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> A Practical Guide to SLOs and SLIs

Learn how to define meaningful Service Level Objectives and Indicators that actually improve your system's reliability.

#sre #observability #reliability

If you’ve worked in infrastructure or SRE, you’ve probably heard the terms SLO and SLI thrown around. But what do they actually mean in practice, and how do you implement them effectively?

What’s the Difference?

Let’s start with the basics:

  • SLI (Service Level Indicator): A quantitative measure of your service’s behavior. Think response time, error rate, or availability.
  • SLO (Service Level Objective): A target value or range for an SLI. This is your reliability goal.

Choosing the Right SLIs

The key is to measure what matters to your users. Here are some common patterns:

For API Services

availability = successful_requests / total_requests
latency_p99 = 99th percentile response time

For Batch Jobs

freshness = time since last successful run
correctness = valid_outputs / total_outputs

Setting Realistic SLOs

A common mistake is setting SLOs too aggressively. Remember:

99.99% uptime sounds great until you realize it means less than 5 minutes of downtime per month.

Start conservative and tighten over time as you improve your systems.

The Error Budget

Here’s where it gets interesting. Your error budget is the inverse of your SLO:

  • If your SLO is 99.9% availability, your error budget is 0.1%
  • This budget is “money” you can spend on deployments, experiments, and migrations

When the budget is exhausted, stop deploying new features and focus on reliability.

Next Steps

  1. Identify your critical user journeys
  2. Define SLIs that capture user experience
  3. Set initial SLOs based on historical data
  4. Implement monitoring and alerting
  5. Review and adjust quarterly

The goal isn’t perfection—it’s making informed tradeoffs between velocity and reliability.

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