slo-implementation

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 m...

Best use case

slo-implementation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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 m...

Teams using slo-implementation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/slo-implementation/SKILL.md --create-dirs "https://raw.githubusercontent.com/ratnesh-maurya/cursor-claude-personas/main/devops-cloud-engineer/.claude/skills/slo-implementation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/slo-implementation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How slo-implementation Compares

Feature / Agentslo-implementationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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 m...

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# SLO Implementation

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

## Do not use this skill when

- The task is unrelated to slo implementation
- You need a different domain or tool outside this scope

## Instructions

- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.

## Purpose

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

## Use this skill when

- 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 Error: 0.05% = 21.6 minutes/month
- Remaining Budget: 50%

### Error Budget Policy

```yaml
error_budget_policy:
  - remaining_budget: 100%
    action: Normal development velocity
  - remaining_budget: 50%
    action: Consider postponing risky changes
  - remaining_budget: 10%
    action: Freeze non-critical changes
  - remaining_budget: 0%
    action: Feature freeze, focus on reliability
```

**Reference:** See `references/error-budget.md`

## SLO Implementation

### Prometheus Recording Rules

```yaml
# SLI Recording Rules
groups:
  - name: sli_rules
    interval: 30s
    rules:
      # Availability SLI
      - record: sli:http_availability:ratio
        expr: |
          sum(rate(http_requests_total{status!~"5.."}[28d]))
          /
          sum(rate(http_requests_total[28d]))

      # Latency SLI (requests < 500ms)
      - record: sli:http_latency:ratio
        expr: |
          sum(rate(http_request_duration_seconds_bucket{le="0.5"}[28d]))
          /
          sum(rate(http_request_duration_seconds_count[28d]))

  - name: slo_rules
    interval: 5m
    rules:
      # SLO compliance (1 = meeting SLO, 0 = violating)
      - record: slo:http_availability:compliance
        expr: sli:http_availability:ratio >= bool 0.999

      - record: slo:http_latency:compliance
        expr: sli:http_latency:ratio >= bool 0.99

      # Error budget remaining (percentage)
      - record: slo:http_availability:error_budget_remaining
        expr: |
          (sli:http_availability:ratio - 0.999) / (1 - 0.999) * 100

      # Error budget burn rate
      - record: slo:http_availability:burn_rate_5m
        expr: |
          (1 - (
            sum(rate(http_requests_total{status!~"5.."}[5m]))
            /
            sum(rate(http_requests_total[5m]))
          )) / (1 - 0.999)
```

### SLO Alerting Rules

```yaml
groups:
  - name: slo_alerts
    interval: 1m
    rules:
      # Fast burn: 14.4x rate, 1 hour window
      # Consumes 2% error budget in 1 hour
      - alert: SLOErrorBudgetBurnFast
        expr: |
          slo:http_availability:burn_rate_1h > 14.4
          and
          slo:http_availability:burn_rate_5m > 14.4
        for: 2m
        labels:
          severity: critical
        annotations:
          summary: "Fast error budget burn detected"
          description: "Error budget burning at {{ $value }}x rate"

      # Slow burn: 6x rate, 6 hour window
      # Consumes 5% error budget in 6 hours
      - alert: SLOErrorBudgetBurnSlow
        expr: |
          slo:http_availability:burn_rate_6h > 6
          and
          slo:http_availability:burn_rate_30m > 6
        for: 15m
        labels:
          severity: warning
        annotations:
          summary: "Slow error budget burn detected"
          description: "Error budget burning at {{ $value }}x rate"

      # Error budget exhausted
      - alert: SLOErrorBudgetExhausted
        expr: slo:http_availability:error_budget_remaining < 0
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "SLO error budget exhausted"
          description: "Error budget remaining: {{ $value }}%"
```

## SLO Dashboard

**Grafana Dashboard Structure:**

```
┌────────────────────────────────────┐
│ SLO Compliance (Current)           │
│ ✓ 99.95% (Target: 99.9%)          │
├────────────────────────────────────┤
│ Error Budget Remaining: 65%        │
│ ████████░░ 65%                     │
├────────────────────────────────────┤
│ SLI Trend (28 days)                │
│ [Time series graph]                │
├────────────────────────────────────┤
│ Burn Rate Analysis                 │
│ [Burn rate by time window]         │
└────────────────────────────────────┘
```

**Example Queries:**

```promql
# Current SLO compliance
sli:http_availability:ratio * 100

# Error budget remaining
slo:http_availability:error_budget_remaining

# Days until error budget exhausted (at current burn rate)
(slo:http_availability:error_budget_remaining / 100)
*
28
/
(1 - sli:http_availability:ratio) * (1 - 0.999)
```

## 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**

## Reference Files

- `assets/slo-template.md` - SLO definition template
- `references/slo-definitions.md` - SLO definition patterns
- `references/error-budget.md` - Error budget calculations

## Related Skills

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

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