Documentation

• 1: About
• 1.1: License
• 2: Concept
• 2.1: Overview
• 2.2: Architecture
• 2.3: Storage
• 2.4: Snapshot
• 2.5: Clone
• 2.6: Monitoring
• 2.7: Security
• 3: Tutorial
• 3.1: Installation
• 3.2: Quick Start
• 3.3: VS Code
• 3.4: Jupyter
• 3.5: Claude Code
• 3.6: Database
• 3.7: Application
• 4: Task
• 4.1: Backup
• 4.2: Restore
• 4.3: Clone
• 4.4: Deploy
• 4.5: SSL
• 4.6: Domain
• 4.7: Scale
• 4.8: Migrate
• 4.9: Monitor
• 4.10: Upgrade
• 5: Reference
• 5.1: CLI
• 5.2: Configuration
• 5.3: VS Code Server
• 5.4: JupyterLab
• 5.5: PostgreSQL
• 5.6: Nginx
• 5.7: Grafana
• 5.8: JuiceFS
• 5.9: Extensions
• 5.10: REST API

1 - About

Piglet Run is a lightweight runtime environment from Pigsty, designed as a cloud coding sandbox for AI Web Coding.

What is Piglet Run?

Piglet Run integrates:

• PostgreSQL 18 with 400+ extensions
• JuiceFS distributed storage with PITR support
• VS Code Server for web-based development
• JupyterLab for data science
• Claude Code for AI-assisted coding
• Grafana for observability

All in a single, easy-to-deploy package.

Project Links

Topics

1.1 - License

Apache License 2.0

Piglet Run is licensed under the Apache License 2.0.

Copyright 2025 Ruohang Feng

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

What This Means

The Apache 2.0 license allows you to:

• ✅ Use - Use the software for any purpose
• ✅ Modify - Modify the source code
• ✅ Distribute - Distribute copies of the software
• ✅ Commercial Use - Use in commercial projects
• ✅ Patent Grant - Includes patent rights from contributors

Requirements

When using Piglet Run, you must:

• Include the license and copyright notice
• State any significant changes made to the code
• Include the NOTICE file if one exists

Third-Party Components

Piglet Run includes several third-party open source components:

Please refer to each component’s license for specific terms.

2 - Concept

Concept documentation helps you understand the principles and architecture behind Piglet Run.

What You’ll Learn

• How Piglet Run works under the hood
• The design philosophy and architecture
• Key concepts like snapshots, cloning, and storage

Topics

2.1 - Overview

What is Piglet Run?

Piglet Run is a lightweight runtime environment from Pigsty, designed as a cloud coding sandbox for AI Web Coding. It integrates PostgreSQL database, JuiceFS distributed storage, VS Code, JupyterLab, and more into a unified environment.

Why Piglet Run?

In the age of AI-assisted development, developers need:

• Instant development environments that just work
• Powerful databases with all extensions available
• Safe experimentation with easy rollback
• Seamless collaboration between humans and AI agents

Piglet Run provides all of this in a single package.

Key Features

Who is it for?

• Solo developers who want a powerful dev environment
• Teams that need shared development infrastructure
• AI developers using Claude Code or similar tools
• Data scientists working with PostgreSQL and Jupyter
• Learners exploring PostgreSQL and web development

How it works

┌─────────────────────────────────────────────────────────────┐
│                      Piglet Run                             │
├─────────────────────────────────────────────────────────────┤
│  ┌─────────┐  ┌─────────┐  ┌─────────┐  ┌─────────┐       │
│  │ VS Code │  │ Jupyter │  │ Claude  │  │  Nginx  │       │
│  │ Server  │  │   Lab   │  │  Code   │  │ Proxy   │       │
│  └────┬────┘  └────┬────┘  └────┬────┘  └────┬────┘       │
│       │            │            │            │             │
│       └────────────┴────────────┴────────────┘             │
│                         │                                   │
│  ┌──────────────────────┴──────────────────────┐           │
│  │              JuiceFS (Shared Storage)       │           │
│  └──────────────────────┬──────────────────────┘           │
│                         │                                   │
│  ┌──────────────────────┴──────────────────────┐           │
│  │         PostgreSQL 18 + 400+ Extensions     │           │
│  └─────────────────────────────────────────────┘           │
│                                                             │
│  ┌─────────────────────────────────────────────┐           │
│  │      VictoriaMetrics + Grafana (Monitoring) │           │
│  └─────────────────────────────────────────────┘           │
└─────────────────────────────────────────────────────────────┘

Next Steps

• Install Piglet Run to get started
• Learn about the Architecture
• Explore the Storage system

2.2 - Architecture

System Architecture

Piglet Run is built on top of Pigsty, providing a streamlined development environment.

Components

Network Architecture

Internet
    │
    ▼
┌─────────┐
│  Nginx  │ :80, :443
└────┬────┘
     │
     ├──────────────┬──────────────┬──────────────┐
     │              │              │              │
     ▼              ▼              ▼              ▼
┌─────────┐   ┌─────────┐   ┌─────────┐   ┌─────────┐
│ VS Code │   │ Jupyter │   │ Grafana │   │   App   │
│ /code   │   │/jupyter │   │  /ui    │   │   /*    │
└─────────┘   └─────────┘   └─────────┘   └─────────┘

Storage Architecture

All development work is stored in PostgreSQL via JuiceFS:

┌─────────────────────────────────────┐
│          Working Directory          │
│         ~/workspace                 │
└──────────────┬──────────────────────┘
               │
               ▼
┌─────────────────────────────────────┐
│            JuiceFS                  │
│     (POSIX-compatible FS)           │
└──────────────┬──────────────────────┘
               │
               ▼
┌─────────────────────────────────────┐
│          PostgreSQL                 │
│     (Metadata + Data Chunks)        │
└─────────────────────────────────────┘

Next Steps

• Learn about Storage
• Understand Snapshots

2.3 - Storage

JuiceFS Shared Storage

Piglet Run uses JuiceFS to provide a distributed filesystem backed by PostgreSQL.

Why JuiceFS?

• POSIX Compatible: Works like a normal filesystem
• Database-Backed: Data stored in PostgreSQL
• Snapshots: Point-in-time recovery support
• Multi-User: Share workspace across sessions

How It Works

┌────────────────────────────────────────────┐
│              Application Layer             │
│   (VS Code, Jupyter, Claude Code, etc.)    │
└──────────────────┬─────────────────────────┘
                   │ POSIX API
                   ▼
┌────────────────────────────────────────────┐
│               JuiceFS FUSE                 │
│         (Filesystem in Userspace)          │
└──────────────────┬─────────────────────────┘
                   │
        ┌──────────┴──────────┐
        │                     │
        ▼                     ▼
┌───────────────┐    ┌───────────────┐
│   Metadata    │    │  Data Chunks  │
│  (PostgreSQL) │    │  (PostgreSQL) │
└───────────────┘    └───────────────┘

Features

Next Steps

• Learn about Snapshots
• Understand Cloning

2.4 - Snapshot

Time Machine

Piglet Run provides point-in-time recovery for both database and filesystem.

