Files
kalzu-value-store/CLAUDE.md
ryyst 64680a6ece docs: document daemon process management commands
Update README.md and CLAUDE.md to document new process management:
- Add "Process Management" section with daemon commands
- Update all examples to use `./kvs start/stop/status` instead of `&` and `pkill`
- Document global PID/log directories (~/.kvs/)
- Update cluster setup examples
- Update development workflow
- Add daemon package to project structure

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-05 23:10:25 +03:00

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# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Commands for Development
### Build and Test Commands
```bash
# Build the binary
go build -o kvs .
# Run with default config (auto-generates config.yaml)
./kvs start config.yaml
# Run with custom config
./kvs start /path/to/config.yaml
# Check running instances
./kvs status
# Stop instance
./kvs stop config
# Run comprehensive integration tests
./integration_test.sh
# Create test conflict data for debugging
go run test_conflict.go data1 data2
# Build and test in one go
go build -o kvs . && ./integration_test.sh
```
### Process Management Commands
```bash
# Start as background daemon
./kvs start <config.yaml> # .yaml extension optional
# Stop daemon
./kvs stop <config> # Graceful SIGTERM shutdown
# Restart daemon
./kvs restart <config> # Stop then start
# Show status
./kvs status # All instances
./kvs status <config> # Specific instance
# Run in foreground (for debugging)
./kvs <config.yaml> # Logs to stdout, blocks terminal
# View daemon logs
tail -f ~/.kvs/logs/kvs_<config>.yaml.log
# Global state directories
~/.kvs/pids/ # PID files (works from any directory)
~/.kvs/logs/ # Daemon log files
```
### Development Workflow
```bash
# Format and check code
go fmt ./...
go vet ./...
# Run dependencies management
go mod tidy
# Check build without artifacts
go build .
# Test specific cluster scenarios
./kvs start node1.yaml
./kvs start node2.yaml
# Wait for cluster formation
sleep 5
# Test data operations
curl -X PUT http://localhost:8081/kv/test/data -H "Content-Type: application/json" -d '{"test":"data"}'
curl http://localhost:8082/kv/test/data # Should replicate within ~30 seconds
# Check daemon status
./kvs status
# View logs
tail -f ~/.kvs/logs/kvs_node1.yaml.log
# Cleanup
./kvs stop node1
./kvs stop node2
```
## Architecture Overview
### High-Level Structure
KVS is a **distributed, eventually consistent key-value store** built around three core systems:
1. **Gossip Protocol** (`cluster/gossip.go`) - Decentralized membership management and failure detection
2. **Merkle Tree Sync** (`cluster/sync.go`, `cluster/merkle.go`) - Efficient data synchronization and conflict resolution
3. **Modular Server** (`server/`) - HTTP API with pluggable feature modules
### Key Architectural Patterns
#### Modular Package Design
- **`auth/`** - Complete JWT authentication system with POSIX-inspired permissions
- **`cluster/`** - Distributed systems logic (gossip, sync, merkle trees)
- **`daemon/`** - Process management (daemonization, PID files, lifecycle)
- **`storage/`** - BadgerDB abstraction with compression and revision history
- **`server/`** - HTTP handlers, routing, and lifecycle management
- **`features/`** - Utility functions for TTL, rate limiting, tamper logging, backup
- **`types/`** - Centralized type definitions for all components
- **`config/`** - Configuration loading with auto-generation
- **`utils/`** - Cryptographic hashing utilities
#### Core Data Model
```go
// Primary storage format
type StoredValue struct {
UUID string `json:"uuid"` // Unique version identifier
Timestamp int64 `json:"timestamp"` // Unix timestamp (milliseconds)
Data json.RawMessage `json:"data"` // Actual user JSON payload
}
```
#### Critical System Interactions
**Conflict Resolution Flow:**
1. Merkle trees detect divergent data between nodes (`cluster/merkle.go`)
2. Sync service fetches conflicting keys (`cluster/sync.go:fetchAndCompareData`)
3. Sophisticated conflict resolution logic in `resolveConflict()`:
