Advanced Topics
Deep dive into advanced concepts, performance optimization, deployment strategies, and testing best practices for Agno-Go.
Overview
This section covers advanced topics for developers who want to:
- 🏗️ Understand the architecture - Learn the core design principles and patterns
- ⚡ Optimize performance - Achieve sub-microsecond agent instantiation
- 🚀 Deploy to production - Best practices for production deployments
- 🧪 Test effectively - Comprehensive testing strategies and tools
Core Topics
Architecture
Learn about Agno-Go's modular architecture and design philosophy:
- Core interfaces (Model, Toolkit, Memory)
- Abstraction patterns (Agent, Team, Workflow)
- Go concurrency model integration
- Error handling strategies
- Package organization
Key concepts: Clean architecture, dependency injection, interface design
Performance
Understand performance characteristics and optimization techniques:
- Agent instantiation (~180ns average)
- Memory footprint (~1.2KB per agent)
- Concurrency and parallelism
- Benchmarking tools and methodologies
- Performance comparison with other frameworks
Key metrics: Throughput, latency, memory efficiency, scalability
Deployment
Production deployment strategies and best practices:
- AgentOS HTTP server setup
- Container deployment (Docker, Kubernetes)
- Configuration management
- Monitoring and observability
- Scaling strategies
- Security considerations
Key technologies: Docker, Kubernetes, Prometheus, distributed tracing
Testing
Comprehensive testing approaches for multi-agent systems:
- Unit testing patterns
- Integration testing with mocks
- Performance benchmarking
- Test coverage requirements (>70%)
- CI/CD integration
- Testing tools and utilities
Key tools: Go testing, testify, benchmarking, coverage reports
Quick Links
Performance Benchmarks
# Run all benchmarks
make benchmark
# Run specific benchmark
go test -bench=BenchmarkAgentCreation -benchmem ./pkg/agno/agent/
# Generate CPU profile
go test -bench=. -cpuprofile=cpu.out ./pkg/agno/agent/See detailed performance metrics →
Production Deployment
# Build AgentOS server
cd pkg/agentos && go build -o agentos
# Run with Docker
docker build -t agno-go-agentos .
docker run -p 8080:8080 -e OPENAI_API_KEY=$OPENAI_API_KEY agno-go-agentosTesting Coverage
Current test coverage by package:
| Package | Coverage | Status |
|---|---|---|
| types | 100.0% | ✅ Excellent |
| memory | 93.1% | ✅ Excellent |
| team | 92.3% | ✅ Excellent |
| toolkit | 91.7% | ✅ Excellent |
| workflow | 80.4% | ✅ Good |
| agent | 74.7% | ✅ Good |
Design Principles
KISS (Keep It Simple, Stupid)
Agno-Go embraces simplicity:
- Focused scope: 3 LLM providers (OpenAI, Anthropic, Ollama) instead of 8+
- Essential tools: 5 core tools instead of 15+
- Clear abstractions: Agent, Team, Workflow
- Minimal dependencies: Standard library first
Performance First
Go's concurrency model enables:
- Native goroutine support for parallel execution
- No GIL (Global Interpreter Lock) limitations
- Efficient memory management
- Compile-time optimizations
Production Ready
Built for real-world deployments:
- Comprehensive error handling
- Context-aware cancellation
- Structured logging
- OpenTelemetry integration
- Health checks and metrics
Contributing
Interested in contributing to Agno-Go? Check out:
- Architecture documentation - Understand the codebase
- Testing guide - Learn testing standards
- GitHub repository - Submit PRs
- Development guide - Development setup
Additional Resources
Documentation
Community
Next Steps
- 📖 Start with Architecture to understand core design
- ⚡ Learn about Performance optimization techniques
- 🚀 Review Deployment strategies for production
- 🧪 Master Testing best practices
Note: This section assumes familiarity with basic Agno-Go concepts. If you're new, start with the Guide section.