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SkyDeck Dashboard - Implementation Summary

Overview

Complete web-based dashboard for managing SkyPilot experiments with declarative desired state management, automatic reconciliation, and persistent job history tracking.

Status: ✅ Fully Implemented (Phase 1-3 Complete)

Project Structure

packages/skydeck/
├── skydeck/                   # Main package
│   ├── __init__.py            # Package initialization
│   ├── __main__.py            # Entry point for python -m skydeck
│   ├── models.py              # ✅ Pydantic data models
│   ├── database.py            # ✅ SQLite async database layer
│   ├── flag_schema.py         # ✅ Dynamic flag inference system
│   ├── state_manager.py       # ✅ SkyPilot state cache
│   ├── desired_state.py       # ✅ Experiment CRUD operations
│   ├── poller.py              # ✅ Background SkyPilot poller
│   ├── reconciler.py          # ✅ Reconciliation engine
│   ├── app.py                 # ✅ FastAPI REST API
│   ├── run.py                 # ✅ CLI entry point
│   └── static/                # Web UI
│       ├── index.html         # ✅ Dashboard HTML
│       ├── styles.css         # ✅ Styling
│       └── app.js             # ✅ Frontend logic
├── tests/                     # Test suite
│   ├── test_models.py         # ✅ Model tests
│   └── test_database.py       # ✅ Database tests
├── examples/                  # Usage examples
│   ├── simple_experiment.py   # ✅ Basic example
│   └── grid_search.py         # ✅ Grid search example
├── pyproject.toml             # ✅ Package configuration
├── README.md                  # ✅ Full documentation
├── QUICKSTART.md              # ✅ Quick start guide
└── .gitignore                 # ✅ Git ignore rules

Implementation Details

Core Components (All Implemented ✅)

  1. Data Models (models.py)

    • Job: Single execution with full lifecycle tracking
    • Experiment: Configuration template with flags
    • Cluster: SkyPilot cluster information
    • JobStatus: Enum for job states
    • DesiredState: Enum for desired states
    • Request/Response models for API

  2. Database Layer (database.py)

    • 4 tables: experiments, jobs, clusters, flag_schemas
    • Full async operations with aiosqlite
    • Foreign key constraints with cascade delete
    • Efficient indexing
    • Row-to-model conversion helpers

  3. Flag Schema System (flag_schema.py)

    • Dynamic flag inference from Pydantic models
    • Type detection (STRING, INTEGER, FLOAT, BOOLEAN, CHOICE)
    • Recursive extraction for nested models
    • Database storage for typeahead autocomplete

  4. State Manager (state_manager.py)

    • Caches current SkyPilot state
    • Updates from sky.status() and sky.queue()
    • Maintains read-only view of infrastructure
    • Syncs job status to database

  5. Desired State Manager (desired_state.py)

    • CRUD operations for experiments
    • Manages desired state (what user wants)
    • Identifies experiments needing reconciliation
    • Enforces business rules

  6. Background Poller (poller.py)

    • Polls SkyPilot every 30s (configurable)
    • Async task with graceful start/stop
    • Calls sky.status() for clusters
    • Calls sky.queue() for each cluster's jobs
    • Updates StateManager cache

  7. Reconciliation Engine (reconciler.py)

    • Runs every 60s (configurable)
    • Compares desired vs current state
    • Takes actions:
      • LAUNCH: sky.launch() for new jobs
      • START: sky.start() for stopped clusters
      • STOP: sky.stop() and sky.cancel()
      • TERMINATE: sky.down() for cleanup
    • Creates Job records
    • Updates experiment state

  8. FastAPI Backend (app.py)

    • Lifespan context manager for startup/shutdown
    • REST API endpoints:
      • Experiments: CRUD, state management, job history
      • Jobs: Cancel operations
      • Clusters: List and status
      • Flag schemas: Typeahead metadata
      • System: Health, refresh, reconcile
    • Static file serving
    • Proper error handling

  9. Web UI (static/)

    • Single-page dashboard
    • Real-time updates (5s polling)
    • Experiment management:
      • Create with full configuration
      • Start/Stop/Terminate controls
      • Edit flags with JSON editor
      • View job history
    • Cluster status display
    • Color-coded status badges
    • Responsive design

  10. CLI Entry Point (run.py)

    • Argparse configuration
    • Environment variable support
    • Uvicorn server management
    • Logging setup

Key Features Implemented

✅ Declarative State Management

  • User sets desired_state (RUNNING/STOPPED/TERMINATED)
  • System automatically reconciles to match
  • No manual SkyPilot commands needed

✅ Job History Tracking

  • Complete execution history per experiment
  • Timestamps: created, submitted, started, ended
  • Exit codes and error messages
  • Never lose experiment outcomes

✅ Dynamic Flag Configuration

  • Flags stored as flexible dict
  • Type-safe with schema inference
  • JSON editor with validation
  • Typeahead autocomplete ready

✅ Automatic Reconciliation

  • Background loop ensures consistency
  • Handles crashes and restarts
  • One running job per experiment enforced
  • Cluster lifecycle management

✅ SQLite Persistence

  • All state survives restarts
  • Single file database
  • Async operations
  • Foreign key constraints

✅ Real-time Updates

  • Web UI polls every 5 seconds
  • Background tasks update state
  • Manual refresh available
  • Force reconciliation on demand

API Endpoints (All Implemented ✅)

Experiments

  • GET /api/experiments - List all
  • POST /api/experiments - Create new
  • GET /api/experiments/{id} - Get details
  • DELETE /api/experiments/{id} - Delete
  • POST /api/experiments/{id}/state - Update desired state
  • GET /api/experiments/{id}/status - Full status
  • GET /api/experiments/{id}/jobs - Job history
  • POST /api/experiments/{id}/flags - Update flags

Jobs

  • POST /api/jobs/{id}/cancel - Cancel job

Clusters

  • GET /api/clusters - List all

System

  • GET /api/health - Health status
  • GET /api/flag-schemas - Flag metadata
  • POST /api/refresh - Force poll
  • POST /api/reconcile - Force reconciliation

Testing

Unit Tests (Implemented ✅)

  • test_models.py: Command building, state detection
  • test_database.py: CRUD operations, persistence

Test Coverage

  • Data model validation
  • Command building logic
  • Reconciliation detection
  • Database operations
  • State transitions

Run tests with:

uv run pytest tests/ -v

Examples (All Implemented ✅)

Simple Experiment

uv run python examples/simple_experiment.py

Creates a single test experiment.

Grid Search

uv run python examples/grid_search.py

Creates a 2×4 grid over nodes × layers (8 experiments total).

Documentation (All Implemented ✅)

  1. README.md: Complete architecture and design documentation
  2. QUICKSTART.md: Step-by-step getting started guide
  3. IMPLEMENTATION_SUMMARY.md: This file
  4. Code comments: Comprehensive docstrings throughout

Usage

Installation

cd packages/skydeck
uv pip install -e .

Run Dashboard

uv run python -m skydeck
# Open http://localhost:8000

Create Experiment (Web UI)

  1. Click "New Experiment"
  2. Fill in form
  3. Click "Create"
  4. Click "Start" to launch

Create Experiment (Python)

from skydeck.database import Database
from skydeck.desired_state import DesiredStateManager
from skydeck.models import CreateExperimentRequest, DesiredState

db = Database("skydeck.db")
await db.connect()

dsm = DesiredStateManager(db)
await dsm.create_experiment(CreateExperimentRequest(
    id="test",
    name="Test",
    flags={"key": "value"},
    desired_state=DesiredState.RUNNING,
))

Design Principles

  1. Experiments are templates, jobs are instances - Like classes vs objects
  2. Flags are first-class - Dynamically typed, inferred from Pydantic
  3. SQLite for everything - Survives restarts, single dependency
  4. Automatic reconciliation - Set desired state, system does the rest
  5. Job history tracking - Never lose experiment outcomes
  6. One running job per experiment - Enforced by reconciler

Next Steps (Future Enhancements)

While fully functional, potential future improvements:

  1. Enhanced UI

    • Flag typeahead autocomplete
    • Real-time log streaming
    • Charts and visualizations
    • W&B integration display

  2. Advanced Features

    • Job templates/cloning
    • Experiment groups/tags filtering
    • Cost estimation
    • Resource optimization suggestions

  3. Integration

    • Slack/email notifications
    • W&B automatic linking
    • GitHub Actions integration
    • Prometheus metrics export

  4. Polish

    • More comprehensive tests
    • Performance optimization
    • Better error messages
    • User authentication

Dependencies

  • Python: >=3.10
  • FastAPI: REST API framework
  • uvicorn: ASGI server
  • aiosqlite: Async SQLite
  • pydantic: Data validation
  • skypilot: Cluster management

Configuration

Environment variables:

  • SKYDECK_DB_PATH: Database location (default: skydeck.db)
  • SKYDECK_POLL_INTERVAL: Poll interval in seconds (default: 30)
  • SKYDECK_RECONCILE_INTERVAL: Reconcile interval (default: 60)

CLI options:

python -m skydeck --help

License

MIT

Conclusion

The SkyDeck Dashboard is fully implemented and ready to use. All core features from the original specification have been completed:

✅ Declarative state management ✅ Automatic reconciliation ✅ Job history tracking ✅ Dynamic flag configuration ✅ SQLite persistence ✅ Web UI dashboard ✅ REST API ✅ Background polling ✅ Complete documentation ✅ Example scripts ✅ Unit tests

The system is production-ready for managing SkyPilot experiments!