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attune/work-summary/phases/PHASE-5-COMPLETE.md
2026-02-04 17:46:30 -06:00

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Phase 5 Worker Service - COMPLETE

Completion Date: 2026-01-14
Status: All Core Components Implemented, Compiled, and Tested
Build Status: 0 errors, 0 warnings
Test Status: 17/17 unit tests passing


Executive Summary

Phase 5 (Worker Service) core implementation is COMPLETE. The worker service can now:

  • Register itself in the database with automatic heartbeat
  • Execute Python and Shell actions via subprocess
  • Manage execution lifecycle from request to completion
  • Store execution artifacts (logs, results)
  • Communicate with the Executor service via RabbitMQ
  • Handle graceful shutdown

Lines of Code: ~2,500 lines of production Rust code
Test Coverage: 17 unit tests covering all core functionality
Documentation: Comprehensive architecture documentation in docs/worker-service.md


Completed Components (Phase 5.1-5.4, 5.6)

5.1 Worker Foundation

  • Worker Registration (registration.rs): Database registration with capabilities
  • Heartbeat Manager (heartbeat.rs): Periodic status updates every 30s
  • Service Orchestration (service.rs): Main service lifecycle management
  • Main Entry Point (main.rs): CLI with config and name overrides
  • Library Interface (lib.rs): Public API for testing

5.2 Runtime System

  • Runtime Trait (runtime/mod.rs): Async abstraction for action execution
  • Python Runtime (runtime/python.rs):
    • Execute Python code via subprocess
    • Parameter injection through wrapper script
    • Timeout support, stdout/stderr capture
    • JSON result parsing
  • Shell Runtime (runtime/shell.rs):
    • Execute bash scripts via subprocess
    • Parameters as environment variables (PARAM_*)
    • Timeout support, output capture
  • Local Runtime (runtime/local.rs): Facade delegating to Python/Shell
  • Runtime Registry: Dynamic runtime selection and lifecycle management

5.3 Execution Logic

  • Action Executor (executor.rs):
    • Load execution and action from database
    • Prepare execution context (parameters, env vars)
    • Execute via runtime registry
    • Handle success/failure cases
    • Update execution status in database
    • Publish status messages to MQ

5.4 Artifact Management

  • Artifact Manager (artifacts.rs):
    • Store stdout/stderr logs per execution
    • Store JSON results
    • Support custom file artifacts
    • Retention policy with cleanup
    • Per-execution directory structure: /tmp/attune/artifacts/{worker}/execution_{id}/

5.6 Worker Health

  • Automatic worker registration on startup
  • Periodic heartbeat updates (configurable interval)
  • Graceful shutdown with worker deregistration
  • Worker capability reporting

Deferred Components

📋 5.5 Secret Management (TODO)

  • Fetch secrets from Key table
  • Decrypt encrypted secrets
  • Inject into execution environment
  • Clean up after execution

📋 5.7 Testing (Partial - Unit Tests Complete)

  • Unit tests for all runtimes (17 tests passing)
  • Integration tests pending (3 tests marked #[ignore], need DB)
  • End-to-end execution tests
  • Message queue integration tests

📋 Advanced Features (Future)

  • Container runtime (Docker)
  • Remote worker support
  • Concurrent execution limits
  • Worker capacity management

Technical Implementation

Architecture Pattern

  • Trait-based runtime system for extensibility
  • Repository pattern for database access
  • Message queue for service communication
  • Graceful shutdown via tokio signals

Key Design Decisions

  1. Direct SQL in registration: Simpler than repository pattern for CRUD
  2. Runtime trait with lifecycle methods: setup(), execute(), cleanup()
  3. Facade pattern for LocalRuntime: Unified interface for multiple runtimes
  4. Worker-specific queues: worker.{worker_id}.executions for direct routing
  5. Local filesystem for artifacts: Cloud storage deferred to future

Data Flow

1. Executor publishes: execution.scheduled → worker.{id}.executions
2. Worker consumes message
3. Load execution and action from database
4. Prepare context (params from config.parameters)
5. Execute in Python/Shell runtime
6. Publish: ExecutionStatusChanged (running)
7. Capture stdout/stderr/result
8. Store artifacts
9. Update execution status (Completed/Failed)
10. Publish: ExecutionStatusChanged (completed/failed)

Configuration

Worker Configuration

worker:
  name: worker-01              # Optional, defaults to hostname
  worker_type: Local           # Local, Remote, Container
  runtime_id: null             # Optional runtime association
  host: null                   # Optional, defaults to hostname
  port: null                   # Optional
  max_concurrent_tasks: 10     # Max parallel executions
  heartbeat_interval: 30       # Seconds between heartbeats
  task_timeout: 300            # Default task timeout (5 min)

Environment Overrides

ATTUNE__WORKER__NAME=my-worker
ATTUNE__WORKER__MAX_CONCURRENT_TASKS=20
ATTUNE__WORKER__HEARTBEAT_INTERVAL=60

Testing Results

Unit Tests (17/17 Passing)

Runtime Tests:
  ✅ Python simple execution
  ✅ Python timeout handling
  ✅ Python error handling
  ✅ Shell simple execution
  ✅ Shell parameter passing
  ✅ Shell timeout handling
  ✅ Shell error handling
  ✅ Local runtime Python delegation
  ✅ Local runtime Shell delegation
  ✅ Local runtime unknown rejection

Artifact Tests:
  ✅ Store logs (stdout/stderr)
  ✅ Store JSON results
  ✅ Delete execution artifacts

Executor Tests:
  ✅ Parse action reference
  ✅ Invalid action reference

Service Tests:
  ✅ Queue name format
  ✅ Status string conversion

Integration Tests (3 ignored, require DB):
  ⏳ Worker registration
  ⏳ Worker capabilities
  ⏳ Heartbeat manager

Build Status

cargo check --workspace: ✅ Success
cargo build -p attune-worker: ✅ Success
cargo test -p attune-worker --lib: ✅ 17/17 passing

Files Created/Modified

New Files (11)

  1. crates/worker/src/lib.rs - Library interface
  2. crates/worker/src/registration.rs - Worker registration
  3. crates/worker/src/heartbeat.rs - Heartbeat manager
  4. crates/worker/src/runtime/mod.rs - Runtime trait & registry
  5. crates/worker/src/runtime/python.rs - Python runtime
  6. crates/worker/src/runtime/shell.rs - Shell runtime
  7. crates/worker/src/runtime/local.rs - Local runtime facade
  8. crates/worker/src/artifacts.rs - Artifact management
  9. crates/worker/src/executor.rs - Action executor
  10. crates/worker/src/service.rs - Service orchestration
  11. docs/worker-service.md - Architecture documentation

Modified Files (3)

  1. crates/worker/src/main.rs - Complete rewrite with CLI
  2. crates/worker/Cargo.toml - Added dependencies
  3. crates/common/src/config.rs - Updated WorkerConfig
  4. crates/common/src/error.rs - Added From

Dependencies Added

Production

  • hostname = "0.4" - Worker name defaults
  • async-trait = "0.1" - Runtime trait
  • thiserror (workspace) - RuntimeError

Development

  • tempfile = "3.8" - Artifact testing

Known Limitations

  1. No Secret Management: Secrets not yet injected into executions
  2. No Concurrent Limits: max_concurrent_tasks not yet enforced
  3. No Action Code Loading: Actions must provide code inline (no pack storage yet)
  4. Local Filesystem Only: Artifacts stored locally, no cloud storage
  5. No Container Runtime: Docker execution not yet implemented
  6. No Remote Workers: Single-node only

Next Steps

Immediate (Next Session)

  1. Integration Testing:

    • Run ignored tests with real PostgreSQL
    • Test with real RabbitMQ
    • End-to-end execution flow
    • Create test pack with sample actions
  2. Secret Management (Phase 5.5):

    • Implement secret fetching from database
    • Add encryption/decryption support
    • Inject secrets as env vars
    • Clean up after execution

Future Enhancements

  1. Concurrent Execution Control:

    • Track active executions
    • Enforce max_concurrent_tasks
    • Queue executions when at capacity
  2. Action Code Loading:

    • Load action code from pack storage
    • Support code_path for file-based actions
    • Cache frequently used actions
  3. Container Runtime:

    • Docker integration
    • Container image management
    • Volume mounting for code injection
  4. Remote Workers:

    • Worker-to-worker communication
    • Load balancing across workers
    • Geographic distribution

How to Use

Start Worker Service

# Default configuration
cargo run -p attune-worker

# Custom config file
cargo run -p attune-worker -- --config /path/to/config.yaml

# Override worker name
cargo run -p attune-worker -- --name worker-prod-01

# With environment variables
ATTUNE__WORKER__NAME=worker-01 \
ATTUNE__WORKER__HEARTBEAT_INTERVAL=60 \
cargo run -p attune-worker

Example Python Action

def run(x, y):
    """Add two numbers"""
    return x + y

Example Shell Action

#!/bin/bash
echo "Hello, $PARAM_NAME!"

Documentation

  • Architecture: docs/worker-service.md
  • Work Summary: work-summary/2026-01-14-worker-service-implementation.md
  • API Documentation: docs/api-executions.md
  • Configuration: docs/configuration.md

Success Metrics

Compilation: 0 errors, 0 warnings
Tests: 17/17 unit tests passing
Code Quality: Clean architecture, proper error handling
Documentation: Comprehensive architecture doc
Extensibility: Trait-based runtime system
Production Ready: Core functionality complete


Team Notes

The Worker Service foundation is production-ready for core functionality. All compilation errors have been resolved, tests are passing, and the architecture is solid. The service can execute Python and Shell actions, manage artifacts, and communicate with the Executor service.

Recommended: Proceed with integration testing using real database and message queue, then implement secret management (Phase 5.5) before production deployment.

The implementation demonstrates:

  • Strong type safety with Rust's type system
  • Async/await throughout for performance
  • Proper error handling and recovery
  • Extensible design for future enhancements
  • Clean separation of concerns

Phase 5 Status: COMPLETE (5.1-5.4, 5.6), PARTIAL (5.7), 📋 TODO (5.5)