Database PITR

PostgreSQL’s built-in PITR (Point-in-Time Recovery) allows you to restore the database to any point in time. Managed by pgBackRest.

# Show backup information
pig pb info

# List all backups
pig pb ls

# Create a full backup
pig pb backup full

# Restore to latest backup
pig pb restore

# Restore to specific time
pig pb restore -t "2025-01-29 10:00:00"

Filesystem Snapshots

JuiceFS snapshots preserve the state of your workspace:

# Create a snapshot (using juicefs CLI)
juicefs snapshot create /jfs/data snapshot-before-experiment

# List snapshots
juicefs snapshot list /jfs/data

# Restore from snapshot
juicefs snapshot restore /jfs/data snapshot-before-experiment

Use Cases

Backup Management

# View backup status
pig pb info

# View backup logs
pig pb log tail

# Create incremental backup
pig pb backup incr

# Create differential backup
pig pb backup diff

Next Steps

• Learn about Cloning
• See Restore Task
• See Backup Task

2.5 - Clone

Instant Cloning

Piglet Run supports Copy-on-Write (CoW) cloning for rapid database forking.

How It Works

Copy-on-Write means:

• Zero copy at clone time
• Only changed blocks consume storage
• TB-scale databases clone in milliseconds

Original Database
┌─────────────────────┐
│ Block A │ Block B │ Block C │
└────┬────┴────┬────┴────┬────┘
     │         │         │
     ▼         ▼         ▼
┌────────────────────────────┐
│      Shared Storage        │
└────────────────────────────┘
     ▲         ▲         ▲
     │         │         │
┌────┴────┬────┴────┬────┴────┐
│ Block A │ Block B │ Block C │ (shared)
│         │ Block B'│         │ (changed in clone)
└─────────┴─────────┴─────────┘
Cloned Database

Use Cases

Database Cloning

Using PostgreSQL utilities:

# Create database from template
pig pg psql -c "CREATE DATABASE dev TEMPLATE prod"

# Or using pg_dump/pg_restore for cross-server clone
pg_dump -Fc prod > prod.dump
pg_restore -d dev prod.dump

Using pgBackRest for Cloning

# Restore to a new cluster as a clone
pig pb restore --target-pgdata=/data/pg-clone

# Or restore to specific time point
pig pb restore -t "2025-01-29 10:00:00" --target-pgdata=/data/pg-clone

Filesystem Cloning with JuiceFS

# Clone directory using JuiceFS snapshot
juicefs snapshot create /jfs/workspace ws-snapshot
juicefs snapshot restore /jfs/workspace-clone ws-snapshot

Next Steps

• See Clone Task
• Learn about Snapshots

2.6 - Monitoring

Full Observability

Piglet Run includes a complete monitoring stack based on VictoriaMetrics and Grafana.

Components

Dashboards

Access Grafana at http://<ip>/ui

Available dashboards:

• Claude Code: AI agent monitoring
• PostgreSQL: Database performance
• System: Host metrics
• JuiceFS: Filesystem statistics

Metrics

Over 3000+ metrics collected:

• Database queries, connections, locks
• System CPU, memory, disk, network
• Application-specific metrics

Alerts

Configure alerts for:

• High CPU/memory usage
• Database connection limits
• Disk space warnings
• Query performance issues

Next Steps

• See Monitor Task
• Learn about Grafana Reference

2.7 - Security

Security Model

Piglet Run provides multiple layers of security for your development environment.

Access Control

Authentication

Default authentication methods:

• VS Code: Password or token
• Jupyter: Token-based
• Grafana: Username/password
• PostgreSQL: Role-based access

Encryption

Best Practices

1. Change default passwords immediately
2. Enable SSL for all services
3. Restrict network access
4. Regular security updates

Next Steps

• Configure SSL
• Set up Domain

3 - Tutorial

Tutorial documentation provides step-by-step guides to learn Piglet Run from scratch.

Learning Path

Follow these tutorials in order to get started:

1. Installation - Set up Piglet Run on your server
2. Quick Start - Create your first project
3. VS Code - Using the web-based VS Code
4. Jupyter - Data analysis with Jupyter
5. Claude Code - AI-assisted development
6. Database - Working with PostgreSQL

Topics

3.1 - Installation

Install Piglet Run

This tutorial guides you through installing Piglet Run on a fresh server.

Prerequisites

• OS: Linux (Ubuntu 22.04+, Debian 12+, RHEL 8+, Rocky 8+)
• CPU: 2+ cores recommended
• RAM: 4GB minimum, 8GB+ recommended
• Disk: 40GB+ free space
• Network: Internet access for package download

Quick Install

1. Install Pig CLI

# Default (Cloudflare CDN)
curl -fsSL https://repo.pigsty.io/pig | bash

# China Mirror
curl -fsSL https://repo.pigsty.cc/pig | bash

2. Setup Repositories

pig repo set          # Setup all required repositories

3. Install Pigsty with Piglet Profile

pig sty init          # Download Pigsty to ~/pigsty
cd ~/pigsty
./configure -m piglet # Configure with piglet preset
./install.yml         # Run installation playbook

Step-by-Step Installation

Download and Install Pig

curl -fsSL https://repo.pigsty.io/pig | bash

Setup Repositories

pig repo set                          # One-step repo setup
pig repo add all --region china       # Use China mirrors if needed

Install PostgreSQL and Extensions

pig install pg17                      # Install PostgreSQL 17
pig install pg_duckdb vector -v 17    # Install extensions

Install Pigsty Distribution

pig sty init                          # Download Pigsty
pig sty boot                          # Install Ansible
pig sty conf -m piglet                # Generate piglet config
pig sty deploy                        # Run deployment

Verify Installation

After installation, check status:

pig status                            # Check pig environment
pig ext status                        # Check installed extensions
pig pg status                         # Check PostgreSQL status

Access the services:

Troubleshooting

Check Logs

pig pg log tail                       # PostgreSQL logs
pig pt log -f                         # Patroni logs (if HA enabled)

Common Issues

Next Steps

• Continue with Quick Start
• Learn about VS Code

3.2 - Quick Start

Your First 5 Minutes

This tutorial gets you productive with Piglet Run in 5 minutes.

Access Your Environment

After installation, access your environment:

Create Your First Project

1. Open VS Code

Navigate to http://<ip>/code in your browser.

2. Open Terminal

Press Ctrl+` to open the integrated terminal.

3. Create a Project

cd ~/workspace
mkdir my-first-project
cd my-first-project

4. Create a Simple App

Create app.py:

from http.server import HTTPServer, SimpleHTTPRequestHandler

print("Server running on http://localhost:8000")
HTTPServer(('', 8000), SimpleHTTPRequestHandler).serve_forever()

5. Run It

python app.py

Connect to PostgreSQL

psql postgres://postgres@localhost/postgres

Or in Python:

import psycopg
conn = psycopg.connect("postgres://postgres@localhost/postgres")

Next Steps

• Learn more about VS Code
• Explore Jupyter
• Try Claude Code

3.3 - VS Code

Web-based VS Code

Learn to use the web-based VS Code server in Piglet Run.

