Latency

Check 4 — latency

Question: how expensive is a rollout end to end?

Requires a model endpoint. If none was configured, output:

{"name": "latency", "status": "N/A", "score": null, "justification": "no model endpoint provided"}

Steps

1. Read the shared rollout cache the orchestrator already generated (/tmp/envaudit_rollouts.json, produced by rlenv-audit rollouts ... -n 20 -k 8, which drives verifiers' own vf-eval engine under the hood). Do not roll out again — checks 4 and 5 share this one cache. If the file is missing but an endpoint was configured, generate it once with rlenv-audit rollouts <env> --endpoint <url> --model <name> -n 20 -k 8 --out /tmp/envaudit_rollouts.json.

2. From its timing block read mean_s, p50_s, p90_s, max_s, total_s and calls — per-rollout end-to-end times vf-eval recorded (generation plus scoring). Note max_concurrent in the cache: timings reflect generation at that concurrency (the realistic batched-rollout setting), so read them as throughput-under-load rather than single-request latency. If the cache was generated with --dummy ("dummy": true, empty timing), there is no real timing to judge — output N/A with justification "dummy rollouts — no real timing".

3. Judge the numbers in context: a per-rollout mean of a few seconds is normal for a hosted model; tens of seconds, heavy tail (p90 ≫ p50), or frequent errors mean the env's verification/tooling is slow and will bottleneck training throughput.

Output

This check is informational — reserve FAIL for pathological cases (errors on most rollouts, or absurd latency). Score reflects throughput health.

{"name": "latency", "status": "PASS|WARN|FAIL", "score": <int>,
 "justification": "<one line: mean/p90 per rollout, total, any error rate>"}