Platform comparison guide

Complete decision matrix and platform selection guide for self-hosted runners

Choosing the right platform for your self-hosted runners is crucial for DevOps success. This comprehensive guide provides detailed comparisons, decision frameworks, and migration strategies to help you select the optimal platform for your specific needs.

Overview#

Self-hosted runners give you control over your CI/CD infrastructure, but platform selection can dramatically impact your productivity, security, and operational costs. The right choice depends on your team size, technical requirements, existing infrastructure, and long-term goals.

Why platform choice matters:

• Performance: Build times can vary 2-5x between platforms
• Scaling: Auto-scaling capabilities differ significantly
• Cost: Total ownership costs range from free to enterprise pricing
• Security: Built-in security features and compliance vary widely
• Integration: DevOps Hub API compatibility and feature depth

This guide compares four major platforms to help you make an informed decision based on concrete criteria rather than assumptions.

Feature comparison matrix#

Setup complexity analysis#

GitHub Actions (3/5 - Medium)#

Time to first runner: 15-30 minutes

Pros:

• Well-documented setup process
• Single binary download and configuration
• Automatic updates available
• Integration with GitHub ecosystem

Cons:

• Requires GitHub organization access
• Limited customization without enterprise features
• Network connectivity requirements

1
# Typical setup time breakdown
2
# Download and extract: 2 minutes
3
# Configuration: 5-10 minutes
4
# Service setup: 3-5 minutes
5
# First test run: 5-10 minutes

GitLab Runners (3/5 - Medium)#

Time to first runner: 20-45 minutes

Pros:

• Multiple executor types for flexibility
• Docker integration out-of-the-box
• Good documentation and examples

Cons:

• Executor choice can be overwhelming
• Kubernetes executor requires cluster knowledge
• Registration token management

Jenkins Agents (5/5 - Very High)#

Time to first runner: 2-4 hours

Pros:

• Ultimate flexibility and customization
• Extensive plugin ecosystem
• Mature platform with enterprise features

Cons:

• Steep learning curve
• Requires Jenkins controller setup
• Complex authentication and security configuration
• Multiple connection methods to understand

Bazel Remote Execution (4/5 - High)#

Time to first runner: 1-3 hours

Pros:

• Horizontal scaling by design
• Excellent build performance
• Container-native execution

Cons:

• Requires Bazel build system knowledge
• gRPC networking complexity
• Limited to Bazel-compatible projects

Scaling capabilities#

Auto-scaling comparison#

Scaling scenarios#

High-concurrency builds (50+ parallel jobs):

1. Bazel RBE - Purpose-built for massive parallelization
2. GitLab Runners - Kubernetes executor scales efficiently
3. GitHub Actions - Good for repository-bound workflows
4. Jenkins Agents - Requires significant configuration effort

Burst workloads (occasional high demand):

1. GitHub Actions - Excellent burst handling with hosted runners
2. Bazel RBE - Rapid worker provisioning
3. GitLab Runners - Docker Machine auto-scaling
4. Jenkins Agents - Manual intervention often needed

Cost-optimized scaling:

1. GitLab Runners - Efficient resource utilization
2. Jenkins Agents - Maximum control over infrastructure costs
3. Bazel RBE - Pay-per-compute model
4. GitHub Actions - Can be expensive for large-scale usage

Security considerations#

Built-in security features#

GitHub Actions:

• OpenID Connect (OIDC) for cloud authentication
• Encrypted secrets management
• IP allowlists and repository restrictions
• Audit logs and compliance features

GitLab Runners:

• Role-based access control (RBAC)
• Project-level and group-level runners
• Container execution isolation
• Variable masking and protection

Jenkins Agents:

• Extensive security plugin ecosystem
• Matrix-based security model
• Script approval and sandboxing
• Credential management system

Bazel Remote Execution:

• Container isolation by design
• gRPC authentication and encryption
• Network segmentation capabilities
• Audit trail for all executions

Security hardening comparison#

Security-focused recommendations#

High-security environments:

1. GitLab Runners - Strong RBAC and isolation features
2. GitHub Actions - Good security with proper configuration
3. Jenkins Agents - Highly customizable but requires security expertise
4. Bazel RBE - Container isolation but limited built-in security

DevOps Hub integration#

API compatibility and integration depth#

GitHub Actions (⭐⭐⭐⭐⭐ Full Integration):

1
# Deep integration with branch management
2
- name: Create DevOps Hub Branch
3
  uses: devopshub/create-branch@v1
4
  with:
5
    parent: main
6
    name: feature-${{ github.run_number }}
7
8
- name: Run Tests
9
  env:
10
    DATABASE_URL: ${{ steps.create-branch.outputs.connection-string }}
11
  run: npm test
12
13
- name: Cleanup Branch
14
  if: always()
15
  uses: devopshub/cleanup-branch@v1

GitLab Runners (⭐⭐⭐⭐ Strong Integration):

1
# Custom CI/CD templates and API calls
2
create_environment:
3
  script:
4
    - devopshub branch create --parent main --name "gitlab-${CI_PIPELINE_ID}"
5
    - echo "CONNECTION_STRING=$(devopshub branch connection-string)" >> build.env
6
  artifacts:
7
    reports:
8
      dotenv: build.env

Jenkins Agents (⭐⭐⭐ Moderate Integration):

1
// Pipeline library integration
2
pipeline {
3
    stages {
4
        stage('Setup') {
5
            steps {
6
                script {
7
                    def branch = devOpsHub.createBranch([
8
                        parent: 'main',
9
                        name: "jenkins-${BUILD_NUMBER}"
10
                    ])
11
                    env.DATABASE_URL = branch.connectionString
12
                }
13
            }
14
        }
15
    }
16
}

Bazel Remote Execution (⭐⭐⭐ Moderate Integration):

1
# Custom rules and API integration
2
load("@rules_devopshub//devopshub:defs.bzl", "devopshub_environment")
3
4
devopshub_environment(
5
    name = "test_env",
6
    parent_branch = "main",
7
    branch_name = "bazel-test",
8
    connection_var = "DATABASE_URL",
9
)

Integration capabilities by platform#

Use case recommendations#

Decision tree framework#

Small teams (under 10 developers)#

Recommended: GitHub Actions

• Rationale: Lowest operational overhead, excellent documentation
• Setup time: 15-30 minutes
• Monthly cost: $0-100 (free tier covers most usage)
• Best for: GitHub-hosted projects, standard web development

Alternative: GitLab Runners

• When to choose: Using GitLab as primary platform
• Setup time: 20-45 minutes
• Monthly cost: $0-50 (GitLab.com free tier)

Enterprise teams (100+ developers)#

Recommended: Jenkins Agents

• Rationale: Maximum customization, control, and flexibility
• Setup time: 4-8 hours initial setup
• Monthly cost: Infrastructure costs only
• Best for: Large organizations needing maximum control

Alternative: GitLab Runners

• When to choose: Kubernetes-heavy environments
• Kubernetes executor: Excellent for container-native workloads

Multi-cloud environments#

Recommended: Jenkins Agents

• Rationale: Platform-agnostic, maximum flexibility
• Considerations: Higher operational complexity
• Best for: Hybrid cloud, multiple cloud providers

Alternative: GitLab Runners

• When to choose: Kubernetes-heavy environments
• Kubernetes executor: Excellent for container-native workloads

Security-focused organizations#

Recommended: GitLab Runners

• Rationale: Strong built-in security with granular access control
• Security highlights: RBAC, container isolation, variable protection
• Best for: Financial services, healthcare, government

Alternative: GitHub Actions

• When to choose: GitHub-centric workflows with enterprise features
• Security highlights: OIDC, encrypted secrets, audit logs

Cost-sensitive projects#

Recommended: GitLab Runners

• Rationale: Most efficient resource utilization
• Cost factors: Only infrastructure costs, no per-minute charges
• Best for: Open source projects, startups

Alternative: Jenkins Agents

• When to choose: Have existing infrastructure
• Cost factors: Pure infrastructure costs, maximum control

High-performance build requirements#

Recommended: Bazel Remote Execution

• Rationale: Built for massive parallelization and performance
• Performance benefits: 5-10x faster builds for large codebases
• Best for: Large monorepos, C++/Java projects, Google-style development

Alternative: GitLab Runners (Kubernetes)

• When to choose: Need containerized high-performance builds
• Performance benefits: Efficient resource scheduling and scaling

Specialized workload guidance#

Machine Learning and AI:

1. GitLab Runners - Kubernetes executor with GPU support
2. Jenkins Agents - Flexible GPU and specialized hardware support
3. GitHub Actions - Good GPU runner options for GitHub projects

Mobile Development (iOS/Android):

1. GitHub Actions - Excellent macOS runner support
2. GitLab Runners - Good multi-platform support
3. Jenkins Agents - Maximum customization for mobile toolchains

Distributed Systems and Microservices:

1. Bazel Remote Execution - Excellent for large, interconnected codebases
2. GitLab Runners - Good container orchestration
3. Jenkins Agents - Pipeline orchestration capabilities

Architecture support#

ARM/x64 compatibility matrix#

Cross-compilation capabilities#

Bazel Remote Execution - Best for cross-compilation:

1
# Cross-platform build targets
2
platform_mappings = {
3
    "linux_x86_64": "@platforms//os:linux,cpu:x86_64",
4
    "linux_aarch64": "@platforms//os:linux,cpu:aarch64",
5
    "darwin_x86_64": "@platforms//os:osx,cpu:x86_64",
6
    "darwin_arm64": "@platforms//os:osx,cpu:aarch64",
7
    "windows_x86_64": "@platforms//os:windows,cpu:x86_64"
8
}

GitLab Runners - Good for container-based cross-compilation:

1
build_matrix:
2
  parallel:
3
    matrix:
4
      - ARCH: [amd64, arm64]
5
        OS: [linux, darwin, windows]
6
  image: multiarch/crossbuild

GitHub Actions - Matrix builds across platforms:

1
strategy:
2
  matrix:
3
    os: [ubuntu-latest, windows-latest, macos-latest]
4
    arch: [x64, arm64]

Migration guidance#

Platform migration strategies#

From GitHub Actions to GitLab Runners#

Migration timeline: 2-4 weeks Complexity: Medium

Key considerations:

• Workflow YAML syntax differences
• Secret management migration
• Runner registration setup
• CI/CD variable configuration

1
# GitHub Actions workflow
2
name: CI/CD Pipeline
3
on: [push, pull_request]
4
jobs:
5
  build:
6
    runs-on: self-hosted
7
    steps:
8
      - uses: actions/checkout@v4
9
      - run: npm test
10
11
# GitLab CI equivalent
12
build:
13
  tags:
14
    - self-hosted
15
  script:
16
    - npm test

From Jenkins to GitLab Runners#

Migration timeline: 4-8 weeks Complexity: High

Key considerations:

• Jenkinsfile to GitLab CI/CD YAML conversion
• Plugin functionality replacement
• Credential migration
• Build artifact handling

1
// Jenkins Pipeline
2
pipeline {
3
    agent { label 'linux' }
4
    stages {
5
        stage('Build') {
6
            steps {
7
                sh 'npm install && npm run build'
8
            }
9
        }
10
    }
11
}

1
# GitLab CI equivalent
2
build:
3
  stage: build
4
  tags:
5
    - linux
6
  script:
7
    - npm install && npm run build

Migration best practices#

1. Parallel Operation Phase (Week 1-2)

• Run both systems simultaneously
• Mirror critical workflows
• Validate output consistency
• Train team on new platform

2. Gradual Transition (Week 3-4)

• Migrate non-critical workflows first
• Update documentation and runbooks
• Establish monitoring and alerting
• Backup existing configurations

3. Full Cutover (Week 5-6)

• Migrate remaining workflows
• Decommission old infrastructure
• Update team processes
• Post-migration optimization

Hybrid strategies#

Multi-platform deployment patterns#

Repository-based distribution:

1
# .github/workflows/primary.yml (GitHub Actions)
2
name: Primary Build
3
on: [push, pull_request]
4
jobs:
5
  build:
6
    if: github.repository == 'org/main-repo'
7
    runs-on: self-hosted
8
9
# .gitlab-ci.yml (GitLab backup)
10
stages:
11
  - build
12
build:
13
  stage: build
14
  rules:
15
    - if: $CI_PIPELINE_SOURCE == "schedule"
16
  script:
17
    - npm run build

Workload-based distribution:

• GitHub Actions: Web applications, API services
• GitLab Runners: Container builds, Kubernetes deployments
• Jenkins Agents: Legacy applications, specialized builds
• Bazel RBE: Large monorepos, performance-critical builds

Geographic distribution:

• Primary region: GitHub Actions (US East)
• Secondary region: GitLab Runners (EU Central)
• Backup region: Jenkins Agents (Asia Pacific)

Avoiding vendor lock-in#

Standardization strategies:

1. Common configuration patterns - Use similar YAML structures
2. Shared scripts - Platform-agnostic build scripts
3. Container-based builds - Reduce platform dependencies
4. External orchestration - Use external tools for complex logic

