Observability

Overview

Transform your application into a transparent, observable system where you can ask questions like "why are signups failing?" and get intelligent, natural-language diagnostics that help you understand and fix issues quickly.

Key Features

• Natural Language Queries: Ask questions in plain English and get intelligent answers about your application's performance and behavior
• Distributed Tracing: Track requests across your entire system to identify bottlenecks and failure points
• Intelligent Alerting: AI-powered anomaly detection that learns your application's normal patterns
• Performance Monitoring: Real-time metrics and dashboards for application performance
• Error Tracking: Automatic error capture, grouping, and intelligent root cause analysis
• User Journey Tracking: Understand how users interact with your application and where they encounter issues

Implementation Roadmap

1. Phase 1: Basic logging and error tracking
2. Phase 2: Performance monitoring and metrics
3. Phase 3: Distributed tracing implementation
4. Phase 4: Natural language query interface
5. Phase 5: AI-powered insights and predictive analytics

Example Queries

• "Why are signups failing this week?"
• "Show me the slowest API endpoints"
• "What's causing the 500 errors in the payment flow?"
• "Which users are experiencing the most errors?"
• "How has performance changed since the last deployment?"

Tools & Technologies

• Application Performance Monitoring (APM)
• Distributed tracing (Jaeger, Zipkin)
• Centralized logging (ELK Stack, Fluentd)
• Metrics collection (Prometheus, StatsD)
• Natural language processing for queries
• Real-time dashboards and alerting