跳到主要内容
知仓学习社ZHICANG

slo-implementation

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

不碰外部(只输出文字)无严重或高危命中sickn33/agentic-awesome-skills

它会碰到什么

扫了多少4 个文本文件,12 KB
它会碰到什么不碰外部(只输出文字)
命中总数0 处
命中统计严重 0 · 高 0 · 中 0 · 低 0

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

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

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

2. Latency SLI

# 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. Write Success 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

The downtime equivalents below assume a time-based SLI, a 30-day month and a 365-day year; do not convert request-based budgets to downtime without a traffic model.

| 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:

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_under_500ms
    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

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

# 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)

The exhaustion projection below assumes a constant recent burn rate. Zero burn has no finite exhaustion time; an exhausted budget must display as already exhausted. Missing telemetry is not healthy traffic.

Additional Burn-Rate Recording Rules

Include these rules in the same recording-rule group before using the alert examples:

- record: slo:http_availability:burn_rate_1h
  expr: (sum(rate(http_requests_total{status=~"5.."}[1h])) / sum(rate(http_requests_total[1h]))) / (1 - 0.999)
- record: slo:http_availability:burn_rate_6h
  expr: (sum(rate(http_requests_total{status=~"5.."}[6h])) / sum(rate(http_requests_total[6h]))) / (1 - 0.999)
- record: slo:http_availability:burn_rate_30m
  expr: (sum(rate(http_requests_total{status=~"5.."}[30m])) / sum(rate(http_requests_total[30m]))) / (1 - 0.999)

SLO Alerting Rules

groups:
  - name: slo_alerts
    interval: 1m
    rules:
      # Fast burn: 14.4x rate, 1 hour window
      # Approximately 2.14% of a 28-day budget in 1 hour at constant traffic
      - 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
      # Approximately 5.36% of a 28-day budget in 6 hours at constant traffic
      - 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:

# 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
/
slo:http_availability:burn_rate_5m

Multi-Window Burn Rate Alerts

# 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

  • [inline example](#setting-slo-targets) - 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

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

想直接用这个技能?

本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。

它属于哪个仓库

星标★ 46,490
本站分层T1
该仓技能数6676
原文件路径plugins/agentic-bundle-aas-observability-ir/skills/slo-implementation/SKILL.md

同一个仓库里的其他技能

看这个仓库的全部 6676 个技能

同名技能的其他版本

有 5 个不同仓库或目录里都有叫 slo-implementation 的技能。它们内容并不相同,别混用: