Best Self Hosted Alternatives to CodeSignal

INGInious is an automated exercises assessment platform designed to run and grade students' programming submissions inside isolated Docker environments. It provides a web frontend for students and teachers, an administration interface for course and task management, and integration points for external LMS platforms.

Key Features

• Automated grading of programming exercises using custom tests and pluggable grading environments
• Executes student code inside Docker-based sandboxes to isolate and control runtime behavior
• Web frontend for submissions and an admin UI for course/task management and student monitoring
• Integrations with external learning systems (LMS) such as Moodle and edX via standard connectors
• Deployable via Docker Compose with provided example grading environments and a tasks folder for courses
• Supports multiple programming languages through configurable grading containers and task definitions
• Includes demo tasks and tooling for creating and importing exercise sets

Use Cases

• University and classroom programming courses requiring scalable, consistent automated grading
• MOOCs and online learning platforms that need external graders integrated with LMS
• Technical training and coding interview platforms that require reproducible, sandboxed code evaluation

Limitations and Considerations

• Execution relies on Docker containers: secure configuration (SELinux, namespaces) is required for safely running untrusted code
• Out-of-the-box deployment is oriented around Docker Compose; large-scale horizontal scaling requires additional infrastructure and orchestration
• Administrators must manage and maintain grading environment images and task repositories to cover target languages and toolchains

INGInious is suitable for institutions and instructors who need a configurable, containerized autograding solution that integrates with existing LMS workflows. It emphasizes secure execution, extensible grading environments, and a teacher-focused administration interface.