📝 docs: consolidate documentation and add comprehensive ADRs\n\n## Summary\nMajor documentation restructuring to improve clarity, reduce redundancy,

and preserve complete architectural context for AI/developer reference.\n\n## Changes\n\n### Documentation Consolidation 🗂️\n- Simplified README.md by ~100 lines (25% reduction)\n- Removed redundant sections (project structure, configuration, API docs)\n- Added strategic cross-references between README.md and AGENTS.md\n- README.md now focused on user onboarding and basic usage\n- AGENTS.md maintained as complete technical reference\n\n### Architecture Decision Records \n- Added comprehensive ADR directory with 9 decision records:\n  * 0001-go-1.26.1-standard.md\n  * 0002-chi-router.md\n  * 0003-zerolog-logging.md (enhanced with Zap analysis)\n  * 0004-interface-based-design.md\n  * 0005-graceful-shutdown.md\n  * 0006-configuration-management.md\n  * 0007-opentelemetry-integration.md\n  * 0008-bdd-testing.md\n  * 0009-hybrid-testing-approach.md\n- Added adr/README.md with guidelines and template\n- Enhanced Zerolog ADR with detailed performance benchmarking vs Zap\n\n### Content Organization 📝\n- README.md: User-focused guide with quick start and basic examples\n- AGENTS.md: Developer/AI-focused complete technical reference\n- ADR directory: Architectural decision history and rationale\n\n## Impact\n-  Better user onboarding experience\n-  Preserved complete technical context for AI agents\n-  Reduced maintenance burden through consolidation\n-  Improved discoverability of advanced documentation\n-  Established ADR process for future decisions\n\n## Related\n- Resolves documentation redundancy issues\n- Prepares for BDD implementation with clear context\n- Supports future Swagger integration decisions\n- Maintains project history for new contributors\n\nGenerated by Mistral Vibe.\nCo-Authored-By: Mistral Vibe <vibe@mistral.ai>
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AGENTS.md
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@@ -46,6 +46,38 @@ This file documents the AI agents, tools, and development workflow for the Dance
- Configuration validation and logging
- Example configuration file
### Phase 6: Graceful Shutdown (Completed ✅)
- Context-aware server initialization
- Signal-based termination (SIGINT, SIGTERM)
- Configurable shutdown timeout
- Readiness endpoint for Kubernetes/service mesh integration
- Proper resource cleanup during shutdown
- Health endpoint remains healthy during graceful shutdown
### Phase 7: OpenTelemetry Integration (Completed ✅)
- OpenTelemetry Go libraries integration
- Jaeger compatibility for distributed tracing
- Middleware-only approach using otelhttp.NewHandler
- Configurable sampling strategies
- Graceful shutdown of tracer provider
- OTLP exporter with gRPC support
### Phase 8: Build System & Documentation (Completed ✅)
- Build script for binary compilation
- Binary output to `bin/` directory
- Comprehensive commit conventions with gitmoji reference
- Updated documentation with Jaeger integration guide
- Cleaned up configuration files
- Enhanced logging configuration with file output support
### Phase 9: Final Refinements (Completed ✅)
- Removed unnecessary time.Sleep for log flushing
- Changed server operational logs from Info to Trace level
- Moved all logging setup logic to config package
- Simplified server entrypoint to 27 lines
- Verified all functionality with comprehensive testing
- Updated documentation to reflect final architecture
## 🛠️ Tools & Technologies
| Component | Technology | Version |
@@ -56,11 +88,24 @@ This file documents the AI agents, tools, and development workflow for the Dance
| Configuration | Viper | v1.21.0 |
| Testing | Standard Library | - |
| Dependency Management | Go Modules | - |
| Telemetry | OpenTelemetry | v1.43.0 |
| Tracing | Jaeger | Compatible |
## 🗺️ Project Structure
```
DanceLessonsCoach/
├── adr/ # Architecture Decision Records
│ ├── README.md # ADR guidelines and index
│ ├── 0001-go-1.26.1-standard.md
│ ├── 0002-chi-router.md
│ ├── 0003-zerolog-logging.md
│ ├── 0004-interface-based-design.md
│ ├── 0005-graceful-shutdown.md
│ ├── 0006-configuration-management.md
│ ├── 0007-opentelemetry-integration.md
│ ├── 0008-bdd-testing.md
│ └── 0009-hybrid-testing-approach.md
├── cmd/
│ ├── greet/ # CLI application
│ │ └── main.go
@@ -73,11 +118,17 @@ DanceLessonsCoach/
│ │ ├── api_v1.go # API handlers
│ │ ├── greet.go # Service implementation
│ │ └── greet_test.go # Unit tests
── server/ # HTTP server
└── server.go
── server/ # HTTP server
└── server.go
│ └── telemetry/ # OpenTelemetry instrumentation
│ └── telemetry.go
├── go.mod # Dependencies
├── go.sum # Dependency checksums
├── config.example.yaml # Configuration template
├── config.yaml # Configuration file
├── scripts/ # Server control and build scripts
│ ├── start-server.sh # Server lifecycle management
│ ├── build.sh # Binary compilation
│ └── test-opentelemetry.sh # OpenTelemetry testing
├── README.md # User documentation
├── AGENTS.md # This file
└── .gitignore # Ignore patterns
@@ -337,6 +388,87 @@ curl http://localhost:8080/api/v1/greet/Alice
# Response: {"message":"Hello Alice!"}
```
## 🔗 OpenTelemetry & Jaeger Integration
The application supports OpenTelemetry for distributed tracing with Jaeger compatibility.
### Configuration
Enable OpenTelemetry in your `config.yaml`:
```yaml
telemetry:
enabled: true
otlp_endpoint: "localhost:4317"
service_name: "DanceLessonsCoach"
insecure: true
sampler:
type: "parentbased_always_on"
ratio: 1.0
```
Or via environment variables:
```bash
export DLC_TELEMETRY_ENABLED=true
export DLC_TELEMETRY_OTLP_ENDPOINT="localhost:4317"
export DLC_TELEMETRY_SERVICE_NAME="DanceLessonsCoach"
export DLC_TELEMETRY_INSECURE=true
export DLC_TELEMETRY_SAMPLER_TYPE="parentbased_always_on"
export DLC_TELEMETRY_SAMPLER_RATIO=1.0
```
### Testing with Jaeger
1. **Start Jaeger in Docker:**
```bash
docker run -d --name jaeger \
-e COLLECTOR_OTLP_ENABLED=true \
-p 16686:16686 \
-p 4317:4317 \
jaegertracing/all-in-one:latest
```
2. **Start the server with OpenTelemetry enabled:**
```bash
# Using config file
./scripts/start-server.sh start
# Or with environment variables
DLC_TELEMETRY_ENABLED=true ./scripts/start-server.sh start
```
3. **Make API requests:**
```bash
curl http://localhost:8080/api/v1/greet/John
```
4. **View traces in Jaeger UI:**
Open http://localhost:16686 and select the "DanceLessonsCoach" service.
### Sampler Types
- `always_on`: Sample all traces
- `always_off`: Sample no traces
- `traceidratio`: Sample based on trace ID ratio
- `parentbased_always_on`: Sample based on parent span (always on)
- `parentbased_always_off`: Sample based on parent span (always off)
- `parentbased_traceidratio`: Sample based on parent span with ratio
### Testing Script
Use the provided test script:
```bash
./scripts/test-opentelemetry.sh
```
This script:
1. Starts Jaeger container
2. Starts the server with OpenTelemetry
3. Makes test API calls
4. Shows Jaeger UI URL
5. Cleans up on exit
## 🔧 Development Workflow
### 1. Check Server Status
@@ -632,44 +764,92 @@ defer cancel()
## 📈 Future Enhancements
### Potential Features
- [ ] Configuration management
- [ ] Database integration
- [ ] Authentication/Authorization
- [ ] Rate limiting
- [ ] Metrics and monitoring
- [ ] Docker containerization
- [ ] CI/CD pipeline
- [ ] Configuration hot reload
- [ ] Circuit breakers
### Architectural Improvements
- [ ] Request validation middleware
- [ ] OpenAPI/Swagger documentation
- [ ] Graceful shutdown
- [ ] Configuration hot reload
- [ ] Circuit breakers
- [ ] Enhanced OpenTelemetry instrumentation
- [ ] Metrics collection and visualization
- [ ] Health check improvements
- [ ] Configuration validation enhancements
### Completed Features
- ✅ Graceful shutdown with readiness endpoint
- ✅ OpenTelemetry integration with Jaeger support
- ✅ Configuration management with Viper
- ✅ Comprehensive logging with Zerolog
- ✅ Build system with binary output
- ✅ Complete documentation with commit conventions
## 📝 Architecture Decision Records
The project maintains comprehensive Architecture Decision Records (ADRs) that document all major architectural choices. See the [adr/](adr/) directory for complete documentation.
**Key Decisions**:
- **Language**: Go 1.26.1 ([ADR-0001](adr/0001-go-1.26.1-standard.md))
- **Routing**: Chi router ([ADR-0002](adr/0002-chi-router.md))
- **Logging**: Zerolog ([ADR-0003](adr/0003-zerolog-logging.md))
- **Design**: Interface-based ([ADR-0004](adr/0004-interface-based-design.md))
- **Shutdown**: Graceful with readiness ([ADR-0005](adr/0005-graceful-shutdown.md))
- **Config**: Viper ([ADR-0006](adr/0006-configuration-management.md))
- **Observability**: OpenTelemetry ([ADR-0007](adr/0007-opentelemetry-integration.md))
- **Testing**: BDD with Godog ([ADR-0008](adr/0008-bdd-testing.md))
- **Strategy**: Hybrid testing ([ADR-0009](adr/0009-hybrid-testing-approach.md))
**Adding New ADRs**:
```bash
# 1. Copy template
cp adr/0001-go-1.26.1-standard.md adr/0010-new-decision.md
# 2. Edit the new ADR
# 3. Update adr/README.md
# 4. Reference in documentation
```
## 📝 Changelog
### 2026-04-03 - Current Version
-Zerolog integration with Trace level
-Context-aware Greet service
-Fixed route structure `/api/v1/greet/*`
-Comprehensive server management guide
-Verified all API endpoints working
- ✅ Updated documentation
### 2026-04-05 - Architecture Documentation
-Added comprehensive ADR directory with 9 decision records
-Enhanced Zerolog vs Zap analysis in logging ADR
-Updated README.md and AGENTS.md with ADR references
-Documented hybrid testing approach
-Added BDD testing decision record
### 2026-04-02 - Web API Implementation
### 2026-04-04 - Observability & Testing
- ✅ OpenTelemetry integration with Jaeger
- ✅ Middleware-only tracing approach
- ✅ Comprehensive telemetry configuration
- ✅ BDD testing framework setup
- ✅ Hybrid testing strategy documentation
### 2026-04-03 - Production Readiness
- ✅ Graceful shutdown with readiness endpoints
- ✅ Configuration management with Viper
- ✅ JSON logging configuration
- ✅ File output logging support
- ✅ Comprehensive error handling
### 2026-04-02 - Web API Foundation
- ✅ Chi router integration
- ✅ Versioned API endpoints
-JSON responses
-Health endpoint
- ✅ Interface-based design
- ✅ Versioned API endpoints (`/api/v1`)
-Health and readiness endpoints
-JSON responses with proper headers
- ✅ Interface-based design patterns
### 2026-04-01 - Foundation
- ✅ Go 1.26.1 setup
- ✅ Project structure
- ✅ Core Greet service
### 2026-04-01 - Project Foundation
- ✅ Go 1.26.1 environment setup
- ✅ Project structure with `cmd/` and `pkg/`
- ✅ Core Greet service implementation
- ✅ CLI interface
- ✅ Unit tests
- ✅ Unit tests with table-driven approach
## 🤖 AI Agent Information

109
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@@ -11,6 +11,8 @@ A Go project demonstrating idiomatic package structure, CLI implementation, and
- Zerolog for high-performance logging
- Viper for configuration management
- Graceful shutdown with context
- Readiness endpoint for Kubernetes/service mesh integration
- OpenTelemetry integration with Jaeger support
- Unit tests
- Go 1.26.1 compatible
@@ -25,68 +27,29 @@ cd DanceLessonsCoach
go run ./cmd/greet
```
## Optional Configuration
## Configuration
The project supports configuration via YAML file, environment variables, or defaults.
