Warehouse13

Enterprise Test Artifact Storage

A lightweight, cloud-native API for storing and querying test artifacts including CSV files, JSON files, binary files, and packet captures (PCAP). Built with FastAPI and supports both AWS S3 and self-hosted MinIO storage backends.

Features

• Multi-format Support: Store CSV, JSON, binary files, and PCAP files
• Flexible Storage: Switch between AWS S3 and self-hosted MinIO
• Rich Metadata: Track test configurations, results, and custom metadata
• Powerful Querying: Query artifacts by test name, suite, result, tags, date ranges, and more
• RESTful API: Clean REST API with automatic OpenAPI documentation
• Cloud-Native: Fully containerized with Docker and Kubernetes/Helm support
• Production-Ready: Includes GitLab CI/CD pipeline for automated deployments

Architecture

┌─────────────┐
│   FastAPI   │  ← REST API
│   Backend   │
└──────┬──────┘
       │
       ├─────────┐
       ↓         ↓
┌──────────┐  ┌────────────┐
│PostgreSQL│  │ S3/MinIO   │
│(Metadata)│  │ (Blobs)    │
└──────────┘  └────────────┘

• PostgreSQL: Stores artifact metadata, test configs, and query indexes
• S3/MinIO: Stores actual file contents (blob storage)
• FastAPI: Async REST API for uploads, downloads, and queries

Quick Start

Standard Deployment (Internet Access)

Linux/macOS:

./quickstart.sh

Windows (PowerShell):

.\quickstart.ps1

Air-Gapped/Restricted Environment Deployment

For environments with restricted npm access:

./quickstart-airgap.sh

This script:

1. Builds Angular locally (where npm works)
2. Packages pre-built files into Docker
3. Starts all services

See DEPLOYMENT.md for detailed instructions.

Manual Setup with Docker Compose

1. Clone the repository:

git clone <repository-url>
cd datalake

2. Copy environment configuration:

cp .env.example .env

3. Start all services:

docker-compose up -d

4. Access the application:

• Web UI: http://localhost:8000
• API Docs: http://localhost:8000/docs
• MinIO Console: http://localhost:9001

Using Python Directly

1. Install dependencies:

pip install -r requirements.txt

2. Set up PostgreSQL and MinIO/S3

3. Configure environment variables in .env

4. Run the application:

python -m uvicorn app.main:app --reload

API Usage

Upload an Artifact

curl -X POST "http://localhost:8000/api/v1/artifacts/upload" \
  -F "file=@test_results.csv" \
  -F "test_name=auth_test" \
  -F "test_suite=integration" \
  -F "test_result=pass" \
  -F 'test_config={"browser":"chrome","timeout":30}' \
  -F 'tags=["regression","smoke"]' \
  -F "description=Authentication test results"

Query Artifacts

curl -X POST "http://localhost:8000/api/v1/artifacts/query" \
  -H "Content-Type: application/json" \
  -d '{
    "test_suite": "integration",
    "test_result": "fail",
    "start_date": "2024-01-01T00:00:00",
    "limit": 50
  }'

Download an Artifact

curl -X GET "http://localhost:8000/api/v1/artifacts/123/download" \
  -o downloaded_file.csv

Get Presigned URL

curl -X GET "http://localhost:8000/api/v1/artifacts/123/url?expiration=3600"

List All Artifacts

curl -X GET "http://localhost:8000/api/v1/artifacts/?limit=100&offset=0"

Delete an Artifact

curl -X DELETE "http://localhost:8000/api/v1/artifacts/123"

API Endpoints

Method	Endpoint	Description
POST	/api/v1/artifacts/upload	Upload a new artifact with metadata
GET	/api/v1/artifacts/{id}	Get artifact metadata by ID
GET	/api/v1/artifacts/{id}/download	Download artifact file
GET	/api/v1/artifacts/{id}/url	Get presigned download URL
DELETE	/api/v1/artifacts/{id}	Delete artifact and file
POST	/api/v1/artifacts/query	Query artifacts with filters
GET	/api/v1/artifacts/	List all artifacts (paginated)
GET	/	API information
GET	/health	Health check
GET	/docs	Interactive API documentation

