Sync Revo with your Datadog for monitoring, analytics, and performance insights.

What It Is

Revo connects to your Datadog account to read metrics, logs, alerts, and incident data—then transforms infrastructure and application monitoring into searchable, actionable intelligence that powers engineering decisions.

What It Unlocks

• Search your entire monitoring history using natural language across metrics, logs, traces, incidents, and dashboards
• Auto-detect patterns in system performance, error rates, deployment impacts, and incident frequency
• Cross-reference monitoring data with Jira issues, GitHub PRs, deployment logs, customer support tickets, and engineering meetings
• Auto-generate incident reports and post-mortems with full context—what happened, when, who was affected, and how it was resolved

How to Use It for Emails

When drafting email replies, Revo automatically pulls relevant Datadog context:

• "Is the API down?" → Revo checks Datadog metrics and recent alerts to confirm service status and error rates
• "What caused last night's outage?" → Revo searches incident logs, alert history, and trace data to summarize root cause and impact
• "How's performance been since the deployment?" → Revo pulls post-deployment metrics, compares to baseline, and flags anomalies
• Includes source links to Datadog dashboards, alerts, and incidents so you can verify data and drill deeper

Result: Emails grounded in real system data—no more "I think it's running fine" or vague status updates.

How to Use It from Chat

Ask questions directly in Revo:

• "What alerts fired in the last 24 hours?"
• "Show me error rate trends for the API service this week"
• "What incidents were opened during the last deployment?"
• "Has latency increased since yesterday's release?"
• "What's the current status of our critical SLOs?"
• "Summarize the incident from last Tuesday—what was the root cause?"

Revo searches across Datadog metrics, logs, traces, and incidents—delivering answers with dashboard links and exact timestamps.

How to Use It in Workflows

Trigger workflows FROM Datadog:

• Critical alert fires
  
  • → Pull service context and recent deployments
  • → Create P0 Jira issue
  • → Notify #engineering in Slack with alert details, affected services, and on-call engineer
  • → Draft incident update email for stakeholders
• Incident resolved
  
  • → Auto-generate post-mortem draft
  • → Cross-reference with GitHub commits and Jira tickets
  • → Extract timeline, root cause, and mitigation steps
  • → Post to #incidents for review
• SLO breach detected
  
  • → Analyze contributing factors
  • → Create engineering issue
  • → Notify leadership with trend analysis
  • → "Error budget consumed—here's why"
• Deployment anomaly
  
  • → Compare pre/post metrics
  • → Flag regressions
  • → Notify deployment owner
  • → "Latency increased 40% after deploy—investigate?"

Post results TO Slack or generate insights:

• Weekly reliability report
  
  • → "3 incidents this week, avg resolution time 45 min, top affected service: API Gateway"
  • → Post to #engineering
• Performance trends
  
  • → "CPU usage trending up 20% over 30 days—capacity planning needed?"
  • → Share with infrastructure team
• Incident summary
  
  • → "5 alerts fired during deploy window—4 auto-resolved, 1 required manual intervention"
  • → Post to #deployments
• Customer impact analysis
  
  • → Cross-reference Datadog incidents with Intercom support tickets
  • → "Login errors spiked during API incident—12 customer complaints"
  • → Notify CS and product

Result: Datadog data becomes living intelligence that feeds your engineering context—incidents auto-document, alerts trigger smart workflows, system health informs product decisions, and no outage insight gets lost. Infrastructure knowledge compounds across your entire company brain.