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Common Workflows

Learn common patterns for using the Overwatch Chrome Extension effectively.

Scenario: Production alert triggered in monitoring platform

  1. Alert Detection

    • Monitoring platform triggers alert
    • Navigate to alert details page
    • Extension automatically detects context
  2. Review Context

    • Click extension icon to review extracted data
    • Verify affected services and metrics
    • Check severity and impact scope
  3. Create Incident

    • Click “Create Incident” in overlay
    • Review pre-populated incident details
    • Add any additional context
    • Submit incident creation
  4. Get AI Guidance

    • Review suggested procedures
    • Check similar past incidents
    • Select most relevant solution
  5. Execute Resolution

    • Follow turn-by-turn guidance
    • Monitor progress in real-time
    • Document resolution steps
  6. Verify Fix

    • Confirm metrics return to normal
    • Mark incident as resolved
    • Capture learnings for team

Scenario: Investigating issue without formal alert

  1. Identify Problem

    • Notice anomaly in dashboard
    • Observe performance degradation
    • Detect error patterns in logs
  2. Report Problem

    • Press Ctrl+Shift+R or click extension icon
    • Select “Report Problem”
    • Describe issue in detail (minimum 50 chars)
  3. Provide Context

    • Extension auto-extracts dashboard context
    • Add manual details about observations
    • Select problem type and urgency
  4. Get Solutions

    • AI analyzes problem and context
    • Solutions ranked by confidence
    • Turn-by-turn guidance displayed
  5. Follow Guidance

    • Execute suggested troubleshooting steps
    • Monitor results after each step
    • Report success or failure
  6. Document Outcome

    • Mark solution as successful/unsuccessful
    • Add notes about what worked
    • Solution captured for future use

Scenario: Investigating performance degradation

  1. Detect Degradation

    • Review performance dashboards
    • Identify affected metrics
    • Note time range of issue
  2. Capture Baseline

    • Document normal performance metrics
    • Note current degraded metrics
    • Calculate deviation percentage
  3. Report with Context

    • Use on-demand reporting feature
    • Describe performance issue with metrics
    • Include baseline vs current comparison
  4. Analyze Patterns

    • AI identifies potential root causes
    • Review suggested diagnostic procedures
    • Check for recent changes
  5. Execute Diagnostics

    • Follow diagnostic procedures
    • Collect additional metrics
    • Narrow down root cause
  6. Apply Fix

    • Implement recommended solution
    • Monitor performance recovery
    • Verify return to baseline

Scenario: Issue affecting multiple monitoring platforms

  1. Initial Detection

    • Alert in primary monitoring platform
    • Check other platforms for correlation
  2. Gather Context from Each Platform

    • Use extension on each platform
    • Extract context from Datadog, New Relic, etc.
    • Note timing and correlation
  3. Create Unified Incident

    • Create single incident with primary platform
    • Add context from other platforms manually
    • Document cross-platform correlation
  4. Coordinated Investigation

    • AI analyzes multi-platform context
    • Identifies service dependencies
    • Suggests investigation order
  5. Execute Coordinated Fix

    • Follow service-specific procedures
    • Monitor all platforms during fix
    • Verify resolution across platforms
  6. Document Cascade

    • Capture how issue propagated
    • Document resolution sequence
    • Share learnings with team

Scenario: Investigating application errors

  1. Error Detection

    • Error appears in monitoring platform
    • Review error message and stack trace
    • Check error frequency and affected users
  2. Extract Error Context

    • Use extension to capture error details
    • Include stack trace and error message
    • Note affected services and endpoints
  3. Report or Create Incident

    • Use on-demand reporting for investigation
    • Or create formal incident if critical
    • Include full error context
  4. Analyze Root Cause

    • AI analyzes error patterns
    • Suggests potential code issues
    • Links to similar past errors
  5. Fix and Deploy

    • Follow suggested code fixes
    • Test fix in staging
    • Deploy to production
  6. Monitor Resolution

    • Verify error frequency decreases
    • Check affected user metrics
    • Confirm fix is effective

Speed Up Your Workflow:

ActionWindows/LinuxmacOS
Toggle OverlayCtrl+Shift+OCmd+Shift+O
Report ProblemCtrl+Shift+RCmd+Shift+R
Create IncidentCtrl+Shift+ICmd+Shift+I
Search ProceduresCtrl+Shift+PCmd+Shift+P
Capture ScreenshotCtrl+Shift+SCmd+Shift+S
Copy ContextCtrl+Shift+CCmd+Shift+C
  1. React Quickly: Extension speeds up context gathering
  2. Trust Auto-Extraction: Verify but don’t re-type extracted data
  3. Add Human Context: Supplement automated extraction with observations
  4. Follow Procedures: Don’t skip steps to save time
  5. Document Outcomes: Help improve future recommendations
  1. Be Specific: Detailed descriptions get better solutions
  2. Include Metrics: Numbers and values help AI analysis
  3. Note What You Tried: Helps eliminate ineffective solutions
  4. Select Correct Type: Accurate problem categorization improves results
  5. Report Outcomes: Successful resolutions help everyone
  1. Start with Context: Gather all available data first
  2. Use Extension Throughout: Capture context at each step
  3. Document as You Go: Don’t wait until end to document
  4. Share Learnings: Update procedures with new discoveries
  5. Close the Loop: Always report final outcome

For workflow questions, contact support@overwatch-observability.com.


Related Documentation: