Intelligent Microservice Debugging & Analysis
Automatically understand, visualize, and debug complex microservice architectures using AI-powered graph analysis.
Built for developers who've debugged one too many microservice incidents
Modern microservice architectures are incredibly complex and debugging them is painful:
- Finding the source of an error across dozens of services is like finding a needle in a haystack
- Understanding downstream impacts when something breaks requires tribal knowledge and manual investigation
- Answering "what if I change this?" means hours of manual code archaeology across multiple repositories
- Service dependencies are scattered across repos, configs, documentation, and team knowledge
- Root cause analysis often involves jumping between logs, code, and team members
When a production error occurs, teams waste hours or even days trying to:
- Figure out which microservice actually caused the problem
- Understand which other services are affected
- Identify what changed recently that could have caused it
- Assess the blast radius before attempting a fix
AppGraph AI creates an intelligent graph memory of your entire microservice ecosystem that AI agents can reason over.
Instead of manual detective work, you get:
- Instant service dependency mapping from your GitHub repositories
- AI-powered error analysis that pinpoints the source microservice from error logs
- Visual impact analysis showing exactly which services are affected
- Natural language Q&A about your architecture and "what-if" scenarios
- Context-aware debugging that correlates errors with recent code changes
Think of it as giving your entire microservice architecture a brain that understands how everything connects and can explain what's happening when things go wrong.
- Upload GitHub repo links (single repos or entire organizations)
- Automatic analysis detects HTTP/gRPC calls, message queues, API contracts, and database dependencies
- Unified dependency graph built across all your microservices
- Interactive visualization showing how every service connects
- Paste any error log or stack trace into the chat
- AI parses and understands the error in the context of your service graph
- Pinpoints the source microservice with confidence reasoning
- Highlights all affected services (upstream and downstream impact)
- Correlates with recent changes to show what might have caused it
- Real-time visualization of your entire microservice architecture
- Visual impact highlighting when errors occur
- Click to explore endpoints, dependencies, and recent code changes
- Filter and navigate by service, protocol type, or recency
Ask anything about your architecture:
- "Which services call the payment API?"
- "If I change the
/inventory/stockendpoint, what will break?" - "Show me all services that depend on the auth database"
- "What changed in checkout-service in the last week?"
- "What's the path from user-service to notification-service?"
The AI understands your service graph and answers with precise information and visual highlights.
When you paste an error, you get:
- Likely origin service identified from error patterns
- Impact cascade visualization of all affected services
- Recent code changes that might be related
- Evidence reasoning explaining how the conclusion was reached
- Suggested next steps for investigation and remediation
- Understand the impact before making changes
- See which services depend on specific endpoints or resources
- Identify circular dependencies and architectural issues
- Assess deployment risks across service boundaries
To run the app, please visit /docs.