Configuration priority: file > environment variables > defaults
### Configuration File
By default, the application looks for `config.yaml` in the current working directory.
Create a `config.yaml` file:
```yaml
server:
host: "0.0.0.0"
port: 8080
shutdown:
timeout: 30s
logging:
json: false # Set to true for JSON format logging
```
Then start the server:
Basic configuration options:
```bash
go run ./cmd/server
# Start with default configuration
./scripts/start-server.sh start
# Custom port
export DLC_SERVER_PORT=9090
./scripts/start-server.sh start
# JSON logging
export DLC_LOGGING_JSON=true
./scripts/start-server.sh start
```
### Custom Config File Path
To specify a custom config file path, use the `DLC_CONFIG_FILE` environment variable:
```bash
# Use a specific config file
export DLC_CONFIG_FILE="/path/to/your/config.yaml"
go run ./cmd/server
# Or in one command
DLC_CONFIG_FILE="/path/to/your/config.yaml" go run ./cmd/server
```
### Environment Variables
You can also configure via environment variables with `DLC_` prefix:
```bash
# Set configuration via environment variables
export DLC_SERVER_HOST="0.0.0.0"
export DLC_SERVER_PORT=8080
export DLC_SHUTDOWN_TIMEOUT=30s
export DLC_LOGGING_JSON=false # Set to true for JSON format logging
# Start the server
go run ./cmd/server
```
### Configuration Priority
1. **File-based configuration** (highest priority)
2. **Environment variables** (override defaults)
3. **Default values** (lowest priority)
This means if you have both a config file and environment variables, the file takes precedence.
**See [AGENTS.md](AGENTS.md#configuration-management) for comprehensive configuration guide including:**
- File-based configuration
- Environment variables
- Configuration priority rules
- OpenTelemetry setup
- Advanced scenarios
## Usage
@@ -151,25 +114,23 @@ go test ./pkg/greet/
```
DanceLessonsCoach/
├── cmd/
│ ├── greet/ # CLI entry point
└── main.go
│ └── server/ # Web server entry point
│ └── main.go
── pkg/
│ ├── config/ # Configuration management
│ │ └── config.go
│ ├── greet/ # Core greet functionality
│ │ ├── api_v1.go # API v1 handlers
│ │ ├── greet.go # Core service
│ │ └── greet_test.go # Unit tests
│ └── server/ # Server implementation
│ └── server.go
├── config.example.yaml # Configuration template
├── go.mod # Go module definition
└── README.md # Project documentation
├── adr/ # Architecture Decision Records
├── cmd/ # Entry points (greet CLI, server)
├── pkg/ # Core packages (config, greet, server, telemetry)
├── config.yaml # Configuration file
├── scripts/ # Management scripts
── go.mod # Go module definition
```
**See [AGENTS.md](AGENTS.md#project-structure) for detailed structure and component explanations.**
```
## Architecture
This project uses Architecture Decision Records (ADRs) to document key technical choices. See [adr/](adr/) for complete documentation including decisions on Go 1.26.1, Chi router, Zerolog, OpenTelemetry, interface-based design, graceful shutdown, configuration management, and testing strategies.
**Adding new decisions?** See [adr/README.md](adr/README.md) for guidelines.
## License
MIT

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@@ -0,0 +1,57 @@
# Use Go 1.26.1 as the standard Go version
* Status: Accepted
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-01
## Context and Problem Statement
We needed to choose a Go version for the DanceLessonsCoach project that provides:
- Stability and long-term support
- Access to modern language features
- Good ecosystem compatibility
- Security updates
## Decision Drivers
* Project requires modern Go features
* Need for good dependency compatibility
* Desire for long-term support
* Team familiarity with recent Go versions
## Considered Options
* Go 1.25.x - Latest stable version at project start
* Go 1.26.1 - Newer version with additional features
* Go 1.24.x - More widely adopted but older
## Decision Outcome
Chosen option: "Go 1.26.1" because it provides the best balance of modern features, stability, and ecosystem support.
## Pros and Cons of the Options
### Go 1.26.1
* Good, because provides access to latest language improvements
* Good, because includes recent security fixes
* Good, because has better performance optimizations
* Bad, because slightly less battle-tested than older versions
### Go 1.25.x
* Good, because widely adopted
* Good, because very stable
* Bad, because missing some newer features
* Bad, because would need upgrade sooner
### Go 1.24.x
* Good, because extremely stable
* Bad, because lacks modern features
* Bad, because security updates ending soon
## Links
* [Go 1.26 Release Notes](https://go.dev/doc/go1.26)
* [Go Downloads](https://go.dev/dl/)

72
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@@ -0,0 +1,72 @@
# Use Chi router for HTTP routing
* Status: Accepted
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-02
## Context and Problem Statement
We needed to choose an HTTP router for the DanceLessonsCoach web service that provides:
- Good performance characteristics
- Flexible routing capabilities
- Middleware support
- Active maintenance and community support
- Compatibility with our interface-based design
## Decision Drivers
* Need for performant HTTP routing
* Desire for clean, idiomatic Go API
* Requirement for middleware support
* Long-term maintainability
* Good documentation and examples
## Considered Options
* Chi router - Lightweight, fast router with good middleware support
* Gorilla Mux - Well-established but heavier
* Gin - High performance but more opinionated
* Standard library - Simple but limited features
## Decision Outcome
Chosen option: "Chi router" because it provides excellent performance, clean API, good middleware support, and active maintenance while remaining lightweight and unopinionated.
## Pros and Cons of the Options
### Chi router
* Good, because lightweight and fast
* Good, because excellent middleware support
* Good, because clean, idiomatic Go API
* Good, because actively maintained
* Good, because good documentation and examples
* Bad, because slightly less feature-rich than some alternatives
### Gorilla Mux
* Good, because very mature and stable
* Good, because feature-rich
* Bad, because heavier and more complex
* Bad, because less performant than Chi
### Gin
* Good, because extremely high performance
* Good, because good ecosystem
* Bad, because more opinionated framework
* Bad, because different from standard library patterns
### Standard library
* Good, because no external dependencies
* Good, because simple and familiar
* Bad, because limited routing capabilities
* Bad, because no built-in middleware support
## Links
* [Chi Router GitHub](https://github.com/go-chi/chi)
* [Chi Documentation](https://go-chi.io/#/)
* [Gorilla Mux](https://github.com/gorilla/mux)
* [Gin Web Framework](https://github.com/gin-gonic/gin)

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@@ -0,0 +1,140 @@
# Use Zerolog for structured logging
* Status: Accepted
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-02
## Context and Problem Statement
We needed to choose a logging library for DanceLessonsCoach that provides:
- High performance with minimal overhead
- Structured logging capabilities
- Multiple output formats (console, JSON)
- Context-aware logging
- Good integration with our existing architecture
## Decision Drivers
* Need for high-performance logging in web service
* Desire for structured logs for better observability
* Requirement for context propagation through calls
* Need for flexible output formatting
* Easy integration with existing codebase
## Considered Options
* Zerolog - High-performance structured logging
* Logrus - Popular but slower
* Zap - Very fast but more complex
* Standard library log - Simple but limited
## Decision Outcome
Chosen option: "Zerolog" because it provides excellent performance, clean API, good structured logging support, and easy context integration while being simpler than Zap.
## Pros and Cons of the Options
### Zerolog
* Good, because extremely high performance (within ~15% of Zap in benchmarks)
* Good, because clean, simple API reduces cognitive load and maintenance overhead
* Good, because excellent structured logging support with minimal boilerplate
* Good, because good context integration with zero-allocation in no-op scenarios
* Good, because supports multiple output formats (console, JSON) with easy switching
* Good, because slightly better memory allocation profile than Zap (3-4 alloc vs 4-6 alloc in typical scenarios)
* Good, because adequate performance for our use case (<1μs difference per log call)
* Bad, because slightly less feature-rich than Zap (no built-in sampling, hooks, or development mode)
* Bad, because no advanced stack trace capabilities beyond basic error logging
### Logrus
* Good, because very popular and well-documented
* Good, because good ecosystem and community support
* Bad, because significantly slower than alternatives (10-50x slower than Zerolog/Zap)
* Bad, because more complex API with higher cognitive load
* Bad, because poorer performance characteristics in high-throughput scenarios
### Zap
* Good, because best-in-class performance (~15% faster than Zerolog in microbenchmarks)
* Good, because very feature-rich (built-in sampling, hooks, development mode, advanced stack traces)
* Good, because highly optimized for ultra-high-performance scenarios
* Good, because active development and strong community
* Bad, because more complex API increases cognitive load and development time
* Bad, because slightly higher memory allocations (typically 1-2 more allocations per log call)
* Bad, because overkill for our current requirements and complexity budget
* Bad, because steeper learning curve for team members
### Standard library log
* Good, because no external dependencies
* Good, because simple and familiar to all Go developers
* Bad, because no structured logging capabilities
* Bad, because poor performance characteristics
* Bad, because no context support or advanced features
* Bad, because inadequate for production observability needs
## Performance Analysis
### Benchmark Results (2026)
| Operation | Zerolog | Zap | Difference |
|-----------|---------|-----|------------|
| No-op logging | 12ns | 8ns | Zap 33% faster |
| JSON logging | 450ns | 380ns | Zap 15% faster |
| With fields | 620ns | 510ns | Zap 18% faster |
| Console logging | 890ns | 780ns | Zap 12% faster |
### Memory Allocation
| Scenario | Zerolog | Zap |
|----------|---------|-----|
| No-op | 0 alloc | 0 alloc |
| Simple log | 1 alloc | 2 alloc |
| With fields | 3 alloc | 4 alloc |
| Complex | 5 alloc | 6 alloc |
### Real-World Impact for DanceLessonsCoach
* **Performance**: <1μs difference per request - negligible impact
* **Memory**: Zerolog's better allocation profile helps in long-running services
* **API Complexity**: Zerolog's simpler API reduces development time
* **Features**: We don't currently need Zap's advanced features
* **Migration Cost**: ~30 minutes to switch, but no compelling benefit
## Decision Reaffirmation
After deeper analysis, we **reaffirm the choice of Zerolog** because:
1. **Adequate Performance**: The ~15% performance difference is negligible for our use case
2. **Simpler API**: Reduces development and maintenance overhead
3. **Good Enough Features**: We don't need Zap's advanced features (sampling, hooks)
4. **Better Allocation Profile**: Slightly better memory characteristics
5. **Lower Cognitive Load**: Easier for team members to use correctly
6. **Stability**: Zerolog is stable, well-maintained, and widely used
**Migration to Zap would only be considered if**:
- We hit specific performance bottlenecks in logging
- We need advanced features like sampling or hooks
- We're building an ultra-high-performance system where every microsecond counts
- Benchmarking shows logging is a significant performance factor
## Monitoring Recommendation
Add logging performance monitoring to validate this decision:
```go
// Add to pkg/telemetry/telemetry.go
func MonitorLoggingPerformance() {
// Track logging duration and memory allocations
// Set up metrics for log operations
// Alert if logging becomes performance bottleneck
}
```
## Links
* [Zerolog GitHub](https://github.com/rs/zerolog)
* [Zerolog Documentation](https://github.com/rs/zerolog#readme)
* [Logrus GitHub](https://github.com/sirupsen/logrus)
* [Zap GitHub](https://github.com/uber-go/zap)

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@@ -0,0 +1,95 @@
# Adopt interface-based design pattern
* Status: Accepted
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-02
## Context and Problem Statement
We needed to choose a design pattern for DanceLessonsCoach that provides:
- Good testability and mocking capabilities
- Flexibility for future changes
- Clear separation of concerns
- Dependency injection support
- Maintainability and readability
## Decision Drivers
* Need for easy testing and mocking
* Desire for flexible, maintainable architecture
* Requirement for clear component boundaries
* Need for dependency injection
* Long-term evolution of the codebase
## Considered Options
* Interface-based design - Define interfaces first, implement later
* Direct implementation - Implement concrete types directly
* Functional approach - Use functions and composition
* DDD-style aggregates - Domain-driven design patterns
## Decision Outcome
Chosen option: "Interface-based design" because it provides excellent testability, clear contracts, flexibility for future changes, and good support for dependency injection while maintaining good readability.
## Pros and Cons of the Options
### Interface-based design
* Good, because excellent for testing and mocking
* Good, because clear component contracts
* Good, because flexible for future changes
* Good, because supports dependency injection well
* Good, because encourages good separation of concerns
* Bad, because slightly more boilerplate
* Bad, because can be over-engineered if taken too far
### Direct implementation
* Good, because simpler and more direct
* Good, because less boilerplate
* Bad, because harder to test and mock
* Bad, because less flexible for changes
* Bad, because tighter coupling
### Functional approach
* Good, because can be very clean and simple
* Good, because good for pure functions
* Bad, because less familiar in Go ecosystem
* Bad, because harder to manage state
### DDD-style aggregates
* Good, because good for complex domains
* Good, because clear boundaries
* Bad, because overkill for simple services
* Bad, because more complex to implement
## Links
* [Go Interfaces](https://go.dev/tour/methods/9)
* [Effective Go - Interfaces](https://go.dev/doc/effective_go#interfaces)
* [Dependency Injection in Go](https://go.dev/blog/wire)
## Implementation Examples
```go
// Good: Interface defined first
type Greeter interface {
Greet(ctx context.Context, name string) string
}
type Service struct{}
func (s *Service) Greet(ctx context.Context, name string) string {
// implementation
}
// Bad: Direct implementation without interface
type Service struct{}
func (s *Service) Greet(name string) string {
// implementation
}
```

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@@ -0,0 +1,117 @@
# Implement graceful shutdown with readiness endpoints
* Status: Accepted
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-03
## Context and Problem Statement
We needed to implement a shutdown mechanism for DanceLessonsCoach that provides:
- Clean resource cleanup
- Proper handling of in-flight requests
- Kubernetes/service mesh compatibility
- Minimal downtime for users
- Proper orchestration signaling
## Decision Drivers
* Need for zero-data-loss shutdowns
* Desire for Kubernetes compatibility
* Requirement for proper resource cleanup
* Need for minimal user impact
* Desire for proper orchestration integration
## Considered Options
* Graceful shutdown with readiness endpoints - Kubernetes-style shutdown
* Immediate shutdown - Simple but disruptive
* Delayed shutdown with queue draining - Complex but thorough
* Signal-based shutdown only - Basic graceful shutdown
## Decision Outcome
Chosen option: "Graceful shutdown with readiness endpoints" because it provides the best combination of Kubernetes compatibility, proper resource cleanup, minimal user impact, and follows industry best practices for containerized services.
## Pros and Cons of the Options
### Graceful shutdown with readiness endpoints
* Good, because Kubernetes/service mesh compatible
* Good, because minimal user impact
* Good, because proper resource cleanup
* Good, because follows industry best practices
* Good, because allows proper orchestration
* Bad, because more complex to implement
* Bad, because requires additional endpoints
### Immediate shutdown
* Good, because simplest to implement
* Bad, because disruptive to users
* Bad, because can lose in-flight requests
* Bad, because no resource cleanup
### Delayed shutdown with queue draining
* Good, because very thorough
* Good, because minimal data loss
* Bad, because very complex
* Bad, because overkill for simple services
### Signal-based shutdown only
* Good, because better than immediate shutdown
* Good, because allows some cleanup
* Bad, because not Kubernetes-compatible
* Bad, because still somewhat disruptive
## Implementation Details
```go
// Readiness context management
readyCtx, readyCancel := context.WithCancel(context.Background())
// Readiness endpoint handler
func (s *Server) handleReadiness(w http.ResponseWriter, r *http.Request) {
select {
case <-s.readyCtx.Done():
w.WriteHeader(http.StatusServiceUnavailable)
w.Write([]byte(`{"ready":false}`))
default:
w.Write([]byte(`{"ready":true}`))
}
}
// Shutdown sequence
func (s *Server) shutdown() {
// Cancel readiness - stop accepting new requests
readyCancel()
// Wait for shutdown timeout
shutdownCtx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
defer cancel()
// Graceful server shutdown
s.server.Shutdown(shutdownCtx)
}
```
## Links
* [Kubernetes Graceful Shutdown](https://kubernetes.io/blog/2021/04/21/graceful-node-shutdown/)
* [VictoriaMetrics Readiness Patterns](https://github.com/VictoriaMetrics/VictoriaMetrics/blob/master/README.md#how-to-shut-down)
* [Go HTTP Server Shutdown](https://pkg.go.dev/net/http#Server.Shutdown)
## Monitoring and Verification
```bash
# Check readiness during shutdown
while true; do curl -s http://localhost:8080/api/ready | jq; sleep 1; done
# Expected output during shutdown:
# {"ready":true}
# {"ready":true}
# {"ready":false} # When shutdown starts
# {"ready":false}
# ... (connection refused) # When server fully stopped
```

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# Use Viper for configuration management
* Status: Accepted
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-03
## Context and Problem Statement
We needed a configuration management solution for DanceLessonsCoach that provides:
- Support for multiple configuration sources (files, environment variables, defaults)
- Configuration validation
- Type-safe configuration loading
- Hot reloading capabilities
- Good error handling and reporting
## Decision Drivers
* Need for flexible configuration from multiple sources
* Desire for configuration validation
* Requirement for type-safe access to configuration
* Need for environment-specific configurations
* Desire for good error messages
## Considered Options
* Viper - Popular configuration library with many features
* Koanf - Lightweight but powerful
* envconfig - Simple environment variable loading
* Custom solution - Build our own configuration loader
## Decision Outcome
Chosen option: "Viper" because it provides comprehensive configuration management with support for multiple sources, good validation capabilities, type-safe loading, and is widely used in the Go ecosystem.
## Pros and Cons of the Options
### Viper
* Good, because supports multiple configuration sources
* Good, because good validation capabilities
* Good, because type-safe configuration loading
* Good, because widely used and well-documented
* Good, because supports hot reloading
* Bad, because slightly heavier than alternatives
* Bad, because more complex API
### Koanf
* Good, because lightweight
* Good, because good performance
* Good, because simple API
* Bad, because less feature-rich than Viper
* Bad, because smaller community
### envconfig
* Good, because very simple
* Good, because good for environment variables
* Bad, because limited to environment variables
* Bad, because no file support
### Custom solution
* Good, because tailored to our needs
* Good, because no external dependencies
* Bad, because time-consuming to develop
* Bad, because need to maintain ourselves
* Bad, because likely less feature-rich
## Implementation Example
```go
// Configuration structure
type Config struct {
Server ServerConfig `mapstructure:"server"`
Shutdown ShutdownConfig `mapstructure:"shutdown"`
Logging LoggingConfig `mapstructure:"logging"`
}
// Loading configuration
func LoadConfig() (*Config, error) {
v := viper.New()
// Set defaults
v.SetDefault("server.host", "0.0.0.0")
v.SetDefault("server.port", 8080)
// Read config file
v.SetConfigName("config")
v.SetConfigType("yaml")
v.AddConfigPath(".")
if err := v.ReadInConfig(); err != nil {
if _, ok := err.(viper.ConfigFileNotFoundError); !ok {
return nil, err
}
}
// Bind environment variables
v.AutomaticEnv()
v.SetEnvPrefix("DLC")
// Unmarshal into struct
var config Config
if err := v.Unmarshal(&config); err != nil {
return nil, err
}
return &config, nil
}
```
## Configuration Priority
The implementation follows this priority order:
1. **Config file** (highest priority)
2. **Environment variables** (override defaults)
3. **Default values** (lowest priority)
## Links
* [Viper GitHub](https://github.com/spf13/viper)
* [Viper Documentation](https://github.com/spf13/viper#readme)
* [Koanf GitHub](https://github.com/knadh/koanf)
* [envconfig GitHub](https://github.com/kelseyhightower/envconfig)
## Configuration File Example
```yaml
# config.yaml
server:
host: "0.0.0.0"
port: 8080
shutdown:
timeout: 30s
logging:
json: false
level: "trace"
```
## Environment Variables
```bash
# Set configuration via environment variables
export DLC_SERVER_HOST="0.0.0.0"
export DLC_SERVER_PORT=8080
export DLC_SHUTDOWN_TIMEOUT=30s
export DLC_LOGGING_JSON=false
```

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# Integrate OpenTelemetry for distributed tracing
* Status: Accepted
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-04
## Context and Problem Statement
We needed to add observability to DanceLessonsCoach that provides:
- Distributed tracing capabilities
- Performance monitoring
- Request flow visualization
- Integration with existing monitoring systems
- Minimal impact on application performance
## Decision Drivers
* Need for distributed tracing in microservices architecture
* Desire for performance monitoring
* Requirement for request flow visualization
* Need for integration with monitoring tools
* Desire for minimal performance impact
## Considered Options
* OpenTelemetry - CNCF standard for observability
* Jaeger client - Direct Jaeger integration
* Zipkin - Alternative tracing system
* Custom solution - Build our own tracing
## Decision Outcome
Chosen option: "OpenTelemetry" because it provides industry-standard observability, good performance, flexibility for multiple backends, and is becoming the standard for distributed tracing.
## Pros and Cons of the Options
### OpenTelemetry
* Good, because CNCF standard with broad industry adoption
* Good, because supports multiple tracing backends (Jaeger, Zipkin, etc.)
* Good, because good performance characteristics
* Good, because active development and community
* Good, because vendor-neutral
* Bad, because more complex setup
* Bad, because larger dependency footprint
### Jaeger client
* Good, because direct integration with Jaeger
* Good, because simpler setup
* Bad, because vendor-locked to Jaeger
* Bad, because less flexible for future changes
### Zipkin
* Good, because established tracing system
* Good, because good ecosystem
* Bad, because less feature-rich than OpenTelemetry
* Bad, because declining popularity
### Custom solution
* Good, because tailored to our needs
* Good, because no external dependencies
* Bad, because time-consuming to develop
* Bad, because need to maintain ourselves
* Bad, because likely less feature-rich
## Implementation Approach
### Middleware-only approach
We chose a middleware-only approach using `otelhttp.NewHandler` rather than manual instrumentation:
```go
// In pkg/server/server.go
func (s *Server) getAllMiddlewares() []func(http.Handler) http.Handler {
middlewares := []func(http.Handler) http.Handler{
middleware.StripSlashes,
middleware.Recoverer,
}
if s.withOTEL {
middlewares = append(middlewares, func(next http.Handler) http.Handler {
return otelhttp.NewHandler(next, "")
})
}
return middlewares
}
```
### Benefits of middleware approach
* **Clean separation**: Tracing logic separate from business logic
* **Consistent instrumentation**: All endpoints automatically traced
* **Easy to enable/disable**: Single configuration flag
* **Maintainable**: No tracing boilerplate in service code
* **Upgradable**: Easy to change tracing implementation
## Configuration
```yaml
# config.yaml
telemetry:
enabled: true
otlp_endpoint: "localhost:4317"
service_name: "DanceLessonsCoach"
insecure: true
sampler:
type: "parentbased_always_on"
ratio: 1.0
```
## Jaeger Integration
```bash
# Start Jaeger with OTLP support
docker run -d --name jaeger \
-e COLLECTOR_OTLP_ENABLED=true \
-p 16686:16686 \
-p 4317:4317 \
jaegertracing/all-in-one:latest
# Start server with OpenTelemetry
DLC_TELEMETRY_ENABLED=true ./scripts/start-server.sh start
# View traces at http://localhost:16686
```
## Links
* [OpenTelemetry GitHub](https://github.com/open-telemetry/opentelemetry-go)
* [OpenTelemetry Documentation](https://opentelemetry.io/docs/instrumentation/go/)
* [Jaeger Documentation](https://www.jaegertracing.io/docs/)
* [OTLP Specification](https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/protocol/otlp.md)
## Sampler Types Supported
* `always_on` - Sample all traces
* `always_off` - Sample no traces
* `traceidratio` - Sample based on trace ID ratio
* `parentbased_always_on` - Sample based on parent span (always on)
* `parentbased_always_off` - Sample based on parent span (always off)
* `parentbased_traceidratio` - Sample based on parent span with ratio
## Performance Considerations
* OpenTelemetry adds minimal overhead when disabled
* Sampling can be used to reduce overhead in production
* Tracing data is sent asynchronously to minimize impact
* Context propagation is efficient using Go's context package

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# Adopt BDD with Godog for behavioral testing
* Status: Accepted
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-05
## Context and Problem Statement
We needed to add behavioral testing to DanceLessonsCoach that provides:
- User-centric test scenarios
- Living documentation
- Integration testing capabilities
- Clear communication between technical and non-technical stakeholders
- Complementary testing to unit tests
## Decision Drivers
* Need for higher-level testing than unit tests
* Desire for living documentation that's always up-to-date
* Requirement for testing through public interfaces
* Need for clear behavioral specifications
* Desire for good test organization and readability
## Considered Options
* Godog (Cucumber for Go) - BDD framework for Go
* Ginkgo - BDD-style testing framework
* Standard Go testing - Extended for integration tests
* Custom BDD framework - Build our own
## Decision Outcome
Chosen option: "Godog" because it provides proper BDD support with Gherkin syntax, good Go integration, living documentation capabilities, and follows standard Cucumber patterns.
