- name
- sla-monitor
- description
- Set up SLA monitoring and uptime tracking for AI agents and services. Generates monitoring configs, alert rules, and incident response playbooks. Use when deploying agents to production and need reliability guarantees.
SLA Monitor Skill
Purpose
Help teams set up production-grade monitoring for AI agents and automated services. Covers uptime tracking, response time SLAs, error budgets, and incident escalation.
When to Use
- Deploying AI agents to production
- Setting up monitoring for client-facing automation
- Creating SLA documentation for service agreements
- Building incident response procedures
Monitoring Stack Options
Option 1: UptimeRobot (Free tier available)
- 50 monitors free, 5-minute intervals
- HTTP, keyword, ping, port monitors
- Email + Slack + webhook alerts
Option 2: Better Stack (Formerly Uptime.com)
- Status pages included
- Incident management built-in
- Free tier: 10 monitors
Option 3: Self-Hosted (Uptime Kuma)
docker run -d --restart=always -p 3001:3001 -v uptime-kuma:/app/data --name uptime-kuma louislam/uptime-kuma:1SLA Tiers
Tier 1: Standard ($1,500/mo)
- 99.5% uptime guarantee (43.8h downtime/year)
- Response within 4 hours (business hours)
- Monthly performance report
Tier 2: Professional ($3,000/mo)
- 99.9% uptime guarantee (8.76h downtime/year)
- Response within 1 hour (business hours)
- Weekly performance reports
- Quarterly optimization reviews
Tier 3: Enterprise ($5,000+/mo)
- 99.95% uptime (4.38h downtime/year)
- Response within 15 minutes (24/7)
- Real-time dashboard access
- Dedicated support channel
Alert Configuration Template
monitors:
- name: "Agent Health Check"
type: http
url: "https://your-agent-endpoint/health"
interval: 300 # 5 minutes
alerts:
- type: email
threshold: 1 # alert after 1 failure
- type: slack
webhook: "${SLACK_WEBHOOK}"
threshold: 2 # alert after 2 consecutive failures
- type: sms
threshold: 3 # escalate after 3 failures
- name: "API Response Time"
type: http
url: "https://your-agent-endpoint/api"
interval: 60
expected_response_time: 2000 # ms
alerts:
- type: slack
condition: "response_time > 5000"
error_budget:
monthly_target: 99.9
burn_rate_alert: 2.0 # Alert if burning 2x normal rateIncident Response Playbook
Severity 1 — Total Outage
- Acknowledge within 5 minutes
- Status page update within 10 minutes
- Root cause identification within 30 minutes
- Resolution or workaround within 2 hours
- Post-mortem within 24 hours
Severity 2 — Degraded Performance
- Acknowledge within 15 minutes
- Investigation within 30 minutes
- Resolution within 4 hours
- Summary report within 48 hours
Severity 3 — Minor Issue
- Acknowledge within 1 hour
- Resolution within 24 hours
- Logged for next review cycle
Error Budget Calculator
Monthly minutes: 43,200 (30 days)
99.9% SLA = 43.2 minutes downtime allowed
99.5% SLA = 216 minutes downtime allowed
99.0% SLA = 432 minutes downtime allowed
Burn rate = (actual downtime / budget) × 100
If burn rate > 50% with 2+ weeks remaining → review needed
If burn rate > 80% → freeze deploymentsStatus Page Template
Provide clients with a public status page showing:
- Current system status (operational / degraded / outage)
- Component-level status (Agent A, Agent B, API, Dashboard)
- Uptime percentage (30-day rolling)
- Incident history with resolution notes
- Scheduled maintenance windows
Next Steps
Need managed AI agents with built-in SLA monitoring? → AfrexAI handles deployment, monitoring, and maintenance for $1,500/mo → Book a call: https://calendly.com/cbeckford-afrexai/discovery-call → Learn more: https://afrexai-cto.github.io/aaas/landing.html