simple-krr-dashboard

Note

This project is not affiliated with robusta-dev/krr.

Simple KRR dashboard for Kubernetes resource reporting, using robusta-dev/krr to gather data.

Requirements

• Python 3.13+
• pipenv for dependency management
• robusta-dev/krr for Kubernetes resource reporting data

Installation

Data Collection

The dashboard uses data generated by krr using the following command:

krr simple --fileoutput report.table.csv --use-oomkill-data --formatter csv

Local Installation

1. Clone the repository

2. Create and activate a virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # On Unix/macOS
   # or
   .venv\Scripts\activate  # On Windows

3. Install dependencies:

   pipenv install

Docker Installation

1. Build the Docker image:

   docker build -t simple-krr-dashboard .

2. Run the container:

   docker run -v $(pwd)/reports:/reports -p 80:80 simple-krr-dashboard

The dashboard will be available at http://localhost:80

Usage

Local Usage

To run the dashboard:

pipenv run start

Or directly using Python (make sure you're in the project root directory):

PYTHONPATH=src python src/simple_krr_dashboard/main.py

Docker Usage

The Docker container exposes port 80 for the web interface. You can access the dashboard by opening your web browser and navigating to http://localhost:80

Development Commands

# Run tests
pipenv run test

# Run linter
pipenv run lint

# Format code
pipenv run format

# Type checking
pipenv run typecheck

Environment Variables

The following environment variables can be used to configure the application:

Variable	Description	Default	Required
APP_NAME	Name of the application	"Simple KRR Dashboard"	No
APP_VERSION	Version of the application	"1.0.0"	No
KUBERNETES_CLUSTER_NAME	Name of the Kubernetes cluster	None	No
KUBERNETES_DASHBOARD_CSV_PATH	Path to the CSV file containing Kubernetes data	"/reports/report.table.csv"	No
LOG_LEVEL	Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)	"INFO"	No
LOG_FORMAT	Format string for log messages	"%(asctime)s - %(name)s - %(levelname)s - %(message)s"	No
LOG_OUTPUT_FORMAT	Log output format (text, logfmt, json)	"text"	No
DISABLE_HTTP_LOGS	Disable HTTP access logs from Gunicorn	"false"	No

Logging Configuration

The application uses two types of logs:

1. Application Logs: Controlled by LOG_LEVEL (DEBUG, INFO, WARNING, ERROR, CRITICAL) and LOG_OUTPUT_FORMAT (text, logfmt, json)
2. HTTP Access Logs: Controlled by DISABLE_HTTP_LOGS (true/false)

Log Output Formats

The application supports three log output formats:

Text Format (Default)

Human-readable text format suitable for development and debugging.

docker run -v $(pwd)/reports:/reports -p 80:80 -e LOG_OUTPUT_FORMAT=text simple-krr-dashboard

Example output:

2025-12-12 20:30:45,123 - simple_krr_dashboard.main - INFO - Starting application
2025-12-12 20:30:45,456 - simple_krr_dashboard.data - WARNING - No cluster name configured

Logfmt Format

Machine-readable key-value format, ideal for log aggregation systems like Grafana Loki.

docker run -v $(pwd)/reports:/reports -p 80:80 -e LOG_OUTPUT_FORMAT=logfmt simple-krr-dashboard

Example output:

time=2025-12-12T20:30:45.123456 level=info logger=simple_krr_dashboard.main msg="Starting application"
time=2025-12-12T20:30:45.456789 level=warning logger=simple_krr_dashboard.data msg="No cluster name configured"

JSON Format

Structured JSON output, perfect for log parsing and analysis tools like ELK stack, Splunk, or cloud logging services.

docker run -v $(pwd)/reports:/reports -p 80:80 -e LOG_OUTPUT_FORMAT=json simple-krr-dashboard

Example output:

{"time": "2025-12-12T20:30:45.123456", "level": "info", "logger": "simple_krr_dashboard.main", "message": "Starting application"}
{"time": "2025-12-12T20:30:45.456789", "level": "warning", "logger": "simple_krr_dashboard.data", "message": "No cluster name configured"}

Configuration Examples

Disable HTTP access logs (recommended for production):

docker run -v $(pwd)/reports:/reports -p 80:80 -e DISABLE_HTTP_LOGS=true simple-krr-dashboard

Enable HTTP access logs (useful for debugging):

docker run -v $(pwd)/reports:/reports -p 80:80 -e DISABLE_HTTP_LOGS=false simple-krr-dashboard

Change application log level:

# Show only errors
docker run -v $(pwd)/reports:/reports -p 80:80 -e LOG_LEVEL=ERROR simple-krr-dashboard

# Show debug information
docker run -v $(pwd)/reports:/reports -p 80:80 -e LOG_LEVEL=DEBUG simple-krr-dashboard

Production-ready configuration with JSON logs:

docker run -v $(pwd)/reports:/reports -p 80:80 \
  -e LOG_LEVEL=INFO \
  -e LOG_OUTPUT_FORMAT=json \
  -e DISABLE_HTTP_LOGS=true \
  simple-krr-dashboard

Development configuration with detailed text logs:

docker run -v $(pwd)/reports:/reports -p 80:80 \
  -e LOG_LEVEL=DEBUG \
  -e LOG_OUTPUT_FORMAT=text \
  -e DISABLE_HTTP_LOGS=false \
  simple-krr-dashboard

Testing

The project uses pytest for testing. To run the tests:

1. Install test dependencies:

   pipenv install --dev

2. Run the tests:

   pipenv run pytest

3. Run tests with coverage report:

   pipenv run pytest --cov=simple_krr_dashboard tests/

Test Structure

The tests are organized in the following structure:

tests/
├── __init__.py
├── conftest.py           # Common test fixtures
├── test_app.py          # Application tests
├── test_config.py       # Configuration tests
├── test_dashboard.py    # Dashboard component tests
├── test_data.py         # Data processing tests
├── test_logging.py      # Logging tests
└── test_utils.py        # Utility function tests

Writing Tests

When adding new features, please include corresponding tests. The project follows these testing guidelines:

• Use pytest fixtures for common setup
• Mock external dependencies (e.g., file system, data processing)
• Test both success and error cases
• Include docstrings for test functions
• Use meaningful test names that describe the behavior being tested

Contributing

Please read the CONTRIBUTING.md file for details on our code of conduct and the process for submitting pull requests.

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Developed with ❤️ by @ialejandro and Cursor.com