DevOps & Cloud · SLOs and error budgets
SLOStudio
Reliability you can measure.
Define each SLO in a few lines and get correct burn-rate alerts, an error budget everyone understands, and a release gate, on the monitoring you already run.
$ slo-kit status slos.yaml --prometheus http://prometheus:9090
checkout/availability 99.90% SLI 99.909% budget left 9% burn 1h 41.7x BURNING runs out in 1.6 h
checkout/latency 99.00% SLI 99.584% budget left 58% burn 1h 6.6x OK
$ slo-kit suggest slos.yaml
99.9% budget used in the worst window 101% breached <- current
99.5% budget used in the worst window 20% fits <- recommended
$ slo-kit gate slos.yaml
Release gate: closed.
The problem
Teams agree SLOs are a good idea and then stall: the burn-rate alert PromQL is hard to get right, nobody knows what target is realistic, and the error budget never actually stops a risky release.
What it does
Each SLO is a few lines of YAML: availability and latency templates, or your own PromQL
Generates Prometheus recording rules and multi-window, multi-burn-rate alerts (page on fast burn, ticket on slow burn), scaled to any SLO window
Budget status: SLI, budget left, burn rates and how long until the budget runs out, with plain advice
Release gate for CI: blocks deploys while a budget is spent or burning
Suggests the objective your history supports, so targets match how the service really behaves
Monthly report in text, Markdown or HTML with a bar per day and the worst days
Grafana dashboard and OpenSLO export
Works with Prometheus, Thanos, Mimir, VictoriaMetrics and Grafana Cloud, or a CSV exported from Datadog, New Relic or CloudWatch
How it works
- Write the SLOs for your key services
- Load the generated alert rules and dashboard
- Gate releases on the budget and review the monthly report
Works with
Runs in your CI
# Before a production deploy
slo-kit gate slos/ --prometheus $PROMETHEUS_URL
# Alert rules, regenerated on every change
slo-kit rules slos/ --out slo-rules.yml
Your data
- Reads metrics only; nothing is written to your monitoring.
- SLO definitions live in git, next to the code they describe.
- Runs anywhere Python runs, with no agent or database.
Who it's for
Questions
Which alerts does it generate?
Multi-window, multi-burn-rate alerts: a page when the budget is burning fast, a ticket when it's burning steadily, scaled to your SLO window.
How do we pick a target?
suggest reads your history and recommends the highest objective that would still have left a quarter of the budget in your worst month.
Related
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A 30-minute call. We run the product on your export, repository or document and walk you through the results.