SLA, SLO, SLI: The Pillars of Reliable Service Operation

As your systems grow more complex, handshake agreements of "we'll keep it running" no longer cut it. Users expect reliability, management wants accountability, and your team needs clear targets. Enter the world of service level frameworks.

But if you've ever been confused about the alphabet soup of SLA, SLO, and SLI, you're not alone. Let's break down these concepts with practical examples that will help you implement them in your own environment.

The Service Level Triangle: Promises, Targets, and Measurements

┌─────────────────┐
           │                 │
           │      SLA        │
           │                 │
           │  The Promise    │
           │  (External)     │
           │                 │
           └────────┬────────┘
                    │
                    ▼
           ┌─────────────────┐
           │                 │
           │      SLO        │
           │                 │
           │   The Target    │
           │   (Internal)    │
           │                 │
           └────────┬────────┘
                    │
                    ▼
           ┌─────────────────┐
           │                 │
           │      SLI        │
           │                 │
           │ The Measurement │
           │    (Actual)     │
           │                 │
           └─────────────────┘

Each of these components plays a crucial role in ensuring your services remain reliable and your business maintains customer trust.

SLA: The Contract (What You Promise)

An SLA (Service Level Agreement) is your formal promise to customers. It defines what they can expect and what happens when those expectations aren't met.

Real-World SLA Example

SERVICE LEVEL AGREEMENT

Service: E-commerce Platform API
Coverage: 24/7/365

Uptime Commitment: 99.9% monthly availability
- Measured as: (Total minutes in month - Downtime minutes) / Total minutes
- Excludes: Scheduled maintenance (with 5 days notice)

Response Time Commitment: 95% of requests within 300ms

Remedy for Breach:
- <99.9% but >99.0%: 10% service credit
- <99.0% but >95.0%: 25% service credit
- <95.0%: 50% service credit

Reporting: Monthly availability report provided by the 5th of following month

This uptime contract sets clear expectations and consequences. For an e-commerce platform, 99.9% uptime still permits about 43 minutes of downtime per month—enough to impact business but realistic for many SMEs.

The Math Matters: Understanding Availability Percentages

Many teams don't realize what their SLA actually permits:

Availability    Downtime per year    Downtime per month    Downtime per week
99%             3.65 days            7.31 hours            1.68 hours
99.9%           8.77 hours           43.83 minutes         10.08 minutes
99.95%          4.38 hours           21.92 minutes         5.04 minutes
99.99%          52.60 minutes        4.38 minutes          1.01 minutes
99.999%         5.26 minutes         26.30 seconds         6.05 seconds

Choose your service level commitments carefully—they have real business implications.

SLO: The Internal Target (What You Aim For)

Service Level Objectives (SLOs) are your internal targets—typically stricter than your SLAs. Think of them as your early warning system.

How SLOs Protect Your SLAs

// Pseudocode for SLO-based alerting
function checkServiceLevels(service) {
  const availability = calculateAvailability(service);

  // Your SLA promises 99.9% uptime
  const slaThreshold = 99.9;

  // Your SLO targets 99.95% uptime
  const sloThreshold = 99.95;

  if (availability < sloThreshold && availability >= slaThreshold) {
    alertTeam(`WARNING: ${service} availability at ${availability}% - below SLO!`);
  } else if (availability < slaThreshold) {
    alertTeam(`CRITICAL: ${service} availability at ${availability}% - SLA BREACH!`);
    escalateToManagement();
  }
}

Setting your SLOs higher than your SLAs creates a buffer zone where you can address issues before they affect your contractual obligations.

Practical SLO Examples

For a typical web application:

Availability SLO: 99.95% uptime (stricter than 99.9% SLA)
Latency SLO: 90% of requests complete within 200ms (stricter than 300ms SLA)
Error Rate SLO: Less than 0.1% of requests result in 5xx errors (might not be in SLA but tracked internally)

SLI: The Measurements (What Actually Happens)

Service Level Indicators (SLIs) are your actual performance metrics—the SLA metrics that tell you whether you're meeting your objectives.

Common SLIs and How to Track Them

# Example Prometheus query for HTTP success rate SLI
sum(rate(http_requests_total{status=~"2.."}[1h])) / sum(rate(http_requests_total[1h])) * 100

# Example Prometheus query for 90th percentile latency SLI
histogram_quantile(0.9, sum(rate(http_request_duration_seconds_bucket[1h])) by (le))

Effective website uptime monitor tools should collect these metrics continuously and store them for historical analysis.

The Four Golden Signals as SLIs

Google's Site Reliability Engineering (SRE) team recommends focusing on these core metrics:

Latency: How long does it take to serve a request?
Traffic: How many requests is your system handling?
Errors: What percentage of requests are failing?
Saturation: How "full" is your system?

