Slo Implementation

# slo-implementation — additional patterns and templates

## Multi-Window Burn Rate Alerts

```yaml
# Combination of short and long windows reduces false positives
rules:
  - alert: SLOBurnRateHigh
    expr: |
      (
        slo:http_availability:burn_rate_1h > 14.4
        and
        slo:http_availability:burn_rate_5m > 14.4
      )
      or
      (
        slo:http_availability:burn_rate_6h > 6
        and
        slo:http_availability:burn_rate_30m > 6
      )
    labels:
      severity: critical
```

## SLO Review Process

### Weekly Review

- Current SLO compliance
- Error budget status
- Trend analysis
- Incident impact

### Monthly Review

- SLO achievement
- Error budget usage
- Incident postmortems
- SLO adjustments

### Quarterly Review

- SLO relevance
- Target adjustments
- Process improvements
- Tooling enhancements

## Best Practices

1. **Start with user-facing services**
2. **Use multiple SLIs** (availability, latency, etc.)
3. **Set achievable SLOs** (don't aim for 100%)
4. **Implement multi-window alerts** to reduce noise
5. **Track error budget** consistently
6. **Review SLOs regularly**
7. **Document SLO decisions**
8. **Align with business goals**
9. **Automate SLO reporting**
10. **Use SLOs for prioritization**


## Related Skills

- `prometheus-configuration` - For metric collection
- `grafana-dashboards` - For SLO visualization


---
name: slo-implementation
description: Define and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting. Use when establishing reliability targets, implementing SRE practices, or measuring service performance.
---

# SLO Implementation

Framework for defining and implementing Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets.

## Purpose

Implement measurable reliability targets using SLIs, SLOs, and error budgets to balance reliability with innovation velocity.

## When to Use

- Define service reliability targets
- Measure user-perceived reliability
- Implement error budgets
- Create SLO-based alerts
- Track reliability goals

## SLI/SLO/SLA Hierarchy

```
SLA (Service Level Agreement)
  ↓ Contract with customers
SLO (Service Level Objective)
  ↓ Internal reliability target
SLI (Service Level Indicator)
  ↓ Actual measurement
```

## Defining SLIs

### Common SLI Types

#### 1. Availability SLI

```promql
# Successful requests / Total requests
sum(rate(http_requests_total{status!~"5.."}[28d]))
/
sum(rate(http_requests_total[28d]))
```

#### 2. Latency SLI

```promql
# Requests below latency threshold / Total requests
sum(rate(http_request_duration_seconds_bucket{le="0.5"}[28d]))
/
sum(rate(http_request_duration_seconds_count[28d]))
```

#### 3. Durability SLI

```
# Successful writes / Total writes
sum(storage_writes_successful_total)
/
sum(storage_writes_total)
```

**Reference:** See `references/slo-definitions.md`

## Setting SLO Targets

### Availability SLO Examples

| SLO %  | Downtime/Month | Downtime/Year |
| ------ | -------------- | ------------- |
| 99%    | 7.2 hours      | 3.65 days     |
| 99.9%  | 43.2 minutes   | 8.76 hours    |
| 99.95% | 21.6 minutes   | 4.38 hours    |
| 99.99% | 4.32 minutes   | 52.56 minutes |

### Choose Appropriate SLOs

**Consider:**

- User expectations
- Business requirements
- Current performance
- Cost of reliability
- Competitor benchmarks

**Example SLOs:**

```yaml
slos:
  - name: api_availability
    target: 99.9
    window: 28d
    sli: |
      sum(rate(http_requests_total{status!~"5.."}[28d]))
      /
      sum(rate(http_requests_total[28d]))

  - name: api_latency_p95
    target: 99
    window: 28d
    sli: |
      sum(rate(http_request_duration_seconds_bucket{le="0.5"}[28d]))
      /
      sum(rate(http_request_duration_seconds_count[28d]))
```

## Error Budget Calculation

### Error Budget Formula

```
Error Budget = 1 - SLO Target
```

**Example:**

- SLO: 99.9% availability
- Error Budget: 0.1% = 43.2 minutes/month
- Current Er