cost-projection

Forward-looking cost projection that pairs with cost-budget-check:

• cost-budget-check answers "have we crossed the line?" — reactive
• cost-projection answers "when will we cross the line?" — predictive

Algorithm

1. Read all session-* records from the cost-tracking namespace (same source cost-budget-check uses).
2. Filter to a measurement window (default last 7 days on capturedAt/startedAt).
3. Compute the per-day burn rate: windowSpend / windowDays.
4. Linear-extrapolate to each requested horizon (default 7d/30d/90d/365d).
5. If a budget is configured (budget-config key set by cost-budget set):
   • Compute "days until 75% / 90% / 100% consumed" at the current rate.
   • Surface as a separate table block with ALREADY REACHED markers for thresholds already exceeded.

Flags

--window <duration> Measurement window. Nh|Nd|Nw|Nm. Default 7d. --horizons <csv> Projection horizons. Default 7d,30d,90d,365d. --format table|json Default table (markdown).

Env: PROJECTION_NAMESPACE override (default cost-tracking), PROJECTION_QUIET=1 (alias for --format json).

Smoke transcript (3 sessions × $1 over 7d, $20 budget)

| Sessions in window | 3 |
| Window spend | $3.000000 |
| **USD per day** | **$0.428571** |
| All-time spend | $3.000000 across 3 sessions |

## Projected spend (linear extrapolation)
| Horizon | Days | Projected spend |
|---|---:|---:|
| 7d | 7 | $3.0000 |
| 30d | 30 | $12.8571 |

## Budget exhaustion ($20.00 configured)
| Threshold | Target | Remaining | Time at current rate |
|---|---:|---:|---|
| 75% | $15.00 | $12.00 | 28.0 days |
| 90% | $18.00 | $15.00 | 35.0 days |
| 100% | $20.00 | $17.00 | 39.7 days |

When to use

• Finance / SRE planning: hand the JSON output to a budget dashboard for "are we on track for the quarter?".
• CI gates: cost-projection --format json | jq '.budget.exhaustion[2].daysUntilReached < 7' → fail builds when 100% exhaustion is < 1 week away.
• Post-workload-shift sanity check: after a big feature lands, re-run to verify the rate hasn't accelerated past expectations.

Stationarity assumption

Linear extrapolation assumes the current rate holds. The footer reminds operators to re-run after workload shifts. For drift detection over MULTIPLE windows, pair with cost-trend (which already covers benchmark-drift).