These form the foundation of most service level monitoring strategies.

Implementing Service Levels in the Real World

Let's walk through a practical implementation:

Step 1: Define What Matters to Your Users

Start by identifying what your users actually care about. For an e-commerce platform:

User Expectation               Technical SLI
-------------------            -------------
"The site loads quickly"    →  Page load time < 2s
"I can always check out"    →  Checkout success rate > 99.9%
"My orders are accurate"    →  Order error rate < 0.1%
"I can find what I need"    →  Search success rate > 95%

These user-centric metrics should drive your SLA definitions and metrics.

Step 2: Set Realistic Targets

Review your historical performance data before setting SLOs:

# Pseudocode for analyzing historical performance
def analyze_historical_performance(service, metric, lookback_days=90):
    data = fetch_metric_history(service, metric, lookback_days)

    p50 = calculate_percentile(data, 50)
    p90 = calculate_percentile(data, 90)
    p99 = calculate_percentile(data, 99)

    worst_day = find_worst_day(data)

    print(f"Metric: {metric}")
    print(f"P50 (median): {p50}")
    print(f"P90: {p90}")
    print(f"P99: {p99}")
    print(f"Worst day: {worst_day.value} on {worst_day.date}")

    recommended_slo = p90  # Start with 90th percentile as SLO
    recommended_sla = p50  # Start with median as SLA

    return recommended_slo, recommended_sla

Don't pull numbers out of thin air—base them on what your system can actually deliver.

Step 3: Implement Comprehensive Monitoring

Your uptime monitoring must capture all SLIs and alert on SLO violations:

# Example Prometheus alert rule for SLO
groups:
- name: SLO_Alerts
  rules:
  - alert: SLOAvailabilityBreach
    expr: avg_over_time(service_availability[1h]) < 99.95
    for: 15m
    labels:
      severity: warning
    annotations:
      summary: "Service availability below SLO"
      description: "Service {{ $labels.service }} availability at {{ $value }}% (below 99.95% SLO)"

Modern monitor uptime tools should offer built-in support for SLA metrics tracking and alerting.

Step 4: Create an Error Budget

Error budgets transform your SLOs into actionable development guidance:

Monthly Error Budget Calculation:

Total minutes in month: 43,200 (30 days)
SLO: 99.95% uptime
Allowed downtime: 43,200 * (1 - 0.9995) = 21.6 minutes

Current month-to-date downtime: 5.3 minutes
Remaining error budget: 16.3 minutes

When your error budget is high, you can take more risks with deployments. When it's low, focus on stability.

Step 5: Establish Communication Workflows

Define clear protocols for SLA breaches:

SLO Breach (Warning):
1. Notify engineering team via Slack
2. Begin investigation within 15 minutes
3. Document issue in internal tracker
4. Resolve before it affects SLA

SLA Breach (Critical):
1. Notify engineering AND management via PagerDuty
2. Begin incident response immediately
3. Assign incident commander
4. Customer success team prepares communications
5. Post-incident review mandatory within 48 hours

These workflows should be documented and practiced regularly.

Tools That Make Service Level Monitoring Easier

Several tools can help implement effective service level monitoring:

Prometheus + Grafana: Open-source monitoring stack with excellent SLI tracking
Datadog: Commercial platform with built-in SLO features
Bubobot: Provides comprehensive website uptime monitor capabilities with some of the shortest monitoring intervals available

Key features to look for:

High-frequency checks (the shorter the interval, the faster you can respond)
Historical data retention for trend analysis
Custom alert thresholds to match your SLOs
Integration with your communication tools (Slack, PagerDuty, etc.)

Lessons From the Trenches

After helping dozens of teams implement service level frameworks, here are some hard-earned lessons:

Start simple: Begin with 2-3 key metrics before expanding
Be realistic: Base SLOs on actual performance, not aspirations
Create buffers: Your SLO should be stricter than your SLA (aim for 10x less downtime)
Automate everything: Manual tracking will fail eventually
Review regularly: Service levels should evolve with your system

Remember: The goal isn't perfect uptime—it's predictable, reliable service that meets user expectations.

The Bottom Line

Service level agreements aren't just for enterprise companies. Every team responsible for production systems should understand and implement SLAs, SLOs, and SLIs.

Start with clear SLA definitions and metrics that matter to your users. Set internal SLOs that give you room to maneuver. Then track your SLIs religiously with robust uptime monitoring tools.

This foundation will help you balance feature development with reliability, communicate clearly with stakeholders, and—most importantly—sleep better at night knowing you have objective measures of success.

For in-depth guidance on implementing service levels with practical examples and templates, check out our comprehensive guide on the Bubobot blog.

SLA #SLO #SLI #UptimeMetrics

Understanding SLA, SLO, and SLI in the Context of Uptime