App Store template
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Mage AI

Build, schedule, and monitor data pipelines with Mage AI on Sealos. Use a notebook-style editor with PostgreSQL metadata and persistent project files.

Launch in your Sealos workspace.

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Mage AI template preview
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Template deployments
14 on Sealos
Deployment
Your own instance
Category
AI

About this template

Overview

Build, schedule, and monitor data pipelines with Mage AI on Sealos. Use a notebook-style editor with PostgreSQL metadata and persistent project files.

From the documentation

Mage AI provides a notebook-style environment to build, schedule, and monitor data pipelines. The template provisions a dedicated PostgreSQL cluster for metadata and a persistent volume for project files at /home/src.

How to deploy Mage AI

  1. Choose Deploy now to start Mage AI in your Sealos workspace.
  2. Review default_owner_email, default_owner_password in the deployment form.
  3. Launch the template, then inspect the application status and resource cards in Canvas.

Resources to plan for

Start with the resources defined by the Mage AI template. Review CPU, memory, persistent storage, and network allocations for every service in Canvas. Capacity needs depend on your data and workload; monitor usage as they grow.

Template configuration and setup

Access after deployment

Use the application URL or connection details shown in Canvas. Follow the deployment guide for first-time account setup or client configuration, and keep generated credentials available for that step.

Hosting and billing

Sealos monthly plans include compute, memory, storage, and traffic. Size your plan for all deployed services. Software licenses and external AI or API services may have separate terms and charges. Confirm the applicable plan and optional charges in Cost Center.

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For current cloud charges, refer to Sealos plan pricing. Upstream documentation may reference earlier billing models.

Deploy and Host Mage AI on Sealos

Mage AI is an open-source data pipeline tool for building and running data workflows. This template deploys Mage AI with a PostgreSQL database and persistent storage on Sealos Cloud.

About Hosting Mage AI

Mage AI provides a notebook-style environment to build, schedule, and monitor data pipelines. The template provisions a dedicated PostgreSQL cluster for metadata and a persistent volume for project files at /home/src.

The deployment includes a public HTTPS endpoint via Ingress, automatic SSL certificates, and managed networking on Sealos. You can manage resources and environment variables through the Canvas without touching YAML.

Common Use Cases

  • ETL/ELT Pipelines: Ingest, transform, and load data from multiple sources
  • Scheduled Data Workflows: Run recurring jobs with built-in scheduling
  • Feature Engineering: Build reusable data transformations for ML pipelines
  • API Data Ingestion: Pull data from third-party APIs and normalize it
  • Data Quality Checks: Validate and monitor data integrity as part of pipelines

Dependencies for Mage AI Hosting

The Sealos template includes all required dependencies: Mage AI runtime, PostgreSQL database, and persistent storage.

Deployment Dependencies
Implementation Details

Architecture Components:

This template deploys the following services:

  • Mage AI: A StatefulSet running mage start magic on port 6789
  • PostgreSQL Cluster: KubeBlocks PostgreSQL 16.4.0 for pipeline metadata
  • PostgreSQL Init Job: Creates the mage database on first boot
  • Service + Ingress: Internal service with public HTTPS access
  • Persistent Volume: 1Gi storage mounted at /home/src for project files

Configuration:

  • Admin Credentials: Set DEFAULT_OWNER_EMAIL and DEFAULT_OWNER_PASSWORD during deployment
  • Database: Connection details are injected automatically; database name is mage
  • Connection URL: Mage builds its PostgreSQL URL from DB_USER, DB_PASS, DB_HOST, DB_PORT, and DB_NAME

License Information:

Mage AI is licensed under the Apache License 2.0. See the Mage AI GitHub repository for details.

Why Deploy Mage AI on Sealos?

Sealos is an AI-assisted Cloud Operating System built on Kubernetes that unifies the application lifecycle from development to production. By deploying Mage AI on Sealos, you get:

  • One-Click Deployment: Launch Mage AI with PostgreSQL and storage in minutes
  • Auto-Scaling Built-In: Adjust resources as workload grows without manual orchestration
  • Easy Customization: Configure environment variables and storage in the Canvas
  • Zero Kubernetes Expertise Required: Managed Kubernetes benefits without the complexity
  • Persistent Storage Included: Data and projects survive restarts with built-in volumes
  • Instant Public Access: Automatic HTTPS endpoint with SSL certificates
  • Pay-as-You-Go Efficiency: Scale resources to control cost

Deploy Mage AI on Sealos and focus on building data workflows instead of managing infrastructure.

Deployment Guide

  1. Visit Mage AI Template Page
  2. Click the "Deploy Now" button
  3. Configure the parameters in the popup dialog:
    • Default Owner Email: Admin login email
    • Default Owner Password: Admin login password
  4. Wait for deployment to complete (typically 2-4 minutes). After deployment, you will be redirected to the Canvas. For later changes, describe your requirements in the dialog to let AI apply updates, or click the relevant resource cards to modify settings.
  5. Access your Mage AI instance via the provided URLs:
    • Mage AI Web UI: open the provided URL or /sign-in, then log in with your default owner credentials. Mage AI creates this owner account automatically during the first startup; no separate registration step is required.

Configuration

After deployment, you can configure Mage AI through:

  • AI Dialog: Describe the changes you want and let AI apply updates directly
  • Resource Cards: Click the relevant resource cards to modify settings
  • Web UI: Log in at the provided URL or /sign-in using the default owner credentials. Self-registration is not required for the initial owner account.
  • Storage: Projects are stored in /home/src on a persistent volume

Scaling

This template runs a single Mage AI replica by default. To scale resources:

  1. Open Canvas in Sealos
  2. Select your Mage AI deployment
  3. Adjust CPU/Memory limits and click "Update"

Troubleshooting

Common Issues

Issue: Cannot log in to Mage AI

  • Cause: Incorrect default owner email or password
  • Solution: Verify credentials in the deployment configuration and update in Canvas if needed

Issue: Database connection failed

  • Cause: PostgreSQL is still initializing or the init job has not completed
  • Solution: Wait a few minutes and check logs for the PostgreSQL cluster and init job

Issue: 502/Ingress not ready

  • Cause: Mage AI service is still starting
  • Solution: Wait for the StatefulSet to become ready, then refresh the URL
Getting Help

Additional Resources

License

This Sealos template follows the repository licensing terms. Mage AI itself is licensed under the Apache License 2.0; see the Mage AI GitHub repository for details.

From launch to everyday operations

Why deploy
on Sealos

A shorter path from an app you want to an app you can run. Sealos brings deployment and ongoing operations into one place.

  1. One-click deployment

    Start with a ready-made template. Review its configuration and launch from the Sealos console.

  2. Managed Kubernetes

    Run on managed infrastructure with built-in workload scheduling and recovery.

  3. Automatic HTTPS

    Give your application a public HTTPS endpoint with certificates managed for you.

  4. Persistent storage

    Keep application data on persistent volumes across container restarts.

  5. Room to grow

    Adjust CPU, memory, and replicas from the console as your workload changes.

One template. Connected resources.

You Get the Whole Stack

Sealos provisions the resources defined by your template and brings them together in your workspace.

  • App Service

    Container workloads with configurable CPU, memory, and replicas.

  • Public HTTPS URL

    An address for your app, with managed TLS certificates.

  • Database

    A database provisioned alongside your app when the template calls for one.

  • Persistent Volume

    Storage for the files and data your application needs to keep.

  • Environment Variables

    Application settings and secrets configured in one place.

  • Logs & Metrics

    Inspect container logs and resource usage from the console.

Resources and their configuration vary by template. Review the deployment form for this app’s exact setup.

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