johnalbertini14-glitch 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:1
SLA 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 rate
Incident 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 deployments
Status 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/30min → Learn more: https://afrexai-cto.github.io/aaas/landing.html