SLOs have been Google's reliability standard for a decade, and they're now practical for teams your size. The broader industry adoption has produced a practical toolkit for organisations that want to manage reliability systematically.
SLI selection
A Service Level Indicator is a metric that measures a meaningful aspect of service behaviour from the user's perspective. Common SLIs: availability (percentage of requests that succeed), latency (percentage of requests completed within a threshold), and error rate (percentage of requests that return an error). The selection matters: an SLI that is easy to measure but does not correlate with user experience produces a metric that passes while users are having a bad experience.
The error budget model
An SLO defines the target for an SLI: 99.9% of requests complete within 200ms over a rolling 30-day window. If 99.9% is the target, you have 0.1% of requests as an error budget. When the budget is healthy, teams can deploy changes freely. When the budget is being consumed, reliability work takes priority over feature work. The error budget makes the cost of unreliability visible as a shared metric that both engineering and product teams own.
Setting realistic targets
The first SLO for most services should be based on observed performance, not aspirational targets. What SLI level do you actually achieve today? Set the SLO at the current level or slightly above it. Then improve. Starting with a target that requires significant engineering work before the current error budget would be met produces demoralised teams with perpetually breached SLOs.
SLO reporting tools
Azure Monitor workbooks can display SLO compliance over time from metric data. Prometheus and Grafana support SLO dashboards via recording rules that pre-calculate compliance metrics. Nobl9 and Sloth are dedicated SLO management platforms. The tooling choice is secondary to getting the SLI measurement right and the team aligned on the error budget model.