Live from the Runner: Interactively Debugging GitHub Actions with SSH and tmate

There is a specific kind of frustration reserved for DevOps engineers and developers working with CI/CD pipelines. It goes something like this: You write a workflow, push the code, and watch the progress bar spin. Two minutes later, it fails. You check the logs, but the error is ambiguous. You add a print statement, commit, push, and wait again. It fails again.

This cycle—often jokingly referred to as "Commit-Push-Pray"—is a massive drain on productivity. Unlike your local machine, the GitHub Actions runner is an ephemeral "black box." When it crashes, the evidence often disappears with the container.

But what if you could pause the workflow right at the moment of failure, open a terminal, and step inside the runner to look around? At Nohatek, we believe in optimizing development loops to be as tight as possible. Today, we are exploring a powerful technique to do just that using SSH and tmate.

The High Cost of Blind Debugging

Before diving into the technical implementation, it is important to understand why "blind debugging" is an issue worth solving, particularly for CTOs and tech leads managing large teams.

When a pipeline fails, the cost isn't just the few minutes it takes for the runner to execute. The real cost lies in context switching. Every time a developer has to wait 10 minutes for a build to fail, they likely switch tasks. When they return to fix the bug, they must reload the mental context of the problem. If fixing a CI issue takes 15 attempts, you haven't just lost two hours of compute time; you have lost a day of developer focus.

Furthermore, log files are static. They tell you what happened, but rarely why. They cannot show you:

• If a file permission was silently changed.
• If an environment variable was truncated.
• If a dependency was installed in the wrong path.

To solve this, we need interactivity. We need the ability to poke, prod, and execute commands within the live environment where the failure is occurring.

Implementing the Solution: How to Use action-tmate

The community-standard solution for this problem is an open-source action called mxschmitt/action-tmate. This action leverages tmate, a terminal multiplexer (a fork of tmux), to create an instant, encrypted SSH tunnel into your GitHub Actions runner.

Here is how to implement it. Let's assume you have a workflow that is failing during the testing step.

Step 1: Modify Your Workflow YAML

You can inject the tmate step directly before or after the failing step. Here is a basic example:

name: CI Debugging
on: [push]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v3
    
    # Your standard setup steps...
    
    - name: Setup Debug Session
      uses: mxschmitt/action-tmate@v3
      
    - name: Run Tests
      run: npm test

When the runner reaches the "Setup Debug Session" step, it will pause the workflow and provision an SSH server.

Step 2: Access the Runner

Once you push this change, navigate to the Actions tab in your GitHub repository and click on the running job. Look at the logs for the tmate step. You will see output resembling this:

Web shell: https://tmate.io/t/... SSH: ssh key@nyc1.tmate.io

You now have two options:

1. Web Shell: Click the HTTPS link to open a terminal directly in your browser. This is the fastest method.
2. SSH: Copy the SSH command into your local terminal. This is preferred if you want to use your local terminal tools or transfer files.

Once connected, you are inside the runner. You can navigate the file system, check environment variables with env, and run your build commands manually to see exactly where they break.

Best Practices: Security, Conditionals, and Cleanup

While powerful, opening an SSH tunnel into your CI environment comes with significant security considerations. You are essentially opening a door into your infrastructure. Here is how to do it professionally and safely.

1. Never Leave It in Production

The most important rule: Do not merge the tmate step into your main/production branch. If you do, your pipeline will hang indefinitely (or until the timeout limit), waiting for a user to connect. This wastes money on GitHub Actions minutes and blocks deployments.

2. Use Conditionals for Debugging

A smarter way to implement this is to configure the step to run only when a failure occurs. This allows the pipeline to run normally if everything is green, but opens a debug session immediately if it crashes.

- name: Setup tmate session
  uses: mxschmitt/action-tmate@v3
  if: ${{ failure() }}

By adding if: ${{ failure() }}, you automate the debugging process. You don't have to guess where the error is; the system invites you in only when things go wrong.

3. Security Boundaries

Be aware that anyone with read access to the repository logs can see the SSH connection string. For public repositories, this means anyone could potentially access the runner during that session. While the runner is ephemeral and isolated, they could potentially dump environment variables or secrets loaded into that specific job.

Pro Tip: If you are debugging workflows that handle sensitive production secrets, use a private repository or ensure you are using GitHub's environment secrets with restricted access.

The difference between a senior DevOps engineer and a junior one is often the toolset they use to diagnose problems. Moving from "blind" debugging to interactive debugging with SSH and tmate transforms a frustrating, hour-long troubleshooting session into a five-minute fix.

By inspecting the runner live, you validate assumptions, verify file paths, and test fixes in real-time without the overhead of constant commits. It is exactly the kind of efficiency optimization we prioritize at Nohatek.

Whether you are looking to streamline your CI/CD pipelines, migrate to the cloud, or implement AI-driven development workflows, having the right expertise matters. If your team is spending more time fixing pipelines than shipping features, it might be time to talk to us.