What Are GitHub Actions Runners? A Complete Beginner’s Guide to CI/CD Workflows

If you’ve ever pushed code to a GitHub repository and seen tests or deployments trigger automatically, you’ve already experienced the magic of GitHub Actions. But what powers those workflows behind the scenes?

The unsung hero is the GitHub Actions runner. Whether you’re a solo developer or part of a large engineering team, understanding runners is key to optimizing your CI/CD pipelines, reducing costs, and improving performance.

In this guide, we will present:

• What runners are and how they work
• The different types of runners available
• How to choose the right runner for your needs
• The costs involved and how to save money
• How platforms like Tenki make powerful CI/CD effortless

Let’s dive in :

What Is a GitHub Actions Runner?

A GitHub Actions runner is the compute environment—usually a virtual machine or container—that carries out the steps defined in your GitHub workflow.

Every time a workflow is triggered (like when you push code), GitHub uses a runner to process the instructions in your .github/workflows/*.yml file.

Think of it like the backstage crew making your CI/CD performance seamless.

How Runners Work in Your Workflow

Let’s look at a simple example:

on: [push]
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Install dependencies
        run: npm install
      - name: Run tests
        run: npm test

The line runs-on: ubuntu-latest tells GitHub to use a GitHub-hosted runner with Ubuntu. If you want to use a custom or third-party runner (like Tenki), you just update that line, like below

on: [push]
jobs:
  build:
    runs-on: tenki-standard-autoscale
    steps:
      - uses: actions/checkout@v2
      - name: Install dependencies
        run: npm install
      - name: Run tests
        run: npm test

💡 Tip: This small change unlocks more powerful hardware, faster builds, cost efficiency, seamless migration, and maintenance-free runners—all powered by Tenki.

The 3 Types of GitHub Actions Runners

1. GitHub-Hosted Runners

These are managed entirely by GitHub. Each job runs on a fresh virtual machine.

Pros:

• No setup required
• Includes popular tools pre-installed
• Maintained and secured by GitHub

Cons:

• Very old infrastructure, limited performance
• No GPU or ARM support
• High cost at scale

Best for: Small projects, automation exploration, very basic needs

2. Self-Hosted Runners

These are runners you install and manage on your own infrastructure (e.g., on-prem servers, your cloud VMs).

Pros:

• Full control over hardware and software
• Can use any OS, toolchain, or machine type

Cons:

• Manual setup and maintenance
• Security, updates, and scaling are your responsibility
• Not ephemeral by default (can lead to job residue)

Best for: Advanced teams with DevOps skills and very specific needs

3. Third-Party Runners

Third-party services offer the flexibility of self-hosted runners with the ease of cloud-based CI.

Pros:

• Ephemeral runners spun up fresh per job
• Support for custom hardware (GPU, ARM)
• Deploys in your cloud (AWS, GCP, Hetzner, etc.)

Cons:

• We’ve tried hard to find one… but we came up empty-handed..

Best for:Teams looking to scale CI/CD with low ops effort and full control.

4. Tenki

Tenki combines the power and flexibility of self-hosted runners with the simplicity of cloud-based CI/CD—offering seamless migration, zero-maintenance infrastructure, and a developer-friendly experience out of the box.

Pros:

• Ephemeral runners spun up fresh per job
• Built-in autoscaling
• 90% Cheaper than competition
• 30% Faster than competition
• 2 clicks workflow migrations

Cons:

• We’ve tried hard to find one… but we came up empty-handed..

Best for: Designed for teams or individuals who want to scale CI/CD with minimal ops overhead and complete control.

Comparison Table

Choosing the Right Runner Size

A common misconception is: "More CPU cores = faster builds."

While that can be true for some jobs, real performance depends on several factors:

• CPU-bound workflows (e.g. compilation) may benefit from more cores
• Memory-bound jobs (e.g. Docker builds) need more RAM
• I/O-heavy jobs (e.g. test artifact handling) may require disk/network tuning

💡Tips: Manual sizing often leads to overprovisioning or bottlenecks. Tenki solves this by autoscaling per job—giving each workflow the exact compute resources it needs, without waste.