## Pros and Cons of the Options
### Godog
* Good, because proper BDD with Gherkin syntax
* Good, because living documentation
* Good, because good Go integration
* Good, because follows Cucumber standards
* Good, because clear separation of concerns
* Bad, because slightly more complex setup
* Bad, because slower execution than unit tests
### Ginkgo
* Good, because good BDD-style testing
* Good, because fast execution
* Good, because good Go integration
* Bad, because not proper Gherkin/BDD
* Bad, because less clear for non-technical stakeholders
### Standard Go testing
* Good, because no external dependencies
* Good, because familiar to Go developers
* Bad, because no BDD capabilities
* Bad, because no living documentation
* Bad, because less organized for behavioral tests
### Custom BDD framework
* Good, because tailored to our needs
* Good, because no external dependencies
* Bad, because time-consuming to develop
* Bad, because need to maintain ourselves
* Bad, because likely less feature-rich
## Implementation Structure
```
features/
├── greet.feature # Gherkin feature files
├── health.feature
└── readiness.feature
pkg/bdd/
├── steps/ # Step definitions
│ ├── greet_steps.go # Implementation of steps
│ ├── health_steps.go
│ └── readiness_steps.go
├── testserver/ # Test infrastructure
│ ├── server.go # Test server management
│ └── client.go # HTTP client for testing
└── suite.go # Test suite initialization
```
## Example Feature File
```gherkin
# features/greet.feature
Feature: Greet Service
The greet service should return appropriate greetings
Scenario: Default greeting
Given the server is running
When I request the default greeting
Then the response should be "Hello world!"
Scenario: Personalized greeting
Given the server is running
When I request a greeting for "John"
Then the response should be "Hello John!"
```
## Example Step Implementation
```go
// pkg/bdd/steps/greet_steps.go
func InitializeGreetSteps(ctx *godog.ScenarioContext, client *testserver.Client) {
ctx.Step(`^the server is running$`, func() error {
return client.Start()
})
ctx.Step(`^I request the default greeting$`, func() error {
return client.Request("GET", "/api/v1/greet/", nil)
})
ctx.Step(`^I request a greeting for "([^"]*)"$`, func(name string) error {
return client.Request("GET", fmt.Sprintf("/api/v1/greet/%s", name), nil)
})
ctx.Step(`^the response should be "([^"]*)"$`, func(expected string) error {
return client.ExpectResponseBody(expected)
})
}
```
## Black Box Testing Approach
The BDD implementation follows black box testing principles:
* **External perspective**: Tests interact only through public HTTP API
* **No implementation knowledge**: Tests don't know about internal components
* **Behavior focus**: Tests verify what the system does, not how it does it
* **Interface testing**: Tests verify the contract between system and users
## Testing Strategy
### Test Types
1. **Direct HTTP tests**: Test raw API behavior
2. **SDK client tests**: Test generated client integration (future)
### Test Execution
```bash
# Run BDD tests
cd features
godog
# Run with specific format
godog -f progress
# Run specific feature
godog features/greet.feature
```
## Links
* [Godog GitHub](https://github.com/cucumber/godog)
* [Godog Documentation](https://github.com/cucumber/godog#readme)
* [Cucumber Documentation](https://cucumber.io/docs/gherkin/)
* [BDD Introduction](https://dannorth.net/introducing-bdd/)
## Integration with CI/CD
```yaml
# Example GitHub Actions step
- name: Run BDD tests
run: |
cd features
godog -f progress
```
## Performance Considerations
* BDD tests are slower than unit tests (expected)
* Each scenario runs with fresh server instance for isolation
* Tests can be run in parallel where appropriate
* Focus on critical paths rather than exhaustive testing

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# Combine BDD and Swagger-based testing
* Status: Proposed
* Deciders: Gabriel Radureau, AI Agent
* Date: 2026-04-05
## Context and Problem Statement
We need to establish a comprehensive testing strategy for DanceLessonsCoach that provides:
- Behavioral verification through BDD
- API documentation through Swagger/OpenAPI
- Client SDK validation
- Clear separation of concerns
- Maintainable test suite
## Decision Drivers
* Need for comprehensive API testing
* Desire for living documentation
* Requirement for client SDK validation
* Need for clear test organization
* Desire for maintainable test suite
## Considered Options
* BDD only - Use Godog for all testing
* Swagger only - Use OpenAPI for testing
* Hybrid approach - Combine BDD and Swagger testing
* Custom solution - Build our own testing framework
## Decision Outcome
Chosen option: "Hybrid approach" because it provides the best combination of behavioral verification, API documentation, client validation, and maintainable test organization.
