml

# IngestBench v2 — target-shaped throughput config
#
# PURPOSE: Exercises the ~100k EPS target shape: 500-event batches, 190 req/s
#   ceiling (12 000 req/min fixed-window headroom), 1 M events.
#
# MEASURED PERFORMANCE (Apple M5, Go 1.23.0):
#   The generation pipeline renders aws.cloudtrail events at ~65 000 events/s
#   single-threaded (~372 allocs/event, CloudTrail template).  At 500 events/batch
#   that delivers ~130 batches/s — the rate-limiter ceiling (190 req/s) is never
#   the binding constraint.  Achieved EPS against the mock is ~65 500 with zero
#   429s and zero event loss across 1 M events.
#
#   The gap to 100k EPS is generation-limited, not transport-limited.  Closing
#   it is a known follow-up: generation optimisation + parallel generation (Phase 2).
#
# THROUGHPUT CAVEAT: live-run throughput is network/NIC-bound on a laptop.
#   The benchmark numbers above are measured against an in-process mock server.
#
# USAGE:
#   export IB_TOKEN=<your-token>
#   ingestbench validate --config examples/steady-100k.yaml
#   ingestbench run     --config examples/steady-100k.yaml

schema_version: "1.0"
name: steady-100k
seed: 1
mode: realtime

target:
  url: https://collector.example.com/lphc/events/json
  auth:
    scheme: x-api-key
    token_env: IB_TOKEN
  tls:
    verify: true
  batch:
    max_events: 500
    max_bytes: 512KB
  compression: none
  limits:
    # 190 req/s leaves headroom below the verified 12 000 req/min LPHC ceiling.
    max_requests_per_sec: 190
    fixed_window: 1m
  retry:
    max_attempts: 5
    backoff: exponential
    circuit_breaker: true

source:
  id: aws.cloudtrail
  version: ">=1.0"
  entities:
    hosts: 500
    users: 100

workload:
  profile: steady
  # Target EPS; achieved EPS is currently ~65k (generation-limited).
  eps: 65000
  stop:
    total_events: 1000000

observability:
  dashboard: true
  prometheus: "127.0.0.1:9090"
  report: /tmp/ingestbench-100k-report.json

slo:
  min_success_rate: 0.999
  max_p95_ms: 250