SLO Implementation

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/slo-implementation

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

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

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Purpose, SLI/SLO/SLA Hierarchy, Defining SLIs, Setting SLO Targets, Error Budget Calculation, SLO Implementation.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• The task is unrelated to slo implementation
• You need a different domain or tool outside this scope
• Define service reliability targets
• Measure user-perceived reliability
• Implement error budgets
• Create SLO-based alerts

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Clarify goals, constraints, and required inputs.
2. Apply relevant best practices and validate outcomes.
3. Provide actionable steps and verification.
4. If detailed examples are required, open resources/implementation-playbook.md.
5. Current SLO compliance
6. Error budget status
7. Trend analysis

Imported Workflow Notes

Imported: 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

  .

Imported: 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

Imported: Purpose

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

Examples

Example 1: Ask for the upstream workflow directly

Use @slo-implementation to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @slo-implementation against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @slo-implementation for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @slo-implementation using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Start with user-facing services
• Use multiple SLIs (availability, latency, etc.)
• Set achievable SLOs (don't aim for 100%)
• Implement multi-window alerts to reduce noise
• Track error budget consistently
• Review SLOs regularly
• Document SLO decisions

Imported Operating Notes

Imported: 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

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/slo-implementation

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @server-management

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @service-mesh-expert

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @service-mesh-observability

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @sexual-health-analyzer

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Reference Files

• assets/slo-template.md

  - SLO definition template

• references/slo-definitions.md

  - SLO definition patterns

• references/error-budget.md

  - Error budget calculations

Imported: SLI/SLO/SLA Hierarchy

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

Imported: 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. Durability SLI

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

Reference: See

references/slo-definitions.md

Imported: Setting SLO Targets

Availability SLO Examples

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_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]))

Imported: 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

Imported: 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)

SLO Alerting Rules

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 }}%"

Imported: 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
/
(1 - sli:http_availability:ratio) * (1 - 0.999)

Imported: 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

Imported: 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.