Portable workflow patterns:

1
#!/bin/bash
2
# build.sh - Platform-agnostic build script
3
set -e
4
5
echo "🔨 Starting build process..."
6
7
# Install dependencies
8
npm ci
9
10
# Run tests
11
npm test
12
13
# Build application
14
npm run build
15
16
# Package artifacts
17
tar -czf dist.tar.gz dist/
18
19
echo "✅ Build completed successfully"

Total cost of ownership#

Licensing and infrastructure costs#

GitHub Actions#

Free tier: 2,000 minutes/month private repos, unlimited public Paid tiers: $0.008/minute Linux, $0.016/minute Windows, $0.064/minute macOS

Annual cost estimates:

• Small team (500 hours/month): $0-2,400
• Medium team (2,000 hours/month): $9,600-19,200
• Large team (5,000+ hours/month): $24,000-48,000

Additional costs:

• Larger runner sizes: 2x-4x base rates
• Storage: $0.25/GB per month
• Self-hosted infrastructure: Variable

GitLab Runners#

Free tier: 400 minutes/month private projects, unlimited self-hosted Paid tiers: GitLab Premium/Ultimate subscription

Annual cost estimates:

• Self-hosted only: Infrastructure costs only
• With GitLab subscription: $19-99/user/month
• GitLab.com CI minutes: $10/1,000 minutes

Infrastructure costs:

• Small deployment: $200-500/month
• Medium deployment: $1,000-3,000/month
• Large deployment: $5,000+/month

Jenkins Agents#

License: Open source (free) Commercial support: CloudBees ($10,000-50,000+/year)

Infrastructure costs:

• Jenkins controller: $200-1,000/month
• Agent infrastructure: $100-500/month per agent
• Management overhead: 0.5-2 FTE positions

Total annual costs:

• Small deployment: $5,000-15,000
• Medium deployment: $20,000-50,000
• Large deployment: $100,000+

Bazel Remote Execution#

License: Apache 2.0 (free) Commercial services: Google Cloud Build, BuildBarn

Infrastructure costs:

• Worker cluster: $500-5,000/month
• Cache storage: $100-1,000/month
• Network bandwidth: $50-500/month

Total annual costs:

• Small deployment: $8,000-25,000
• Medium deployment: $25,000-75,000
• Large deployment: $100,000+

Operational costs#

Management overhead by platform#

Hidden costs to consider#

Security and compliance:

• Audit requirements: $5,000-25,000/year
• Security scanning tools: $2,000-10,000/year
• Compliance certification: $10,000-50,000/year

Training and expertise:

• Initial training: $2,000-10,000 per team
• Ongoing education: $1,000-5,000/year per person
• Consultant costs: $1,500-3,000/day

Monitoring and observability:

• Monitoring tools: $1,000-5,000/month
• Log aggregation: $500-2,000/month
• Alerting systems: $200-1,000/month

Cost optimization strategies#

Right-sizing recommendations:

1. Monitor usage patterns - Scale based on actual demand
2. Use spot instances - 50-70% savings for non-critical workloads
3. Implement auto-scaling - Reduce idle resource costs
4. Optimize build times - Faster builds = lower costs
5. Share infrastructure - Multi-tenant runner deployments

Budget planning framework:

1
Total Monthly Cost = Infrastructure + Licensing + Operations + Hidden
2
3
Infrastructure = (Compute + Storage + Network) × Usage Factor
4
Licensing = Per-seat or per-minute charges
5
Operations = Personnel × Time × Hourly Rate
6
Hidden = Security + Training + Tools + Compliance

Conclusion#

Platform selection significantly impacts your DevOps success. Use this decision framework:

Start with your constraints:

1. Team size and expertise - Smaller teams benefit from managed solutions
2. Existing infrastructure - Leverage current investments when possible
3. Security requirements - Enterprise environments need robust security
4. Budget limitations - Balance functionality with cost constraints
5. Performance needs - High-performance workloads may justify complexity

Recommended quick-start approach:

1. GitHub Actions for most new teams (fastest time-to-value)
2. GitLab Runners for cost-conscious teams or Kubernetes environments
3. Jenkins Agents when maximum customization is required
4. Bazel RBE for large-scale, performance-critical builds

Platform evolution path: Most teams benefit from starting simple and evolving based on actual needs rather than anticipated complexity. You can always migrate later with the strategies outlined in this guide.

The key is matching your platform choice to your current reality while maintaining flexibility for future growth.