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Performance Tracking

Performance tracking helps you monitor system health, identify bottlenecks, and optimize your Kaie platform for maximum efficiency. Track key performance indicators, system resources, and user experience metrics to ensure smooth operation.

System Performance Metrics

Infrastructure Metrics

Monitor the underlying infrastructure that powers your workflows.

CPU Performance

  • CPU Usage: Percentage of CPU utilization
  • CPU Load Average: Average system load
  • CPU Cores: Number of active CPU cores
  • CPU Temperature: System temperature monitoring

Memory Usage

  • RAM Usage: Random access memory utilization
  • Memory Available: Available memory for processes
  • Memory Swapping: Virtual memory usage
  • Memory Leaks: Detection of memory leaks

Storage Performance

  • Disk Usage: Storage space utilization
  • Disk I/O: Input/output operations per second
  • Disk Latency: Average disk response time
  • Storage Growth: Rate of storage consumption

Network Performance

  • Bandwidth Usage: Network bandwidth utilization
  • Network Latency: Round-trip time for network requests
  • Packet Loss: Percentage of lost network packets
  • Connection Count: Number of active connections

Application Performance

Track the performance of your Kaie application and workflows.

Response Times

  • API Response Time: Average API response time
  • Database Query Time: Database operation duration
  • Workflow Execution Time: Time to complete workflows
  • Page Load Time: Web interface loading time

Throughput

  • Requests per Second: API request throughput
  • Messages per Second: Message processing rate
  • Workflows per Hour: Workflow execution rate
  • Concurrent Users: Number of simultaneous users

Error Rates

  • API Error Rate: Percentage of failed API calls
  • Workflow Error Rate: Percentage of failed workflows
  • Database Error Rate: Percentage of failed database operations
  • Integration Error Rate: Percentage of failed integrations

Availability

  • Uptime: System availability percentage
  • Downtime: Total system downtime
  • Mean Time to Recovery: Average recovery time
  • Service Level Agreement: SLA compliance metrics

Workflow Performance

Execution Performance

Monitor how efficiently your workflows execute.
  • Average Execution Time: Mean time to complete workflows
  • Execution Time Distribution: Range of execution times
  • Slowest Workflows: Workflows with longest execution times
  • Execution Time Trends: How execution times change over time
  • CPU per Workflow: CPU usage per workflow execution
  • Memory per Workflow: Memory usage per workflow execution
  • Database Queries per Workflow: Database load per workflow
  • External API Calls per Workflow: External service usage

Node Performance

Analyze the performance of individual workflow nodes.
  • Node Execution Time: Time for each node to complete
  • Node Success Rate: Percentage of successful node executions
  • Node Error Rate: Percentage of failed node executions
  • Node Utilization: How often each node is used
  • Slowest Nodes: Identify performance bottlenecks
  • Queue Lengths: Number of pending node executions
  • Resource Contention: Competition for system resources
  • Optimization Opportunities: Suggestions for improvement

Integration Performance

External Service Performance

Monitor the performance of external integrations.

API Performance

  • API Response Time: External API response times
  • API Success Rate: Percentage of successful API calls
  • API Rate Limits: Rate limit utilization
  • API Error Analysis: Analysis of API errors

Channel Performance

  • WhatsApp API Performance: WhatsApp Business API metrics
  • Instagram API Performance: Instagram Business API metrics
  • Voice Service Performance: Voice call service metrics
  • SMS Service Performance: SMS service metrics

Database Performance

  • Query Performance: Database query execution times
  • Connection Pool: Database connection utilization
  • Lock Contention: Database lock conflicts
  • Index Usage: Database index utilization

Cache Performance

  • Cache Hit Rate: Percentage of cache hits
  • Cache Miss Rate: Percentage of cache misses
  • Cache Eviction: Cache eviction frequency
  • Cache Size: Current cache size and limits

Third-party Dependencies

Track the performance of third-party services and dependencies.
  • Service Availability: Uptime of external services
  • Service Response Time: Response times of external services
  • Service Error Rate: Error rates of external services
  • Service SLA Compliance: Adherence to service level agreements
  • Fallback Activation: How often fallbacks are used
  • Fallback Success Rate: Success rate of fallback mechanisms
  • Fallback Response Time: Response time of fallback services
  • Fallback Impact: Impact of fallbacks on user experience

User Experience Metrics

Response Time Analysis

Measure how quickly users receive responses.
  • First Response Time: Time to first response
  • Average Response Time: Mean response time
  • 95th Percentile Response Time: Response time for 95% of requests
  • Response Time by Channel: Response times across channels
  • Slow Response Analysis: Identify causes of slow responses
  • Response Time Trends: Track response time improvements
  • Performance Budgets: Set and monitor response time limits
  • Optimization Impact: Measure impact of optimizations

