SLOs and SLIs for Founders: A Plain Language Guide

# SLOs and SLIs for Founders: A Plain Language Guide

A Service Level Indicator (SLI) is a measurement of your system's behavior: request latency, error rate, availability percentage. A Service Level Objective (SLO) is the target you commit to hitting: "99.9% of requests complete in under 500ms." Together, SLIs and SLOs turn "the product should be reliable" from a feeling into a number. That number can be monitored, alerting can be built around it, and when the number is missed, the conversation about why becomes grounded in data rather than opinion.

What you need to know

• SLIs are the metrics; SLOs are the targets; SLAs are the customer-facing contractual commitments (which are separate from internal SLOs)
• Internal SLOs should be stricter than your customer-facing SLAs; the gap between them is your error budget
• The error budget is the most useful concept for engineering teams: it quantifies how much unreliability is acceptable in a given period
• Startups do not need a full SRE practice to benefit from SLOs; three or four well-chosen SLIs and simple targets are enough to start
• The most important SLI for most SaaS products is availability (can users reach the product) followed by error rate (what percentage of requests fail)

The core argument

The reason SLOs matter for founders is not that they are an industry best practice. It is that they force a real conversation about reliability that would otherwise happen only during incidents. Without SLOs, every outage discussion is qualitative: "we need to be more reliable." With SLOs, the discussion becomes specific: "we have used 60% of our monthly error budget in the first two weeks; here is what is consuming it."

That specificity is what makes engineering decisions tractable. If you have an error budget, you can make a deliberate choice to spend some of it on faster shipping (accepting a higher risk of minor incidents) or save it with slower, more careful releases. Without the budget framework, these tradeoffs are invisible and teams tend to either over-engineer reliability or ignore it entirely.

For Nexli, the SLI I care most about is the attendance recording API availability during school hours. A failure in that window has a real operational impact on the schools using the system. That is not the same as a failure at 3am on a Sunday. SLOs let you encode that distinction. The attendance API has a different (stricter) availability target during operating hours than the reporting module, which handles mostly async batch operations. That differentiation is only possible because the reliability targets are explicit.

The error budget framing also helps founders communicate reliability decisions to non-technical stakeholders. "We have used 80% of our reliability budget this month and we have 10 more days to go, so we should hold off on the database migration" is a more persuasive sentence than "we should be careful."

Common mistakes

1. Setting SLOs before you have SLI data. If you do not know what your current error rate or latency distribution looks like, your SLO target will be either trivially achievable or impossible. Measure first, then set targets.

1. Setting too many SLIs. Three or four well-chosen SLIs monitored consistently are better than twenty SLIs that nobody watches. Start with availability, error rate, and latency. Add more when those are under control.

1. Confusing internal SLOs with customer SLAs. Your internal SLO should be stricter than what you promise customers. The gap is your buffer. If your SLO is 99.9% and your SLA is also 99.9%, any SLO miss is automatically an SLA breach.

1. Not defining what "availability" means. A system can be "up" (returning responses) and still failing (returning 500 errors for 20% of requests). Define availability in terms of successful requests, not just server uptime.

1. Building SLOs without alerting. A target that nobody watches is a target that does not change behavior. Connect SLI monitoring to alerting that fires before you run out of error budget, not after.

Where to start

1. Pick three SLIs for your most critical user flows. For most SaaS products: availability of the login flow, error rate on the primary API, and latency on the most-used endpoint. Start with what matters most to users.

1. Measure your current baseline for two weeks before setting targets. Whatever the numbers show, add a small stretch: if your current error rate is 0.3%, target 0.2%. If your P95 latency is 800ms, target 600ms. Aggressive targets early burn goodwill; achievable targets build the habit.

1. Set up a simple dashboard. Grafana Cloud or Datadog can display your SLIs with error budget tracking in an afternoon. The dashboard does not need to be sophisticated; it needs to be visible and checked regularly.

Related reading

• Observability in 2026: Metrics, Logs, Traces
• The Error Budget: SRE for Small Teams
• The On Call Rotation That Engineers Can Actually Sustain
• Incident Response for Startups: A Playbook