Access

Open your browser and navigate to:

http://<ip>/code

Features

The web VS Code includes:

• Full VS Code experience in browser
• Extensions support
• Integrated terminal
• Git integration
• Python, Go, Node.js support

Getting Started

1. Open a Folder

Click “Open Folder” and select /root/workspace.

2. Install Extensions

Recommended extensions:

• Python
• Pylance
• GitLens
• Database Client

3. Configure Settings

Press Ctrl+, to open settings.

Tips

• Use Ctrl+Shift+P for command palette
• `Ctrl+`` for integrated terminal
• Ctrl+B to toggle sidebar

Next Steps

• Try Jupyter
• Learn Claude Code

3.4 - Jupyter

JupyterLab Tutorial

Learn to use JupyterLab for data analysis in Piglet Run.

Access

Navigate to:

http://<ip>/jupyter

Features

• Interactive Python notebooks
• Rich output (charts, tables, images)
• PostgreSQL integration
• Multiple kernels (Python, SQL)

Getting Started

1. Create a Notebook

Click “Python 3” under Notebook.

2. Connect to PostgreSQL

import psycopg
import pandas as pd

conn = psycopg.connect("postgres://postgres@localhost/postgres")
df = pd.read_sql("SELECT * FROM pg_stat_activity", conn)
df.head()

3. Visualize Data

import matplotlib.pyplot as plt

df['state'].value_counts().plot(kind='bar')
plt.show()

Tips

• Use Shift+Enter to run cells
• Save notebooks to /root/workspace/notebooks

Next Steps

• Learn Claude Code
• Explore Database

3.5 - Claude Code

AI-Assisted Development

Learn to use Claude Code for AI-assisted development in Piglet Run.

Prerequisites

You need an Anthropic API key. Set it up:

export ANTHROPIC_API_KEY="your-api-key"

Getting Started

1. Launch Claude Code

In VS Code terminal:

claude

2. Give Instructions

Ask Claude to help with your project:

> Create a FastAPI app with PostgreSQL integration

3. Review and Accept

Claude will:

• Analyze your request
• Generate code
• Explain the changes
• Wait for your approval

Best Practices

Safety

Piglet Run makes AI coding safer:

• Snapshots: Restore any time
• Monitoring: Track AI activity
• Isolation: Sandboxed environment

Monitoring

View Claude Code activity at:

http://<ip>/ui/d/claude-code

Next Steps

• Explore Database
• Build an Application

3.6 - Database

PostgreSQL Basics

Learn to work with PostgreSQL in Piglet Run.

Connect

Using psql

psql postgres://postgres@localhost/postgres

Using Python

import psycopg

conn = psycopg.connect("postgres://postgres@localhost/postgres")

Create Database

CREATE DATABASE myapp;

Install Extensions

PostgreSQL 18 with 400+ extensions available:

-- Vector search
CREATE EXTENSION vector;

-- Time series
CREATE EXTENSION timescaledb;

-- Full text search (Chinese)
CREATE EXTENSION zhparser;

Basic Operations

-- Create table
CREATE TABLE users (
    id SERIAL PRIMARY KEY,
    name TEXT NOT NULL,
    email TEXT UNIQUE,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

-- Insert data
INSERT INTO users (name, email) VALUES ('Alice', '[email protected]');

-- Query
SELECT * FROM users;

Monitoring

View database performance at:

http://<ip>/ui/d/pgsql-overview

Next Steps

• Build an Application
• Learn about Backup

3.7 - Application

Build and Deploy

Learn to build and deploy a web application in Piglet Run.

Create a FastAPI App

1. Set Up Project

cd ~/workspace
mkdir myapp && cd myapp
python -m venv venv
source venv/bin/activate
pip install fastapi uvicorn psycopg[binary]

2. Create Application

Create main.py:

from fastapi import FastAPI
import psycopg

app = FastAPI()

@app.get("/")
def root():
    return {"message": "Hello from Piglet Run!"}

@app.get("/users")
def get_users():
    conn = psycopg.connect("postgres://postgres@localhost/postgres")
    cur = conn.execute("SELECT * FROM users")
    return cur.fetchall()

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)

3. Run Locally

python main.py

4. Deploy with Nginx

See Deploy Task for production deployment.

Next Steps

• Learn to Deploy
• Set up SSL

4 - Task

Task documentation provides goal-oriented guides for specific operations.

How to Use

Each task guide focuses on accomplishing a specific goal:

• Problem-focused: Start with what you want to achieve
• Step-by-step: Clear instructions to follow
• Practical: Real-world scenarios

Topics

4.1 - Backup

Learn how to backup your database and files in Piglet Run.

Overview

Piglet Run provides multiple backup methods to protect your data:

• Database Backup: Full and incremental PostgreSQL backups
• File Backup: User files and configurations
• Snapshot: Complete system state capture

Quick Backup

Create a full backup with a single command:

pig backup create

Backup Database

Full Database Backup

pig backup db --full

Incremental Backup

pig backup db --incremental

Backup Specific Database

pig backup db mydb

Backup Files

Backup User Files

pig backup files

Backup Configurations

pig backup config

Scheduled Backups

Configure automatic backups in /etc/piglet/backup.yml:

backup:
  schedule: "0 2 * * *"  # Daily at 2 AM
  retention: 7           # Keep 7 days
  type: incremental

Backup Storage

Backups are stored in:

Next Steps

• Learn about Restore
• Understand Snapshots

4.2 - Restore

Learn how to restore your database and files from backups or snapshots.

Overview

Piglet Run supports multiple restore scenarios:

• Point-in-Time Recovery: Restore to any moment in time
• Full Restore: Restore from a complete backup
• Selective Restore: Restore specific databases or files

Quick Restore

Restore from the latest backup:

pig restore latest

Restore Database

List Available Backups

pig backup list

Restore Full Backup

pig restore db --backup 2024-01-15

Point-in-Time Recovery

pig restore db --time "2024-01-15 14:30:00"

Restore Specific Database

pig restore db mydb --backup 2024-01-15

Restore Files

Restore All Files

pig restore files --backup 2024-01-15

Restore Specific Directory

pig restore files /home/dba/projects --backup 2024-01-15

Restore from Snapshot

pig snapshot restore snap-20240115

Verification

After restore, verify data integrity:

pig verify db
pig verify files

Next Steps

• Learn about Backup
• Understand Clone

4.3 - Clone

Learn how to clone databases and environments in Piglet Run.

Overview

Cloning allows you to create exact copies of:

• Database: Clone a database for testing or development
• Environment: Clone the entire Piglet Run instance
• Schema Only: Clone structure without data

Quick Clone

Clone a database instantly:

pig clone db mydb mydb_copy

Clone Database

Full Clone

pig clone db production development

Schema Only

pig clone db production development --schema-only

Clone with Data Filter

pig clone db production development --filter "created_at > '2024-01-01'"

Clone Environment

Create Environment Clone

pig clone env --name staging

Clone to Remote Server

pig clone env --target user@remote-server

Clone from Snapshot

pig clone snapshot snap-20240115 --name dev-clone

Clone Options

Use Cases

• Development: Clone production for local development
• Testing: Create isolated test environments
• Analytics: Clone for reporting without impacting production

Next Steps

• Learn about Snapshots
• Understand Backup

4.4 - Deploy

Learn how to deploy web applications on Piglet Run.