User Satisfaction

Track user satisfaction with system performance.
  • User Ratings: Overall user satisfaction scores
  • Performance Ratings: User ratings of system performance
  • Complaint Analysis: Analysis of performance-related complaints
  • Satisfaction Trends: How satisfaction changes over time
  • Bounce Rate: Percentage of users who leave quickly
  • Session Duration: Average time users spend in system
  • Error Encounter Rate: How often users encounter errors
  • Feature Usage: Which features users interact with most

Performance Monitoring

Real-time Monitoring

Monitor system performance in real-time.
  • System Health Dashboard: Real-time system status
  • Performance Metrics Dashboard: Live performance metrics
  • Alert Dashboard: Current system alerts and warnings
  • User Activity Dashboard: Real-time user activity
  • Application Performance Monitoring: APM tools and metrics
  • Infrastructure Monitoring: Server and network monitoring
  • Log Analysis: Real-time log analysis and alerting
  • Custom Monitoring: User-defined monitoring solutions

Alerting and Notifications

Set up alerts for performance issues.
  • Performance Alerts: Alerts for performance degradation
  • Error Alerts: Alerts for system errors
  • Capacity Alerts: Alerts for resource capacity issues
  • SLA Alerts: Alerts for SLA violations
  • Threshold Setting: Set appropriate alert thresholds
  • Alert Channels: Configure notification channels
  • Alert Escalation: Set up alert escalation procedures
  • Alert Suppression: Prevent alert spam and noise

Performance Optimization

Bottleneck Identification

Identify and resolve performance bottlenecks.
  • CPU Bottlenecks: High CPU utilization limiting performance
  • Memory Bottlenecks: Insufficient memory causing slowdowns
  • I/O Bottlenecks: Slow disk or network I/O operations
  • Database Bottlenecks: Slow database queries or connections
  • Code Optimization: Improve algorithm efficiency
  • Resource Scaling: Scale up or out resources
  • Caching: Implement caching strategies
  • Database Optimization: Optimize database queries and indexes

Capacity Planning

Plan for future performance needs.
  • Current Capacity: Current system capacity utilization
  • Growth Projections: Projected capacity needs
  • Peak Load Analysis: Analysis of peak usage periods
  • Resource Requirements: Future resource requirements
  • Vertical Scaling: Scale up existing resources
  • Horizontal Scaling: Scale out with additional resources
  • Auto-scaling: Implement automatic scaling
  • Load Balancing: Distribute load across resources

Performance Testing

Load Testing

Test system performance under various load conditions.
  • Baseline Testing: Test under normal load conditions
  • Stress Testing: Test under high load conditions
  • Spike Testing: Test sudden load increases
  • Endurance Testing: Test under sustained load
  • Throughput: Requests per second under load
  • Response Time: Response times under load
  • Error Rate: Error rates under load
  • Resource Utilization: Resource usage under load

Performance Benchmarking

Compare performance against benchmarks and standards.
  • Industry Benchmarks: Compare against industry standards
  • Historical Benchmarks: Compare against past performance
  • Competitive Benchmarks: Compare against competitors
  • Internal Benchmarks: Compare against internal targets
  • Benchmark Selection: Choose appropriate benchmarks
  • Data Collection: Collect performance data
  • Analysis: Analyze performance against benchmarks
  • Action Planning: Plan improvements based on results

Best Practices

Performance Monitoring

Establish effective performance monitoring practices.
  • Key Metrics Selection: Choose the most important metrics
  • Monitoring Frequency: Set appropriate monitoring intervals
  • Alert Thresholds: Set meaningful alert thresholds
  • Regular Reviews: Schedule regular performance reviews
  • Performance Awareness: Build performance awareness in team
  • Performance Goals: Set clear performance objectives
  • Performance Reviews: Regular performance assessments
  • Continuous Improvement: Foster continuous improvement culture

Optimization Practices

Follow best practices for performance optimization.
  • Measure First: Always measure before optimizing
  • Identify Bottlenecks: Focus on the biggest bottlenecks
  • Test Changes: Test optimizations before deploying
  • Monitor Impact: Monitor the impact of optimizations
  • Response Time Standards: Set response time targets
  • Availability Standards: Set availability targets
  • Throughput Standards: Set throughput targets
  • Quality Standards: Set quality targets

Next Steps

Explore more performance and analytics features: