Skip to content

Thresholds and Budgets

Load thresholds, failure budgets, and scenario expectations are stored as reviewable data instead of implicit dashboard memory.

Purpose

Use this page to understand how Atlas classifies acceptable latency, error, saturation, survival, and degradation behavior across its load scenarios.

Source of Truth

  • ops/load/thresholds/
  • ops/load/contracts/k6-thresholds.v1.json
  • ops/load/contracts/performance-regression-thresholds.json

Threshold Classes

Atlas thresholds fall into five operational classes:

  • latency thresholds such as p95_ms and p99_ms
  • error-rate thresholds such as fail_rate
  • saturation thresholds for CPU, disk, thread pools, and queue pressure
  • survival thresholds for cheap-path or degraded-mode availability
  • degradation thresholds for scenarios like rollout under load, pod churn, and store outage

Threshold Relationships

  • ops/load/contracts/k6-thresholds.v1.json defines the shared scenario-level defaults that many suites inherit
  • ops/load/thresholds/*.thresholds.json holds per-scenario files for the operational surface under review
  • ops/load/contracts/performance-regression-thresholds.json defines the allowed delta between an approved baseline and a candidate run

How Operators Should Use Them

  1. start from the scenario-specific threshold file when it exists
  2. cross-check the matching values in k6-thresholds.v1.json
  3. compare candidate results to the approved baseline and the regression percentage thresholds
  4. escalate any change that claims success while only meeting a weaker local threshold set
  • ops/load/thresholds/
  • ops/load/contracts/k6-thresholds.v1.json
  • ops/load/contracts/performance-regression-thresholds.json