Overview

Piglet Run supports deploying various web applications:

• Static Sites: HTML, CSS, JavaScript
• Node.js: Express, Next.js, React
• Python: Flask, Django, FastAPI
• PHP: Laravel, WordPress

Quick Deploy

Deploy a static site:

pig deploy ./my-site

Deploy Static Site

From Local Directory

pig deploy ./dist --name my-site

From Git Repository

pig deploy https://github.com/user/repo --name my-site

Deploy Node.js Application

Basic Deployment

cd my-node-app
pig deploy --type nodejs

With Custom Port

pig deploy --type nodejs --port 3000

Configuration

Create piglet.yml in your project:

type: nodejs
entry: server.js
port: 3000
env:
  NODE_ENV: production

Deploy Python Application

Flask Application

pig deploy --type python --framework flask

Django Application

pig deploy --type python --framework django

Deployment Management

List Deployments

pig deploy list

View Logs

pig deploy logs my-site

Restart Application

pig deploy restart my-site

Remove Deployment

pig deploy remove my-site

Next Steps

• Configure SSL for HTTPS
• Set up Custom Domain

4.5 - SSL

Learn how to configure SSL certificates for secure HTTPS connections.

Overview

Piglet Run supports multiple SSL certificate options:

• Let’s Encrypt: Free automatic certificates
• Self-Signed: For development and testing
• Custom: Bring your own certificates

Quick SSL Setup

Enable SSL with Let’s Encrypt:

pig ssl enable --domain example.com

Let’s Encrypt Certificates

Enable for Domain

pig ssl letsencrypt --domain example.com --email [email protected]

Multiple Domains

pig ssl letsencrypt --domain example.com --domain www.example.com

Wildcard Certificate

pig ssl letsencrypt --domain "*.example.com" --dns cloudflare

Self-Signed Certificates

Generate Self-Signed

pig ssl self-signed --domain localhost

For Development

pig ssl self-signed --domain dev.local --days 365

Custom Certificates

Install Custom Certificate

pig ssl install --cert /path/to/cert.pem --key /path/to/key.pem

With Certificate Chain

pig ssl install \
  --cert /path/to/cert.pem \
  --key /path/to/key.pem \
  --chain /path/to/chain.pem

Certificate Management

View Certificates

pig ssl list

Check Expiration

pig ssl status

Renew Certificates

pig ssl renew

Configuration

SSL settings in /etc/piglet/ssl.yml:

ssl:
  provider: letsencrypt
  email: [email protected]
  auto_renew: true
  renew_days: 30

Next Steps

• Set up Custom Domain
• Learn about Security

4.6 - Domain

Learn how to set up custom domains for your Piglet Run services.

Overview

Configure custom domains for:

• Main Application: Your primary domain
• Subdomains: Service-specific subdomains
• Multiple Domains: Support multiple domains

Quick Setup

Add a custom domain:

pig domain add example.com

DNS Configuration

Required DNS Records

Point your domain to Piglet Run:

Using Cloudflare

pig domain add example.com --dns cloudflare --api-key YOUR_API_KEY

Add Custom Domain

Primary Domain

pig domain add example.com --primary

Subdomain for Services

pig domain add code.example.com --service vscode
pig domain add jupyter.example.com --service jupyter

Domain Management

List Domains

pig domain list

Remove Domain

pig domain remove old-domain.com

Set Primary

pig domain primary example.com

Configuration

Domain settings in /etc/piglet/domains.yml:

domains:
  primary: example.com
  aliases:
    - www.example.com
  services:
    vscode: code.example.com
    jupyter: jupyter.example.com
    grafana: monitor.example.com

Verify Domain

Check domain configuration:

pig domain verify example.com

Next Steps

• Configure SSL for HTTPS
• Learn about Nginx Configuration

4.7 - Scale

Learn how to scale your Piglet Run resources up or down.

Overview

Piglet Run supports scaling:

• Database: Adjust PostgreSQL resources
• Storage: Expand disk capacity
• Services: Scale service resources

Quick Scale

Scale database resources:

pig scale db --cpu 4 --memory 8G

Scale Database

Increase Resources

pig scale db --cpu 4 --memory 16G

Adjust Connection Limits

pig scale db --max-connections 200

Configure Shared Buffers

pig scale db --shared-buffers 4G

Scale Storage

Expand Disk

pig scale storage --size 100G

Add Storage Volume

pig scale storage add --mount /data/extra --size 50G

Scale Services

VS Code Server

pig scale service vscode --memory 4G

JupyterLab

pig scale service jupyter --memory 8G

Resource Limits

View current resource allocation:

pig scale status

Example output:

Service     CPU    Memory   Storage
---------   ----   ------   -------
PostgreSQL  2      4G       20G
VS Code     1      2G       -
Jupyter     1      2G       -
Nginx       0.5    512M     -

Configuration

Scale settings in /etc/piglet/resources.yml:

resources:
  postgres:
    cpu: 2
    memory: 4G
    storage: 20G
  vscode:
    cpu: 1
    memory: 2G
  jupyter:
    cpu: 1
    memory: 2G

Best Practices

• Monitor resource usage before scaling
• Scale gradually to avoid disruption
• Test changes in development first

Next Steps

• Set up Monitoring
• Learn about Architecture

4.8 - Migrate

Learn how to migrate data from other systems to Piglet Run.

Overview

Piglet Run supports migration from:

• Other PostgreSQL: Migrate from existing PostgreSQL instances
• MySQL/MariaDB: Convert and migrate from MySQL
• Cloud Databases: AWS RDS, Google Cloud SQL, Azure Database
• Files: Import from SQL dumps or CSV files

Quick Migration

Migrate from another PostgreSQL:

pig migrate postgres://user:pass@source-host/dbname

Migrate from PostgreSQL

Direct Connection

pig migrate pg \
  --host source.example.com \
  --port 5432 \
  --user migrate_user \
  --database production

From pg_dump File

pig migrate import backup.sql

Schema Only

pig migrate pg --host source.example.com --schema-only

Migrate from MySQL

Direct Migration

pig migrate mysql \
  --host mysql.example.com \
  --user migrate_user \
  --database myapp

With Type Mapping

pig migrate mysql --host source --type-map mysql-to-pg.yml

Migrate from Cloud

AWS RDS

pig migrate rds \
  --instance mydb-instance \
  --region us-west-2 \
  --profile aws-profile

Google Cloud SQL

pig migrate cloudsql \
  --instance myproject:region:instance \
  --credentials /path/to/credentials.json

Import Files

SQL Dump

pig migrate import dump.sql --database mydb

CSV Files

pig migrate csv data.csv --table users --database mydb

Multiple CSV Files

pig migrate csv ./data/ --database mydb

Migration Options

Verification

Verify migration:

pig migrate verify --source postgres://source/db --target postgres://target/db

Next Steps

• Learn about Backup
• Understand PostgreSQL Configuration

4.9 - Monitor

Learn how to set up alerts and monitoring for your Piglet Run instance.

Overview

Piglet Run includes comprehensive monitoring:

• Grafana Dashboards: Visual monitoring
• Alerting: Configurable alerts
• Metrics: Prometheus-based metrics
• Logs: Centralized logging

Quick Setup

Access monitoring dashboard:

pig monitor open
# Opens Grafana at http://<ip>/ui

Grafana Dashboards

Available Dashboards

Access Dashboards

# Default credentials
URL: http://<ip>/ui
User: admin
Password: (shown during install)

Set Up Alerts

Enable Email Alerts

pig alert email --to [email protected] --smtp smtp.example.com

Enable Slack Alerts

pig alert slack --webhook https://hooks.slack.com/services/...

Enable Webhook Alerts

pig alert webhook --url https://api.example.com/alerts

Alert Rules

View Alert Rules

pig alert list

Add Custom Alert

pig alert add \
  --name "High CPU" \
  --condition "cpu_usage > 80" \
  --duration 5m \
  --severity warning

Default Alerts

Configuration

Alert configuration in /etc/piglet/alerts.yml:

alerts:
  email:
    enabled: true
    to: [email protected]
    smtp:
      host: smtp.example.com
      port: 587
  slack:
    enabled: false
    webhook: ""
  rules:
    - name: high_cpu
      expr: cpu_usage > 80
      for: 5m
      severity: warning

View Logs

# All service logs
pig logs

# Specific service
pig logs postgres
pig logs nginx

Next Steps

• Learn about Grafana
• Understand Architecture

4.10 - Upgrade

Learn how to upgrade your Piglet Run installation.

Overview

Piglet Run upgrades include:

• Minor Updates: Bug fixes and security patches
• Major Upgrades: New features and improvements
• PostgreSQL Upgrades: Database version upgrades

Quick Upgrade

Upgrade to latest version:

pig upgrade

Check for Updates

View Current Version

pig version

Check Available Updates

pig upgrade check

Perform Upgrade

Standard Upgrade

pig upgrade --backup

Upgrade to Specific Version

pig upgrade --version 2.5.0

Dry Run

pig upgrade --dry-run

Upgrade PostgreSQL

Check Compatible Versions

pig upgrade pg --list

Upgrade Database Version

pig upgrade pg --version 17

With Full Backup

pig upgrade pg --version 17 --backup

Before Upgrading

1. Create Backup

   pig backup create --full
   

2. Check Compatibility

   pig upgrade check --verbose
   

3. Review Release Notes

   pig upgrade notes
   

Rollback

If upgrade fails:

Restore from Backup

pig restore --backup pre-upgrade

Rollback to Previous Version

pig upgrade rollback

Upgrade History

View upgrade history:

pig upgrade history

Example output:

Version    Date         Status
-------    ----------   -------
2.5.0      2024-01-15   Current
2.4.1      2024-01-01   Previous
2.4.0      2023-12-15   Archived

Configuration

Upgrade settings in /etc/piglet/upgrade.yml:

upgrade:
  auto_backup: true
  notify: true
  channel: stable  # stable, beta, nightly

Next Steps

• Learn about Backup
• Understand Restore

5 - Reference

Reference documentation provides detailed technical information.

How to Use

Reference docs are for looking up specific information:

• CLI Commands: Full command reference
• Configuration: All configuration options
• Services: Details about built-in services

Topics

5.1 - CLI

Command-line interface reference for Piglet Run, powered by pig - the PostgreSQL package manager.

Overview

The pig CLI provides complete control over PostgreSQL installation, extension management, and system operations.

Installation

# Default (Cloudflare CDN)
curl -fsSL https://repo.pigsty.io/pig | bash

# China Mirror
curl -fsSL https://repo.pigsty.cc/pig | bash

Verify installation:

pig --version
pig --help

Global Options

Main Commands

Repository Management (pig repo)

pig repo list                    # List available repos and modules
pig repo info                    # Show repository information
pig repo status                  # Display current repo config
pig repo add [modules...]        # Add repositories
pig repo set                     # Setup all required repos (recommended)
pig repo rm [modules...]         # Remove repositories
pig repo update                  # Update package cache

Extension Management (pig ext)

pig ext list [pattern]           # Search/list extensions
pig ext info <name>              # Show extension details
pig ext avail <name>             # Show availability matrix
pig ext status                   # Show installed extensions
pig ext scan                     # Scan installed extensions
pig ext add <name> [-v version]  # Install extension
pig ext rm <name>                # Remove extension
pig ext update                   # Update extensions

Installation Alias (pig install)

pig install pg17                 # Install PostgreSQL 17
pig install pg_duckdb -v 17      # Install extension for PG 17
pig install vector postgis       # Install multiple extensions

PostgreSQL Management (pig pg)

pig pg init                      # Initialize data directory
pig pg start                     # Start PostgreSQL
pig pg stop                      # Stop PostgreSQL
pig pg status                    # Check status
pig pg psql [database]           # Connect to database
pig pg ps                        # Show connections
pig pg vacuum [database]         # Vacuum database
pig pg log tail                  # View logs in real-time

Backup Management (pig pb)

pig pb info                      # Show backup information
pig pb ls                        # List all backups
pig pb backup                    # Create backup
pig pb backup full               # Full backup
pig pb backup incr               # Incremental backup
pig pb restore                   # Restore to latest
pig pb restore -t <time>         # Restore to specific time
pig pb log tail                  # View backup logs

Patroni Cluster (pig pt)

pig pt list                      # List cluster members
pig pt config                    # Show cluster config
pig pt status                    # View service status
pig pt log -f                    # View logs in real-time

Pigsty Management (pig sty)

pig sty init                     # Download and install Pigsty
pig sty boot                     # Install Ansible dependencies
pig sty conf [-m template]       # Generate configuration
pig sty deploy                   # Run deployment playbook
pig sty list                     # List available versions

System Status (pig status)

pig status                       # Show environment status

Environment Variables

Examples

# Quick setup for Piglet Run
pig repo set                     # Setup repositories
pig install pg17                 # Install PostgreSQL 17
pig install vector pg_duckdb    # Install extensions
pig sty init && pig sty deploy  # Deploy Pigsty

# Daily operations
pig pg status                    # Check PostgreSQL
pig pb info                      # Check backups
pig ext status                   # Check extensions

See Also

• Configuration Reference
• PostgreSQL Reference
• Installation Tutorial

5.2 - Configuration

Configuration file reference for Piglet Run.

Overview

Piglet Run uses YAML configuration files located in /etc/piglet/.

Main Configuration

File: /etc/piglet/piglet.yml

# Piglet Run Configuration

# System settings
system:
  hostname: piglet
  timezone: UTC
  locale: en_US.UTF-8

# Database settings
database:
  host: localhost
  port: 5432
  user: dba
  database: postgres
  max_connections: 100
  shared_buffers: 256MB

# Services
services:
  vscode:
    enabled: true
    port: 8080
  jupyter:
    enabled: true
    port: 8888
  grafana:
    enabled: true
    port: 3000

# Storage
storage:
  data_dir: /data
  backup_dir: /data/backup
  temp_dir: /tmp/piglet

# Logging
logging:
  level: info
  file: /var/log/piglet/piglet.log
  max_size: 100M
  max_files: 10

Database Configuration

File: /etc/piglet/database.yml

# PostgreSQL Configuration

postgresql:
  version: 17
  data_directory: /data/postgres

  # Connection settings
  listen_addresses: localhost
  port: 5432
  max_connections: 100

  # Memory settings
  shared_buffers: 256MB
  effective_cache_size: 768MB
  work_mem: 4MB
  maintenance_work_mem: 64MB

  # WAL settings
  wal_level: replica
  max_wal_size: 1GB
  min_wal_size: 80MB

  # Logging
  log_destination: csvlog
  logging_collector: on
  log_directory: pg_log

Service Configuration

VS Code Server

File: /etc/piglet/vscode.yml

vscode:
  enabled: true
  port: 8080
  auth: password
  extensions:
    - ms-python.python
    - rust-lang.rust-analyzer

JupyterLab

File: /etc/piglet/jupyter.yml

jupyter:
  enabled: true
  port: 8888
  notebook_dir: /home/dba/notebooks
  kernels:
    - python3
    - ir

Backup Configuration

File: /etc/piglet/backup.yml

backup:
  enabled: true
  schedule: "0 2 * * *"
  retention: 7

  database:
    type: full
    compress: true

  files:
    enabled: true
    paths:
      - /home/dba
      - /etc/piglet

Network Configuration

File: /etc/piglet/network.yml

network:
  # Domain settings
  domain: localhost

  # SSL settings
  ssl:
    enabled: false
    cert: /etc/piglet/ssl/cert.pem
    key: /etc/piglet/ssl/key.pem

  # Proxy settings
  proxy:
    enabled: false
    host: proxy.example.com
    port: 8080

Environment Variables

Override configuration with environment variables:

export PIG_DATABASE_PORT=5433
export PIG_SERVICES_VSCODE_ENABLED=false
export PIG_LOGGING_LEVEL=debug

See Also

• CLI Reference
• PostgreSQL Configuration

5.3 - VS Code Server

VS Code Server configuration and details for Piglet Run.

Overview

Piglet Run includes a pre-configured VS Code Server (code-server) for browser-based development.

Access

Default URL: http://<ip>/code

Configuration

File: /etc/piglet/vscode.yml

vscode:
  enabled: true
  bind_addr: 127.0.0.1:8080
  auth: password
  password: ${VSCODE_PASSWORD}
  cert: false

  # User data directory
  user_data_dir: /home/dba/.local/share/code-server

  # Extensions directory
  extensions_dir: /home/dba/.local/share/code-server/extensions

Pre-installed Extensions

Installing Extensions

Via CLI

code-server --install-extension ms-python.python

Via Settings

1. Open VS Code in browser
2. Go to Extensions (Ctrl+Shift+X)
3. Search and install extensions

Settings

Default settings location: /home/dba/.local/share/code-server/User/settings.json

{
  "editor.fontSize": 14,
  "editor.tabSize": 2,
  "editor.formatOnSave": true,
  "terminal.integrated.defaultProfile.linux": "bash",
  "python.defaultInterpreterPath": "/usr/bin/python3",
  "files.autoSave": "afterDelay"
}

Service Management

# Start VS Code server
pig start vscode

# Stop VS Code server
pig stop vscode

# Restart VS Code server
pig restart vscode

# View logs
pig logs vscode

Keyboard Shortcuts

Troubleshooting

Connection Issues

# Check service status
systemctl status code-server

# Check port binding
ss -tlnp | grep 8080

# View logs
journalctl -u code-server -f

Extension Issues

# List installed extensions
code-server --list-extensions

# Reinstall extension
code-server --uninstall-extension EXTENSION_ID
code-server --install-extension EXTENSION_ID

See Also

• VS Code Tutorial
• Configuration Reference

5.4 - JupyterLab

JupyterLab configuration and details for Piglet Run.

Overview

Piglet Run includes JupyterLab for interactive computing and data analysis.

Access

Default URL: http://<ip>/jupyter

Configuration

File: /etc/piglet/jupyter.yml

jupyter:
  enabled: true
  port: 8888
  token: ${JUPYTER_TOKEN}

  # Notebook directory
  notebook_dir: /home/dba/notebooks

  # Allowed origins
  allow_origin: "*"

  # Kernels
  kernels:
    - python3
    - ir
    - julia

JupyterLab Configuration

File: /home/dba/.jupyter/jupyter_lab_config.py

c.ServerApp.ip = '127.0.0.1'
c.ServerApp.port = 8888
c.ServerApp.open_browser = False
c.ServerApp.notebook_dir = '/home/dba/notebooks'
c.ServerApp.token = ''
c.ServerApp.allow_origin = '*'

Available Kernels

Install Additional Kernels

# R kernel
R -e "IRkernel::installspec()"

# Julia kernel
julia -e 'using Pkg; Pkg.add("IJulia")'

Pre-installed Extensions

Install Extensions

pip install jupyterlab-git
jupyter labextension install @jupyterlab/git

Service Management

# Start Jupyter
pig start jupyter

# Stop Jupyter
pig stop jupyter

# Restart Jupyter
pig restart jupyter

# View logs
pig logs jupyter

Connecting to PostgreSQL

import psycopg2
import pandas as pd

# Connect to database
conn = psycopg2.connect(
    host="localhost",
    database="postgres",
    user="dba"
)

# Query data
df = pd.read_sql("SELECT * FROM my_table", conn)
df.head()

Using SQL Magic

%load_ext sql
%sql postgresql://dba@localhost/postgres

%%sql
SELECT * FROM pg_stat_activity LIMIT 5;

Keyboard Shortcuts

Troubleshooting

Connection Issues

# Check service status
systemctl status jupyter

# Check port binding
ss -tlnp | grep 8888

# View logs
journalctl -u jupyter -f

Kernel Issues

# List available kernels
jupyter kernelspec list

# Reinstall kernel
python -m ipykernel install --user

See Also

• Jupyter Tutorial
• Configuration Reference

5.5 - PostgreSQL

PostgreSQL database configuration and details for Piglet Run.

Overview

Piglet Run includes PostgreSQL 17 as the primary database with optimized defaults.

