SLO Implementation
SkillMonitoring & opsThe slo-implementation skill guides an AI agent through defining Service Level Indicators and Service Level Objectives for a service, including choosing targets and calculating error budgets. It then writes Prometheus recording and alerting rules to measure compliance and warn when the error budget burns too fast, and outlines a Grafana dashboard for tracking reliability goals. Use it when establishing reliability targets, implementing SRE practices, or measuring service performance.
Then ask your AI: use the SLO Implementation skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Have a service whose requests, latency, or writes are already measured by metrics.
What your AI can do with it
- Define availability, latency, and durability SLIs
- Set SLO targets with a chosen window such as 28d
- Calculate error budgets from the SLO target
- Write Prometheus recording and alerting rules
- Outline a Grafana dashboard for reliability goals
Getting started
- Have a service whose requests, latency, or writes are already measured by metrics.
- Decide the SLI type and the SLO target and window you want to track.
- Ask the agent to define the SLIs and SLOs and to calculate the error budget.
- Add the generated Prometheus recording and alerting rules to your Prometheus configuration.
- Build the outlined Grafana dashboard to track the reliability goals.
What this skill tells your AI
The instructions your AI receives, as published by wshobson/agents in plugins/observability-monitoring/skills/slo-implementation/SKILL.md and read by Ahel’s review.
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
# 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)
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:
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
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
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 }}%"
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)
Additional patterns and templates
More detailed templates and worked examples live in references/details.md. Read that file for the full pattern library.
Signals
- GitHub stars
- 40k
- Forks
- 4k
- Last commit
- Oct 2026
Questions
- What is the difference between an SLI, an SLO, and an SLA?
- An SLA is a contract with customers, an SLO is an internal reliability target, and an SLI is the actual measurement. The skill works down that hierarchy from the agreement to the measurement.
- How is an error budget calculated?
- Error Budget = 1 - SLO Target. For a 99.9% availability SLO the budget is 0.1%, which is 43.2 minutes per month. The skill also outlines an error budget policy for spending it.
Advanced
- Item type
- skill
- Key
slo-implementation-wshobson- Source
- github.com/wshobson/agents
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