AI Monitoring and Alerting Agent

The problem

Infrastructure monitoring generates noise. Traditional alerting systems fire off emails for every threshold breach, every blip, every transient spike. On-call engineers learn to ignore most alerts because the signal-to-noise ratio is terrible. When something genuinely critical happens, the alert that matters is buried under dozens of false positives.

Even when alerts reach the right person, they typically contain raw metrics without context. An email saying "CPU at 95%" tells you something is wrong, but not why, whether it's recovering, or what to do about it. Engineers end up opening multiple dashboards, cross-referencing logs, and piecing together the story manually. What if your alerting system could do that analysis first and send you the answer?

How an agent solves this

An AI monitoring agent sits between your metrics/logs infrastructure and your team's inbox. Instead of forwarding raw alerts, it analyzes the situation first — correlating metrics, checking recent deployments, reviewing error logs — and sends a contextual email that explains what is happening, why, and what to do about it.

The agent emails from a dedicated address like alerts@yourcompany.com, and because it's a real email address, your team can reply to ask follow-up questions. "Has it recovered?" "What was the last deploy?" "Show me the error logs." The agent responds with up-to-date information in the same thread.

• Correlate metrics across services before alerting to reduce false positives
• Include probable root cause and suggested remediation in every alert
• Respond to follow-up questions with real-time status updates
• Send deploy failure notifications with commit info and rollback status
• Automatically send recovery notifications when metrics normalize

How it works with Robotomail

Robotomail provides the email layer your monitoring agent needs. Send rich HTML alerts, receive replies from engineers via webhooks, and keep incident conversations threaded so the full timeline is always accessible.

Step 1: Create an alerts mailbox

curl -X POST https://api.robotomail.com/v1/mailboxes \
  -H "Authorization: Bearer rm_your_api_key" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "address": "alerts",
  "domainId": "dom_yourcompany",
  "displayName": "Infrastructure Monitor"
}
JSON

Step 2: Send intelligent alerts

When your agent detects an anomaly, it sends an alert email with context — not just the metric value, but probable cause and suggested actions. Robotomail supports HTML emails, so you can format alerts with clear structure and emphasis.

curl -X POST https://api.robotomail.com/v1/mailboxes/mbx_alerts/messages \
  -H "Authorization: Bearer rm_your_api_key" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "to": [
    "oncall@yourcompany.com"
  ],
  "subject": "[P1] API latency spike — p99 > 2000ms",
  "bodyHtml": "<h2>API Latency Alert</h2><p><strong>Service:</strong> api-gateway</p><p><strong>Metric:</strong> p99 latency at 2,340ms (threshold: 500ms)</p><p><strong>Started:</strong> 2026-03-22 14:32 UTC</p><p><strong>Probable cause:</strong> Database connection pool exhaustion — active connections at 98/100.</p><p><strong>Suggested action:</strong> Scale up connection pool or investigate slow queries on the orders table.</p>",
  "bodyText": "API Latency Alert Service: api-gateway Metric: p99 latency at 2,340ms (threshold: 500ms) Started: 2026-03-22 14:32 UTC Probable cause: Database connection pool exhaustion — active connections at 98/100. Suggested action: Scale up connection pool or investigate slow queries on the orders table."
}
JSON

Step 3: Handle follow-up questions

Engineers can reply directly to an alert email to ask for more information. Robotomail delivers these replies to your webhook, and your agent can respond with the latest status.

{
  "event": "message.received",
  "timestamp": "2026-03-22T14:45:00Z",
  "data": {
    "message_id": "11111111-1111-4111-8111-111111111111",
    "mailbox_id": "22222222-2222-4222-8222-222222222222",
    "mailbox_address": "alerts@yourcompany.com",
    "from": "sarah@yourcompany.com",
    "to": [
      "alerts@yourcompany.com"
    ],
    "cc": [],
    "subject": "Re: [P1] API latency spike — p99 > 2000ms",
    "body_text": "What's the current status? Has it recovered?",
    "thread_id": "33333333-3333-4333-8333-333333333333",
    "received_at": "2026-03-22T14:45:00Z",
    "attachments": []
  }
}

# inReplyTo below stands for the fetched message.messageId; see the reply example below.
curl -X POST https://api.robotomail.com/v1/mailboxes/mbx_alerts/messages \
  -H "Authorization: Bearer rm_your_api_key" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "to": [
    "sarah@yourcompany.com"
  ],
  "subject": "Re: [P1] API latency spike — p99 > 2000ms",
  "bodyText": "Current status update:\n\n- p99 latency: 1,850ms (still elevated, down from 2,340ms)\n- DB connections: 95/100 active\n- Error rate: 0.3% (up from baseline 0.01%)\n\nThe spike began 13 minutes ago. No deployments in the last 2 hours. The slow query log shows 3 queries on the orders table exceeding 5s. Auto-scaling has been triggered for the read replicas.\n\nI'll send another update in 10 minutes or when metrics return to normal.",
  "inReplyTo": "<original-message@example.com>"
}
JSON

Step 4: Deploy failure notifications

Your agent can also watch your CI/CD pipeline and email the team when deploys fail, including the commit that caused the failure and whether an automatic rollback succeeded.

curl -X POST https://api.robotomail.com/v1/mailboxes/mbx_alerts/messages \
  -H "Authorization: Bearer rm_your_api_key" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "to": [
    "engineering@yourcompany.com"
  ],
  "subject": "[Deploy Failed] api-service v2.14.3",
  "bodyText": "Deploy of api-service v2.14.3 failed at 14:22 UTC.\n\nError: Health check failed after 3 retries on /health endpoint.\nCommit: abc1234 by dev@yourcompany.com\nRollback: Automatic rollback to v2.14.2 completed successfully.\n\nLogs: https://logs.internal/deploys/d_9281"
}
JSON

Key benefits

• Context, not just metrics. Every alert includes probable root cause and suggested remediation, so engineers can act immediately instead of investigating from scratch.
• Two-way communication. Reply to any alert to ask follow-up questions. The agent responds with real-time data in the same thread.
• Reduced alert fatigue. The agent correlates signals before alerting, so you get fewer, more meaningful notifications instead of raw threshold breaches.
• Incident timeline in your inbox. Threaded conversations mean the entire incident — from first alert to recovery notification — lives in a single email thread.
• Works with any monitoring stack. Your agent integrates with Datadog, Prometheus, CloudWatch, or custom metrics — Robotomail just handles the email layer.

Read the API documentation to get started, or learn more about why we built Robotomail. Get started and have your monitoring agent sending alerts in minutes — paid plans come with a 30-day money-back guarantee.

# Requires jq. Use mailbox_id and message_id from the verified webhook.
original=$(curl --fail --silent --show-error \
  "https://api.robotomail.com/v1/mailboxes/$ROBOTOMAIL_MAILBOX_ID/messages/$ROBOTOMAIL_MESSAGE_ID" \
  -H "Authorization: Bearer $ROBOTOMAIL_API_KEY") || exit 1

payload=$(printf '%s' "$original" | jq -e --arg body "Thanks, I received your message." '
  .message | if (.messageId | type == "string" and length > 0) then
    {to: [.fromAddress], subject: ("Re: " + .subject), bodyText: $body, inReplyTo: .messageId}
  else error("Original email has no Message-ID") end
') || exit 1

curl --fail --silent --show-error \
  "https://api.robotomail.com/v1/mailboxes/$ROBOTOMAIL_MAILBOX_ID/messages" \
  -H "Authorization: Bearer $ROBOTOMAIL_API_KEY" \
  -H "Content-Type: application/json" \
  --data-binary "$payload"