- Same timestamp → Apply "oldest-node rule" (earliest `joined_timestamp` wins)
- Tie-breaker → UUID comparison for deterministic results
- Winner's data automatically replicated to losing nodes
**Authentication & Authorization:**
- JWT tokens with scoped permissions (`auth/jwt.go`)
- POSIX-inspired 12-bit permission system (`types/types.go:52-75`)
- Resource ownership metadata with TTL support (`types/ResourceMetadata`)
**Storage Strategy:**
- **Main keys**: Direct path mapping (`users/john/profile`)
- **Index keys**: `_ts:{timestamp}:{path}` for time-based queries
- **Compression**: Optional ZSTD compression (`storage/compression.go`)
- **Revisions**: Optional revision history (`storage/revision.go`)
### Configuration Architecture
The system uses feature toggles extensively (`types/Config:271-280`):
```yaml
auth_enabled: true # JWT authentication system
tamper_logging_enabled: true # Cryptographic audit trail
clustering_enabled: true # Gossip protocol and sync
rate_limiting_enabled: true # Per-client rate limiting
revision_history_enabled: true # Automatic versioning
# Anonymous access control (Issue #5 - when auth_enabled: true)
allow_anonymous_read: false # Allow unauthenticated read access to KV endpoints
allow_anonymous_write: false # Allow unauthenticated write access to KV endpoints
```
**Security Note**: DELETE operations always require authentication when `auth_enabled: true`, regardless of anonymous access settings.
### Testing Strategy
#### Integration Test Suite (`integration_test.sh`)
- **Build verification** - Ensures binary compiles correctly
- **Basic functionality** - Single-node CRUD operations
- **Cluster formation** - 2-node gossip protocol and data replication
- **Conflict resolution** - Automated conflict detection and resolution using `test_conflict.go`
- **Authentication middleware** - Comprehensive security testing (Issue #4):
- Admin endpoints properly reject unauthenticated requests
- Admin endpoints work with valid JWT tokens
- KV endpoints respect anonymous access configuration
- Automatic root account creation and token extraction
The test suite uses sophisticated retry logic and timing to handle the eventually consistent nature of the system.
#### Conflict Testing Utility (`test_conflict.go`)
Creates two BadgerDB instances with intentionally conflicting data (same path, same timestamp, different UUIDs) to test the conflict resolution algorithm.
### Development Notes
#### Key Constraints
- **Eventually Consistent**: All operations succeed locally first, then replicate
- **Local-First Truth**: Nodes operate independently and sync in background
- **No Transactions**: Each key operation is atomic and independent
- **Hierarchical Keys**: Support for path-like structures (`/home/room/closet/socks`)
#### Critical Timing Considerations
- **Gossip intervals**: 1-2 minutes for membership updates
- **Sync intervals**: 5 minutes for regular data sync, 2 minutes for catch-up
- **Conflict resolution**: Typically resolves within 10-30 seconds after detection
- **Bootstrap sync**: Up to 30 days of historical data for new nodes
#### Main Entry Point Flow
1. `main.go` parses command-line arguments for subcommands (`start`, `stop`, `status`, `restart`)
2. For daemon mode: `daemon.Daemonize()` spawns background process and manages PID files
3. For server mode: loads config (auto-generates default if missing)
4. `server.NewServer()` initializes all subsystems
5. Graceful shutdown handling with `SIGINT`/`SIGTERM`
6. All business logic delegated to modular packages
#### Daemon Architecture
- **PID Management**: Global PID files stored in `~/.kvs/pids/` for cross-directory access
- **Logging**: Daemon logs written to `~/.kvs/logs/{config-name}.log`
- **Process Lifecycle**: Spawns detached process via `exec.Command()` with `Setsid: true`
- **Config Normalization**: Supports both `node1` and `node1.yaml` formats
- **Stale PID Detection**: Checks process existence via `Signal(0)` before operations
This architecture enables easy feature addition, comprehensive testing, and reliable operation in distributed environments while maintaining simplicity for single-node deployments.