mcuadros/ofelia

A docker job scheduler (aka. crontab for docker)

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Summary Information

Updated 23 minutes ago
Added to GitGenius on September 17th, 2026
Created on September 29th, 2015
Open Issues & Pull Requests: 152 (+0)
GitHub issues: Enabled
Number of forks: 207
Total Stargazers: 3,992 (+0)
Total Subscribers: 34 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 10.1 days
Mean response time: 147.2 days
90th percentile: 466.5 days
Tracked items: 58

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How this project is maintained

95% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Three people close 56% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 41
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,010 days
Stale 30+ days: 39
Stale 90+ days: 33

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (4)
  • question (2)
  • help wanted (1)

Most active issues this week

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Detailed Description

Ofelia is a job scheduler for Docker environments that replaces traditional cron for containerized workloads.

Ofelia addresses the limitations of cron in modern Docker-based infrastructure by providing a scheduler purpose-built for container environments. Rather than running commands on the host system, it leverages Docker's API to execute commands directly inside running containers or spawn new containers for one-off tasks. This approach eliminates the complexity of wrapper scripts and containerized cron solutions by treating Docker as a first-class execution target. The tool supports standard cron expression syntax for scheduling, allowing familiar time-based job definitions.

The project suits teams running Docker or Docker Swarm who need reliable job scheduling without adding complexity to their container orchestration. It works well for maintenance tasks, backups, and periodic operations that should run inside containers rather than on the host. Ofelia offers four job types: executing commands in existing containers, running commands in new containers, running commands on the host, and running commands as temporary services in Swarm mode. This flexibility means a single scheduler can handle diverse job patterns without requiring separate tools.

The project maintains a substantial user base reporting real-world issues and feature requests, indicating active adoption. Response times to issues and pull requests typically span one to two weeks. The issue tracker is dominated by enhancement requests and user questions, suggesting the tool is stable enough for production use while continuing to evolve based on user needs.