Real-World Examples

✅ Microservices in Docker

• Resource Demands: Builds and runs multiple containers concurrently
• Pain Points: CPU and memory contention can lead to slow builds and higher cloud costs
• Recommended Solutions: Leverage Tenki’s autoscaled runners
• Key Benefits:
  – Tenki runners improve parallelism and reduce runtime via memory-efficient container handling
  – Lowers CI bill by reducing compute waste on underutilized VMs
  – Seamless scaling across services, enabling faster CI/CD pipelines

✅ Machine Learning Pipeline

• Resource Demands: Python workloads with heavy CPU/GPU requirements
• Pain Points: Lack of access to affordable, flexible GPUs delays training and model testing
• Recommended Solutions: Use Tenki’s large offering of runners
• Key Benefits:
  – Pay only for the GPU resources you need, when you need them
  – Eliminate queue times and resource contention common on shared runners
  – Supports hybrid workloads and larger datasets without cold starts

✅ Monorepo with Multiple Languages

• Resource Demands: Concurrent testing across JS, Go, Python services
• Pain Points: Long build queues and uneven resource distribution slow down developer workflows
• Recommended Solutions: Leverage Tenki’s autoscaled runners
• Key Benefits:
  – Parallel job execution across languages speeds up builds
  – Tenki automatically scales runners to meet CI demand, reducing bottlenecks
  – Improved visibility and control over resource usage across monorepo projects

Cost Considerations (and How to Save)

GitHub Actions Pricing (2025)

• 2,000 free minutes/month for public repos
• Usage beyond that is billed per minute, with higher rates for macOS

Self-Hosted Runners

• No GitHub usage cost
• But you pay for cloud/infra and must manage uptime, scaling, and security

Tenki: The Smart Middle Ground

Tenki Pricing Advantages:

• $10/month free usage included (~12.500
• Pay only for active minutes
• Autoscaling = no idle time costs, a single rate

Why Tenki Makes CI/CD Easier

Self-hosted runners can save money but often come with serious operational overhead:

• Setting up machines
• Writing autoscaling logic
• Handling VM cleanup and job isolation

Tenki removes all that.

You get:

• Seamless GitHub Actions integration: Works natively with your existing workflows.
• High-performance runners, zero maintenance: Fast execution without the burden of upkeep.
• Automatic scaling: Eliminate workflow maintenance with on-demand scaling.
• Ephemeral, isolated environments:Secure, siloed runners spun up fresh for every job.
• Full support for public repositories: Run workflows openly without extra configuration.

runs-on: tenki-standard-autoscale

👆That’s all you need to get started.

TL;DR

• GitHub Actions runners are the compute engines behind every CI/CD job.
• GitHub-hosted runners are easy but limited.
• Self-hosted runners offer flexibility, but add maintenance.
• Tenki combines the best of both worlds: performance, control, and simplicity.

💡Tips: Looking to cut costs or boost engineering productivity? Tenki makes it easy to save time and money!

👉 Start free at https://app.tenki.cloud/auth/registration

Frequently Asked Questions (FAQ)

• Do I need to rewrite my workflows to use Tenki?
  No. Simply change the runs-on label to match your Tenki runner.
• Can I test Tenki with one GitHub repository?
  Absolutely! You can start with one project and expand gradually.
• Are there any long-term contracts?
  No. Tenki offers flexible, pay-as-you-go pricing.
• Can Tenki handle bursty workloads?
  Yes! It autoscaling runners in seconds to handle high concurrency.

Glossary of Terms

Workflow: An automated process defined in a .yml file under .github/workflows, triggered by events like pushes or pull requests.

Job: A group of steps that execute on the same runner.

Step: An individual command or action, like installing dependencies or running tests.

Runner: The virtual machine (VM) or container that executes jobs in your workflow.

Queue Time: The waiting period before a job starts running.

Execution Time: The time it takes to complete a job once it begins.

Concurrency: The number of jobs that can run simultaneously.

Ephemeral Runner: A runner created for a single job, then automatically destroyed.

Autoscaling: Dynamically increasing or decreasing the number of runners based on demand.

Provisioning: Setting up and launching the compute resources needed for a runner.