SadServers/sadservers

SadServers: Linux & DevOps Troubleshooting Scenarios SaaS

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SadServers/sadservers has 3k+ stars and 100+ forks on GitHub, is written in HCL, and was last pushed on Sep 29, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 27 minutes ago
Added to GitGenius on October 1st, 2026
Created on August 6th, 2022
Open Issues & Pull Requests: 3 (+0)
GitHub issues: Enabled
Number of forks: 117
Total Stargazers: 3,007 (+0)
Total Subscribers: 27 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 6.6 days
Mean response time: 79.0 days
90th percentile: 323.6 days
Tracked items: 18

Charts & Analytics

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Issue Activity (beta)

Open issues: 0
New in 7 days: 0
Closed in 7 days: 0
Avg open age: N/A days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

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

Top labels

  • scenario (3)
  • bug (1)

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Detailed Description

SadServers is a SaaS platform that provides Linux and DevOps troubleshooting practice through real-server scenarios in a Capture-the-Flag format.

The platform addresses the gap between theoretical Linux knowledge and practical troubleshooting ability by presenting users with real-world problems on ephemeral Linux servers. Each scenario describes a specific issue and provides a test condition to verify when the problem is solved. Users access servers through an in-browser SSH shell and have a set time to diagnose and fix the problem. The scenarios cover common production software like databases and web servers, as well as containerization technologies like Docker and Kubernetes, with difficulty ranging from general Linux troubleshooting to technology-specific challenges.

The tool is designed for software developers, system administrators, DevOps engineers, and SREs preparing for troubleshooting-focused job interviews or seeking to improve their practical skills. Organizations use it to assess candidates for Linux, DevOps, and SRE positions. The platform differs from earlier sandbox solutions by offering specific, bounded problems with clear success criteria on actual servers rather than generic environments. The infrastructure supports resumable VMs, command history logging, and a replay system for reviewing solutions.

The project maintains automated testing and linting practices with CI/CD pipelines supporting continuous deployment. Pull requests are used for code review and feature flags enable controlled rollout of changes. The codebase includes documented functions and comments supporting maintainability. The team actively manages issues and maintains a public roadmap while accepting community contributions, including a program for users to create and monetize new scenarios.