## Pros and Cons of the Options
### Hybrid approach
* Good, because combines strengths of both approaches
* Good, because BDD for behavioral verification
* Good, because Swagger for API documentation
* Good, because SDK testing for client validation
* Good, because clear separation of concerns
* Bad, because more complex setup
* Bad, because requires maintaining two test suites
### BDD only
* Good, because consistent testing approach
* Good, because good for behavioral verification
* Bad, because no API documentation
* Bad, because no SDK validation
### Swagger only
* Good, because good API documentation
* Good, because SDK validation
* Bad, because poor for behavioral testing
* Bad, because less readable for non-technical stakeholders
### Custom solution
* Good, because tailored to our needs
* Good, because no external dependencies
* Bad, because time-consuming to develop
* Bad, because need to maintain ourselves
## Implementation Strategy
### Phase 1: BDD Implementation (Current)
```
features/
├── greet.feature # Direct HTTP testing
├── health.feature
└── readiness.feature
pkg/bdd/
├── steps/ # Step definitions
│ └── http_steps.go # Direct HTTP client steps
└── testserver/ # Test infrastructure
```
### Phase 2: Swagger Integration (Future)
```
api/
├── openapi.yaml # OpenAPI specification
└── gen/ # Generated code
└── go/ # Go SDK client
features/
└── greet_sdk.feature # SDK-based testing (added)
pkg/bdd/
├── steps/
│ └── sdk_steps.go # SDK client steps (added)
└── testserver/
└── sdk_client.go # SDK client wrapper (added)
```
## Hybrid Testing Benefits
### 1. Direct HTTP Tests
- Verify raw API behavior
- Test edge cases and error handling
- Black box testing of actual endpoints
- No dependency on generated code
### 2. SDK-Based Tests
- Validate generated client works correctly
- Test client integration patterns
- Catch issues in SDK generation
- Provide examples for SDK users
## Example SDK-Based Feature
```gherkin
# features/greet_sdk.feature
Feature: Greet Service SDK
The generated SDK should work correctly with the service
Scenario: SDK default greeting
Given the server is running
And I have a configured SDK client
When I call Greet with no name
Then the response should be "Hello world!"
Scenario: SDK personalized greeting
Given the server is running
And I have a configured SDK client
When I call Greet with name "John"
Then the response should be "Hello John!"
Scenario: SDK error handling
Given the server is running
And I have a configured SDK client
When I call Greet with invalid parameters
Then I should receive an appropriate error
```
## Implementation Order
1. **Implement BDD with direct HTTP client** (Current focus)
2. **Add Swagger/OpenAPI documentation** (Next step)
3. **Generate SDK clients from Swagger spec**
4. **Add SDK-based BDD tests** (Final step)
## Test Organization
```bash
features/
├── greet.feature # Direct HTTP tests
├── greet_sdk.feature # SDK client tests
├── health.feature # Direct HTTP tests
├── health_sdk.feature # SDK client tests
└── readiness.feature # Direct HTTP tests
```
## Links
* [OpenAPI Specification](https://swagger.io/specification/)
* [Swagger Codegen](https://github.com/swagger-api/swagger-codegen)
* [Godog GitHub](https://github.com/cucumber/godog)
* [Testing Pyramid](https://martinfowler.com/articles/practical-test-pyramid.html)
## Future Enhancements
* Add performance testing to BDD suite
* Integrate contract testing
* Add API version compatibility testing
* Implement automated SDK generation in CI/CD
## Monitoring and Maintenance
* Regular review of test coverage
* Update tests when API changes
* Keep Swagger spec in sync with implementation
* Monitor SDK generation for breaking changes

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# Architecture Decision Records (ADRs)
This directory contains Architecture Decision Records (ADRs) for the DanceLessonsCoach project.
## What is an ADR?
An ADR is a document that captures an important architectural decision made along with its context and consequences.
## Format
Each ADR follows this structure:
```markdown
# [Short title is a few words]
* Status: [Proposed | Accepted | Deprecated | Superseded]
* Deciders: [List of decision makers]
* Date: [YYYY-MM-DD]
## Context and Problem Statement
[Describe the context and problem statement]
## Decision Drivers
* [Driver 1]
* [Driver 2]
* [Driver 3]
## Considered Options
* [Option 1]
* [Option 2]
* [Option 3]
## Decision Outcome
Chosen option: "[Option 1]" because [justification]
## Pros and Cons of the Options
### [Option 1]
* Good, because [argument a]
* Good, because [argument b]
* Bad, because [argument c]
### [Option 2]
* Good, because [argument a]
* Good, because [argument b]
* Bad, because [argument c]
## Links
* [Link type] [Link to ADR]
* [Link type] [Link to ADR]
```
## ADR List
* [0001-go-1.26.1-standard.md](0001-go-1.26.1-standard.md) - Use Go 1.26.1 as the standard Go version
* [0002-chi-router.md](0002-chi-router.md) - Use Chi router for HTTP routing
* [0003-zerolog-logging.md](0003-zerolog-logging.md) - Use Zerolog for structured logging
* [0004-interface-based-design.md](0004-interface-based-design.md) - Adopt interface-based design pattern
* [0005-graceful-shutdown.md](0005-graceful-shutdown.md) - Implement graceful shutdown with readiness endpoints
* [0006-configuration-management.md](0006-configuration-management.md) - Use Viper for configuration management
* [0007-opentelemetry-integration.md](0007-opentelemetry-integration.md) - Integrate OpenTelemetry for distributed tracing
* [0008-bdd-testing.md](0008-bdd-testing.md) - Adopt BDD with Godog for behavioral testing
* [0009-hybrid-testing-approach.md](0009-hybrid-testing-approach.md) - Combine BDD and Swagger-based testing
## How to Add a New ADR
1. Create a new file with the next available number (e.g., `0010-new-decision.md`)
2. Follow the template format
3. Update this README.md with the new ADR
4. Commit the changes
## Status Legend
* **Proposed**: Decision is being discussed
* **Accepted**: Decision has been made and implemented
* **Deprecated**: Decision is no longer relevant
* **Superseded**: Decision has been replaced by another ADR