Configuration

Environment Variables

Variable	Description	Default
DATABASE_URL	PostgreSQL connection string	postgresql://user:password@localhost:5432/datalake
STORAGE_BACKEND	Storage backend (s3 or minio)	minio
AWS_ACCESS_KEY_ID	AWS access key (for S3)	-
AWS_SECRET_ACCESS_KEY	AWS secret key (for S3)	-
AWS_REGION	AWS region (for S3)	us-east-1
S3_BUCKET_NAME	S3 bucket name	test-artifacts
MINIO_ENDPOINT	MinIO endpoint	localhost:9000
MINIO_ACCESS_KEY	MinIO access key	minioadmin
MINIO_SECRET_KEY	MinIO secret key	minioadmin
MINIO_BUCKET_NAME	MinIO bucket name	test-artifacts
MINIO_SECURE	Use HTTPS for MinIO	false
API_HOST	API host	0.0.0.0
API_PORT	API port	8000
MAX_UPLOAD_SIZE	Max upload size (bytes)	524288000 (500MB)

Switching Between S3 and MinIO

To use AWS S3:

STORAGE_BACKEND=s3
AWS_ACCESS_KEY_ID=your_key
AWS_SECRET_ACCESS_KEY=your_secret
AWS_REGION=us-east-1
S3_BUCKET_NAME=your-bucket

To use self-hosted MinIO:

STORAGE_BACKEND=minio
MINIO_ENDPOINT=minio:9000
MINIO_ACCESS_KEY=minioadmin
MINIO_SECRET_KEY=minioadmin
MINIO_BUCKET_NAME=test-artifacts

Deployment

Kubernetes with Helm

Quick Start:

helm install warehouse13 ./helm/warehouse13 --namespace warehouse13 --create-namespace

Production Deployment:

helm install warehouse13 ./helm/warehouse13 \
  --namespace warehouse13 \
  --create-namespace \
  --values ./helm/warehouse13/values-production.yaml

Air-Gapped Deployment:

helm install warehouse13 ./helm/warehouse13 \
  --namespace warehouse13 \
  --create-namespace \
  --values ./helm/warehouse13/values-airgapped.yaml

Access the Application:

kubectl port-forward -n warehouse13 svc/warehouse13-frontend 4200:80
kubectl port-forward -n warehouse13 svc/warehouse13-api 8000:8000

Helm Documentation

• Full Helm Guide: HELM-DEPLOYMENT.md
• Chart README: helm/warehouse13/README.md
• Quick Start: helm/warehouse13/QUICKSTART.md
• Example Configurations:
  • Development: values-dev.yaml
  • Production: values-production.yaml
  • Air-Gapped: values-airgapped.yaml

Helm Configuration

All component images are fully configurable in helm/warehouse13/values.yaml:

• PostgreSQL image and version
• MinIO image and version
• API image and version
• Frontend image and version
• Resource limits and requests
• Storage backend configuration
• Ingress and TLS settings
• Persistence and storage classes

GitLab CI/CD

The included .gitlab-ci.yml provides:

• Automated testing
• Linting
• Docker image builds
• Deployments to dev/staging/prod

Required GitLab CI/CD Variables:

• CI_REGISTRY_USER: Docker registry username
• CI_REGISTRY_PASSWORD: Docker registry password
• KUBE_CONFIG_DEV: Base64-encoded kubeconfig for dev
• KUBE_CONFIG_STAGING: Base64-encoded kubeconfig for staging
• KUBE_CONFIG_PROD: Base64-encoded kubeconfig for prod

Database Schema

The artifacts table stores:

• File metadata (name, type, size, storage path)
• Test information (name, suite, config, result)
• Custom metadata and tags
• Timestamps and versioning

Example Use Cases

Store Test Results

Upload CSV files containing test execution results with metadata about the test suite and configuration.

Archive Packet Captures

Store PCAP files from network tests with tags for easy filtering and retrieval.

Track Test Configurations

Upload JSON test configurations and query them by date, test suite, or custom tags.

Binary Artifact Storage

Store compiled binaries, test data files, or any binary artifacts with full metadata.

Development

Running Tests

pytest tests/ -v

Code Formatting

black app/
flake8 app/

Database Migrations

alembic revision --autogenerate -m "description"
alembic upgrade head

Troubleshooting

Cannot Connect to Database

• Verify PostgreSQL is running
• Check DATABASE_URL is correct
• Ensure database exists

Cannot Upload Files

• Check storage backend is running (MinIO or S3 accessible)
• Verify credentials are correct
• Check file size is under MAX_UPLOAD_SIZE

MinIO Connection Failed

• Ensure MinIO service is running
• Verify MINIO_ENDPOINT is correct
• Check MinIO credentials

License

[Your License Here]

Support

For issues and questions, please open an issue in the repository.