Which CI/CD Tool Wins for Small Teams? Jenkins vs GitLab CI vs GitHub Actions

CI/CD Tool Selection for Small Teams: Jenkins vs GitLab CI vs GitHub Actions Deep Comparison

Introduction

"Which CI/CD tool should we use?" remains a pressing question for many teams in 2025. As an architect who has used Jenkins 1.x to 2.x, GitLab CI, and GitHub Actions extensively, I have seen many teams suffer from choosing the wrong tool: some get trapped by Jenkins' plugin hell, others are frustrated by GitLab CI's resource consumption, and some are shocked by GitHub Actions' minute‑based billing. This article does not merely list feature tables; it analyzes the real pain points of small‑to‑medium teams and provides a deep comparison of the three major CI/CD tools to help you make the right decision in 30 minutes.

Technical Background: Evolution and Current State of CI/CD Tools

What is CI/CD and Why Is It Essential?

CI/CD (Continuous Integration / Continuous Delivery) has moved from an "advanced practice" to a "basic requirement". It solves core problems:

Continuous Integration (CI): automatic compile, test, and check after code submission; early detection of integration issues; keep the main branch always releasable.

Continuous Delivery/Deployment (CD): automated deployment processes, reduce manual operations; deliver new features quickly, frequently, and reliably; enable one‑click rollback and lower release risk.

2025 data shows CI/CD teams deploy 46 times more frequently than traditional teams, reduce failure recovery time by 96×, and cut change failure rates by 5×. For small teams, CI/CD is a survival necessity, not a luxury.

Three Generations of CI/CD Tools

First Generation (2011‑2015): Jenkins Era

Representatives: Jenkins, Travis CI, TeamCity

Features: powerful, complex configuration, plugin ecosystem

Typical architecture: Master‑Slave, Web UI configuration

Second Generation (2015‑2020): Pipeline as Code

Representatives: GitLab CI, Drone CI, CircleCI

Features: configuration as code, deep Git integration, containerized execution

Typical architecture: YAML configuration, Docker Runner

Third Generation (2019‑present): Cloud‑Native and Intelligent

Representatives: GitHub Actions, Tekton, Argo Workflows

Features: Marketplace ecosystem, Serverless execution, AI assistance

Typical architecture: event‑driven, reusable Actions, managed services

Market Share of the Three Tools (2024‑2025)

Jenkins: ~30% (declining)

GitLab CI: ~25% (steady growth)

GitHub Actions: ~35% (rapid growth)

Other tools (CircleCI, Drone, Azure Pipelines, etc.): ~10%

Specific Needs of Small Teams

Quick onboarding – no dedicated DevOps, developers must learn fast.

Cost‑controlled – both labor and operational costs matter.

Simple maintenance – minimal time spent on CI/CD system upkeep.

Good‑enough features – enterprise‑grade capabilities are not required.

Team collaboration – configuration should be easy to share.

Core Content: In‑Depth Comparison of the Three Tools

1. Installation, Deployment, and Maintenance Cost

Jenkins: Heavyweight, Requires Dedicated Maintenance

Installation & Deployment :

# Docker (simplest)
 docker run -d -p 8080:8080 -p 50000:50000 -v jenkins_home:/var/jenkins_home jenkins/jenkins:lts

# Traditional (production‑recommended)
# 1. Install Java
 sudo apt install openjdk-11-jdk
# 2. Add Jenkins repo and install
 wget -q -O - https://pkg.jenkins.io/debian/jenkins.io.key | sudo apt-key add -
 sudo sh -c 'echo deb http://pkg.jenkins.io/debian-stable binary/ > /etc/apt/sources.list.d/jenkins.list'
 sudo apt update && sudo apt install jenkins
# 3. Start Jenkins
 sudo systemctl start jenkins

Initial configuration takes 10‑20 minutes (install plugins, create admin account, set URL, etc.). From installation to usable state takes at least 1‑2 hours.