Connection Details

Connection Strings

Local Connection

psql -U dba -d postgres

TCP Connection

postgresql://dba@localhost:5432/postgres

With Password

postgresql://dba:password@localhost:5432/postgres

Configuration

File: /data/postgres/postgresql.conf

Memory Settings

# Memory
shared_buffers = 256MB
effective_cache_size = 768MB
work_mem = 4MB
maintenance_work_mem = 64MB
huge_pages = try

Connection Settings

# Connections
listen_addresses = 'localhost'
port = 5432
max_connections = 100
superuser_reserved_connections = 3

WAL Settings

# WAL
wal_level = replica
max_wal_size = 1GB
min_wal_size = 80MB
wal_buffers = 8MB
checkpoint_completion_target = 0.9

Logging

# Logging
log_destination = 'csvlog'
logging_collector = on
log_directory = 'pg_log'
log_filename = 'postgresql-%Y-%m-%d_%H%M%S.log'
log_rotation_age = 1d
log_rotation_size = 100MB
log_statement = 'ddl'
log_min_duration_statement = 1000

Client Authentication

File: /data/postgres/pg_hba.conf

# TYPE  DATABASE        USER            ADDRESS                 METHOD
local   all             all                                     trust
host    all             all             127.0.0.1/32            scram-sha-256
host    all             all             ::1/128                 scram-sha-256

Service Management

# Start PostgreSQL
pig start postgres

# Stop PostgreSQL
pig stop postgres

# Restart PostgreSQL
pig restart postgres

# Reload configuration
pig reload postgres

# View logs
pig logs postgres

Database Management

# Create database
pig db create mydb

# List databases
pig db list

# Drop database
pig db drop mydb

# Connect to database
pig db connect mydb

User Management

# Create user
pig user create myuser

# Grant privileges
psql -c "GRANT ALL ON DATABASE mydb TO myuser"

# Change password
pig user passwd myuser

Backup and Restore

# Full backup
pig backup db --full

# Point-in-time recovery
pig restore db --time "2024-01-15 14:30:00"

Performance Tuning

Recommended Settings by RAM

Monitoring

# Connection statistics
psql -c "SELECT * FROM pg_stat_activity"

# Database size
psql -c "SELECT pg_database.datname, pg_size_pretty(pg_database_size(pg_database.datname)) FROM pg_database"

# Table statistics
psql -c "SELECT * FROM pg_stat_user_tables"

See Also

• Database Tutorial
• Extensions Reference
• Backup Task

5.6 - Nginx

Nginx web server configuration for Piglet Run.

Overview

Piglet Run uses Nginx as a reverse proxy and web server for all services.

Configuration

Main config: /etc/nginx/nginx.conf

Site configs: /etc/nginx/conf.d/

Default Configuration

File: /etc/nginx/conf.d/piglet.conf

# Piglet Run Nginx Configuration

upstream vscode {
    server 127.0.0.1:8080;
}

upstream jupyter {
    server 127.0.0.1:8888;
}

upstream grafana {
    server 127.0.0.1:3000;
}

server {
    listen 80;
    server_name _;

    # Homepage
    location / {
        root /www/piglet;
        index index.html;
    }

    # VS Code Server
    location /code {
        proxy_pass http://vscode;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }

    # JupyterLab
    location /jupyter {
        proxy_pass http://jupyter;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_set_header Host $host;
    }

    # Grafana
    location /ui {
        proxy_pass http://grafana;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }
}

SSL Configuration

File: /etc/nginx/conf.d/piglet-ssl.conf

server {
    listen 443 ssl http2;
    server_name example.com;

    ssl_certificate /etc/piglet/ssl/cert.pem;
    ssl_certificate_key /etc/piglet/ssl/key.pem;
    ssl_protocols TLSv1.2 TLSv1.3;
    ssl_ciphers ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256;
    ssl_prefer_server_ciphers off;

    # ... location blocks ...
}

# Redirect HTTP to HTTPS
server {
    listen 80;
    server_name example.com;
    return 301 https://$server_name$request_uri;
}

Service Management

# Start Nginx
pig start nginx

# Stop Nginx
pig stop nginx

# Restart Nginx
pig restart nginx

# Reload configuration
pig reload nginx

# Test configuration
nginx -t

Custom Site Configuration

Create custom site config:

cat > /etc/nginx/conf.d/mysite.conf << 'EOF'
server {
    listen 80;
    server_name mysite.example.com;

    root /www/mysite;
    index index.html;

    location / {
        try_files $uri $uri/ =404;
    }
}
EOF

nginx -t && systemctl reload nginx

Proxy Configuration

WebSocket Support

location /ws {
    proxy_pass http://backend;
    proxy_http_version 1.1;
    proxy_set_header Upgrade $http_upgrade;
    proxy_set_header Connection "upgrade";
    proxy_read_timeout 86400;
}

Node.js Application

location /app {
    proxy_pass http://127.0.0.1:3001;
    proxy_set_header Host $host;
    proxy_set_header X-Real-IP $remote_addr;
    proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
    proxy_set_header X-Forwarded-Proto $scheme;
}

Logging

Access log: /var/log/nginx/access.log

Error log: /var/log/nginx/error.log

log_format main '$remote_addr - $remote_user [$time_local] "$request" '
                '$status $body_bytes_sent "$http_referer" '
                '"$http_user_agent" "$http_x_forwarded_for"';

access_log /var/log/nginx/access.log main;

Rate Limiting

limit_req_zone $binary_remote_addr zone=api:10m rate=10r/s;

location /api {
    limit_req zone=api burst=20 nodelay;
    proxy_pass http://backend;
}

Troubleshooting

# Test configuration
nginx -t

# Check error log
tail -f /var/log/nginx/error.log

# Check access log
tail -f /var/log/nginx/access.log

# View connections
ss -tlnp | grep nginx

See Also

• SSL Configuration
• Domain Setup
• Deploy Applications

5.7 - Grafana

Grafana monitoring dashboard configuration for Piglet Run.

Overview

Piglet Run includes Grafana for comprehensive monitoring and visualization.

Access

Default URL: http://<ip>/ui

Default credentials:

• Username: admin
• Password: (shown during installation)

Configuration

File: /etc/grafana/grafana.ini

[server]
http_port = 3000
root_url = %(protocol)s://%(domain)s/ui/
serve_from_sub_path = true

[security]
admin_user = admin
admin_password = ${GRAFANA_PASSWORD}

[auth.anonymous]
enabled = false

[dashboards]
default_home_dashboard_path = /var/lib/grafana/dashboards/home.json

[database]
type = postgres
host = localhost:5432
name = grafana
user = grafana

Pre-installed Dashboards

Data Sources

Prometheus

apiVersion: 1
datasources:
  - name: Prometheus
    type: prometheus
    url: http://localhost:9090
    access: proxy
    isDefault: true

PostgreSQL

datasources:
  - name: PostgreSQL
    type: postgres
    url: localhost:5432
    database: postgres
    user: grafana
    secureJsonData:
      password: ${GRAFANA_DB_PASSWORD}

Loki (Logs)

datasources:
  - name: Loki
    type: loki
    url: http://localhost:3100
    access: proxy

Service Management

# Start Grafana
pig start grafana

# Stop Grafana
pig stop grafana

# Restart Grafana
pig restart grafana

# View logs
pig logs grafana

Creating Dashboards

Via UI

1. Click “+” in left sidebar
2. Select “Dashboard”
3. Add panels with queries
4. Save dashboard

Via Provisioning

Place JSON dashboard files in /var/lib/grafana/dashboards/

# /etc/grafana/provisioning/dashboards/default.yaml
apiVersion: 1
providers:
  - name: default
    folder: ''
    type: file
    options:
      path: /var/lib/grafana/dashboards

Alerting

Configure Email

[smtp]
enabled = true
host = smtp.example.com:587
user = [email protected]
password = ${SMTP_PASSWORD}
from_address = [email protected]

Create Alert Rule

1. Edit panel query
2. Go to “Alert” tab
3. Set conditions
4. Configure notifications

Useful Queries

PostgreSQL Connections

pg_stat_activity_count

CPU Usage

100 - (avg by (instance) (rate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)

Memory Usage

(1 - node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes) * 100

Disk Usage

(1 - node_filesystem_avail_bytes / node_filesystem_size_bytes) * 100

API Access

Generate API key:

curl -X POST -H "Content-Type: application/json" \
  -d '{"name":"mykey", "role": "Admin"}' \
  http://admin:password@localhost:3000/api/auth/keys

Troubleshooting

# Check service status
systemctl status grafana-server

# View logs
journalctl -u grafana-server -f

# Test database connection
psql -U grafana -d grafana -c "SELECT 1"

See Also

• Monitoring Task
• PostgreSQL Reference

5.8 - JuiceFS

JuiceFS distributed filesystem configuration for Piglet Run.

