slokit
An SLO and error-budget engine for Rust.
slokit does two things the existing tools (all Go or Python) do not do together:
- Library core with no
serde, YAML, or CLI dependencies, so error-budget and burn-rate math embeds directly inside your services (for example, an Axum handler that reports live budget status). - A generator that reads a sloth-compatible YAML spec and emits Prometheus recording rules, metadata rules, and multi-window multi-burn-rate (MWMBR) page/ticket alerts as a single static binary.
It is drop-in compatible with the sloth prometheus/v1 spec, so existing
specs work unchanged, and the generated metrics use the same slo:... names and
sloth_* labels, so your Grafana dashboards keep working.
Install
CLI
# Generate Prometheus rules from a spec
# Generate a Prometheus Operator PrometheusRule instead
# Validate a spec without generating
# Do the error-budget math from the terminal
calc output:
Objective: 99.9% over 30d
Error budget: 0.1000% of events
Total events: 1000000
Allowed bad: 1000.00
Observed bad: 250
Burn rate: 0.25x
Consumed: 25.0000%
Remaining: 75.0000%
Exhausted in: 89d 23h
Burn-rate alert thresholds (error ratio that fires each window):
page long=1h short=5m factor=14.4 threshold=1.4400%
page long=6h short=30m factor=6 threshold=0.6000%
ticket long=1d short=2h factor=3 threshold=0.3000%
ticket long=3d short=6h factor=1 threshold=0.1000%
Spec format
slokit reads the sloth prometheus/v1 spec, plus one extension: an optional
per-SLO period (sloth only offers this as a global flag).
version: "prometheus/v1"
service: myservice
labels:
owner: team-platform
slos:
- name: requests-availability
objective: 99.9
period: 30d # slokit extension; defaults to 30d
sli:
events:
error_query: sum(rate(http_requests_total{code=~"5.."}[{{.window}}]))
total_query: sum(rate(http_requests_total[{{.window}}]))
alerting:
name: MyServiceHighErrorRate
page_alert:
labels:
ticket_alert:
labels:
Library
The core has no serialization or CLI dependencies:
use ;
let slo = new;
// With a million events, 0.1% may fail: ~1,000 allowed failures.
let budget = slo.error_budget;
assert!;
// A sustained 1% error rate is a 10x burn against a 99.9% objective.
let burn = from_error_ratio;
assert!;
Generation lives behind the default spec feature:
use Spec;
use generate_rules;
let spec = from_path?;
let ruleset = generate_rules?;
println!;
# Ok::
Feature flags
| Feature | Default | Pulls in | Enables |
|---|---|---|---|
cli |
yes | clap, anyhow, spec |
the slokit binary |
spec |
yes | serde, serde_norway |
spec parsing and rule generation |
For the lean math-only core: slokit = { version = "0.1", default-features = false }.
The MWMBR model
slokit implements the burn-rate alerting from the Google SRE Workbook. For a
30-day SLO period:
| Severity | Long window | Short window | Burn rate | Budget consumed |
|---|---|---|---|---|
| Page | 1h | 5m | 14.4 | 2% |
| Page | 6h | 30m | 6 | 5% |
| Ticket | 1d | 2h | 3 | 10% |
| Ticket | 3d | 6h | 1 | 10% |
License
Licensed under either of Apache-2.0 or MIT at your option.