Overview

Piglet Run uses JuiceFS for distributed storage, enabling snapshots and fast cloning.

Architecture

JuiceFS consists of:

• Metadata Engine: PostgreSQL stores file metadata
• Object Storage: S3-compatible storage for data blocks
• FUSE Client: Mounts filesystem locally

Configuration

File: /etc/piglet/juicefs.yml

juicefs:
  name: piglet
  metadata: postgres://dba@localhost:5432/juicefs
  storage: minio
  bucket: http://localhost:9000/piglet
  access_key: ${MINIO_ACCESS_KEY}
  secret_key: ${MINIO_SECRET_KEY}

  # Mount options
  mount_point: /data/jfs
  cache_dir: /var/cache/juicefs
  cache_size: 10240  # 10GB

Mount Configuration

File: /etc/juicefs/piglet.conf

[piglet]
meta = postgres://dba@localhost:5432/juicefs
storage = minio
bucket = http://localhost:9000/piglet
access-key = ${MINIO_ACCESS_KEY}
secret-key = ${MINIO_SECRET_KEY}

# Performance options
cache-dir = /var/cache/juicefs
cache-size = 10240
buffer-size = 300
prefetch = 3

Service Management

# Mount filesystem
pig mount jfs

# Unmount filesystem
pig umount jfs

# Check status
pig status jfs

# View statistics
juicefs stats /data/jfs

Commands

Format Filesystem

juicefs format \
  --storage minio \
  --bucket http://localhost:9000/pig \
  postgres://dba@localhost:5432/juicefs \
  piglet

Mount Filesystem

juicefs mount \
  postgres://dba@localhost:5432/juicefs \
  /data/jfs \
  --cache-dir /var/cache/juicefs \
  --cache-size 10240

Check Filesystem

juicefs fsck postgres://dba@localhost:5432/juicefs

Snapshot Operations

Create Snapshot

juicefs snapshot create /data/jfs snap-$(date +%Y%m%d)

List Snapshots

juicefs snapshot list /data/jfs

Restore Snapshot

juicefs snapshot restore /data/jfs snap-20240115

Delete Snapshot

juicefs snapshot delete /data/jfs snap-20240115

Clone Operations

# Clone directory
juicefs clone /data/jfs/source /data/jfs/dest

# Clone with snapshot
juicefs clone /data/jfs/.snapshots/snap-20240115 /data/jfs/restored

Performance Tuning

Cache Settings

# Increase cache size
juicefs config /data/jfs --cache-size 20480

# Enable writeback
juicefs config /data/jfs --writeback

Metadata Cache

# Entry cache TTL
juicefs mount ... --entry-cache 3 --dir-entry-cache 3 --attr-cache 3

Monitoring

Statistics

juicefs stats /data/jfs

Output:

usage: 10.2 GiB (1234567 inodes)
sessions: 1
trash: 0 (0 Bytes)

Prometheus Metrics

juicefs mount ... --metrics localhost:9567

Troubleshooting

# Check mount status
mount | grep juicefs

# View logs
journalctl -u juicefs -f

# Debug mode
juicefs mount --debug ...

# Repair filesystem
juicefs fsck --repair postgres://dba@localhost:5432/juicefs

See Also

• Storage Concept
• Snapshot Concept
• Clone Task

5.9 - Extensions

PostgreSQL extensions available in Piglet Run.

Overview

Piglet Run includes 340+ PostgreSQL extensions from the Pigsty ecosystem.

Pre-installed Extensions

Core Extensions

Vector & AI

Time Series

Geospatial

Full Text Search

Installing Extensions

Via SQL

-- Create extension
CREATE EXTENSION pgvector;

-- Create extension in specific schema
CREATE EXTENSION postgis SCHEMA public;

-- Update extension
ALTER EXTENSION pgvector UPDATE;

Via CLI

pig ext install pgvector
pig ext install postgis

Listing Extensions

Installed Extensions

SELECT * FROM pg_extension;

Available Extensions

SELECT * FROM pg_available_extensions ORDER BY name;

Extension Details

SELECT * FROM pg_available_extension_versions
WHERE name = 'pgvector';

Extension Configuration

pg_stat_statements

-- Enable tracking
ALTER SYSTEM SET shared_preload_libraries = 'pg_stat_statements';

-- Configure
ALTER SYSTEM SET pg_stat_statements.track = 'all';
ALTER SYSTEM SET pg_stat_statements.max = 10000;

pgvector

-- Create extension
CREATE EXTENSION vector;

-- Create vector column
CREATE TABLE items (
    id SERIAL PRIMARY KEY,
    embedding vector(384)
);

-- Create index
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);

PostGIS

-- Create extension
CREATE EXTENSION postgis;

-- Create geometry column
CREATE TABLE locations (
    id SERIAL PRIMARY KEY,
    name TEXT,
    geom geometry(Point, 4326)
);

-- Spatial query
SELECT name FROM locations
WHERE ST_DWithin(geom, ST_MakePoint(-122.4, 37.8)::geography, 1000);

TimescaleDB

-- Create extension
CREATE EXTENSION timescaledb;

-- Create hypertable
CREATE TABLE metrics (
    time TIMESTAMPTZ NOT NULL,
    device_id INTEGER,
    value DOUBLE PRECISION
);

SELECT create_hypertable('metrics', 'time');

Managing Extensions

# List installed extensions
pig ext list

# Show extension info
pig ext info pgvector

# Remove extension
pig ext remove pgvector

See Also

• PostgreSQL Reference
• Database Tutorial

5.10 - REST API

REST API reference for Piglet Run.

Overview

Piglet Run provides a REST API for programmatic access to all features.

Base URL

http://<ip>/api/v1

Authentication

API Key

curl -H "Authorization: Bearer YOUR_API_KEY" \
  http://localhost/api/v1/status

Generate API Key

pig api key create --name mykey

Endpoints

System

Get Status

GET /api/v1/status

Response:

{
  "status": "healthy",
  "version": "2.5.0",
  "uptime": 86400,
  "services": {
    "postgres": "running",
    "vscode": "running",
    "jupyter": "running"
  }
}