Ongoing maintenance (excerpt from a real case): a 50‑person team spends 20‑30 hours per month on plugin updates, version upgrades, disk cleanup, and backup restoration.

Maintenance Item

Frequency

Time

Difficulty

Plugin updates

Weekly

30 min

★★★

Jenkins version upgrade

Quarterly

2‑4 h

★★★★

Disk cleanup

Monthly

1 h

★★

Agent node maintenance

On demand

1‑2 h

★★★

Backup & restore

Weekly

1 h

★★★

Real‑world case : a 50‑person team with one Jenkins master (4 CPU, 8 GB) and three agents (2 CPU, 4 GB each) spent ~5 hours per week on maintenance; after a year, Jenkins itself caused more failures than the application.

GitLab CI: Medium‑weight, Requires Runner Management

Prerequisite : an existing GitLab instance (self‑hosted or gitlab.com).

# Install GitLab Runner (on CI server)
 curl -L https://packages.gitlab.com/install/repositories/runner/gitlab-runner/script.deb.sh | sudo bash
 sudo apt-get install gitlab-runner

# Register Runner
 sudo gitlab-runner register
 # Provide URL, token, description, tags, executor (docker recommended)

# Example config (/etc/gitlab-runner/config.toml)
 concurrent = 4
 check_interval = 0
 [[runners]]
   name = "my-runner"
   url = "https://gitlab.com/"
   token = "xxxxx"
   executor = "docker"
   [runners.docker]
     image = "alpine:latest"
     privileged = false
     volumes = ["/cache", "/var/run/docker.sock:/var/run/docker.sock"]

From installation to usable state: 30‑60 minutes if GitLab already exists.

Ongoing maintenance (typical for a 30‑person team):

Maintenance Item

Frequency

Time

Difficulty

Runner updates

Monthly

10 min

★

Runner status monitoring

Daily

5 min

★★

Docker image cleanup

Weekly

30 min

★★

Config file management

On demand

30 min

★★

Real case: a 30‑person team with two shared runners (4 CPU, 8 GB) and two dedicated runners (8 CPU, 16 GB) handled 300 builds per day with queue time < 5 min.

GitHub Actions: Zero Maintenance, Ready‑to‑Use

Installation is essentially creating a .github/workflows/ci.yml file in the repository. Example:

# .github/workflows/ci.yml
name: CI/CD Pipeline
on:
  push:
    branches: [main, develop]
  pull_request:
    branches: [main]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-node@v3
        with:
          node-version: 18
          cache: npm
      - run: npm ci
      - run: npm test
      - uses: codecov/codecov-action@v3
  deploy-staging:
    needs: test
    if: github.ref == 'refs/heads/develop'
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: docker/login-action@v2
        with:
          username: ${{ secrets.DOCKER_HUB_USERNAME }}
          password: ${{ secrets.DOCKER_HUB_TOKEN }}
      - uses: docker/build-push-action@v4
        with:
          push: true
          tags: myapp:staging
      - uses: appleboy/ssh-action@master
        with:
          host: ${{ secrets.STAGING_HOST }}
          username: ubuntu
          key: ${{ secrets.SSH_KEY }}
          script: |
            docker pull myapp:staging
            docker-compose up -d
  deploy-production:
    needs: test
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    environment:
      name: production
      url: https://myapp.com
    steps:
      # similar to staging, omitted for brevity

From creation to usable state: 5‑10 minutes.

Ongoing maintenance : essentially none. Only monitor minute usage to avoid over‑billing.

2. Configuration Ease and Usability

Jenkins: Web UI vs Jenkinsfile

Web UI : visual, but not versionable; difficult for team collaboration.

Jenkinsfile (Groovy DSL) : powerful but steep learning curve; complex debugging; versionable but syntax heavy.

pipeline {
    agent any
    environment {
        DOCKER_IMAGE = "myapp"
        DOCKER_TAG = "${env.BUILD_NUMBER}"
    }
    stages {
        stage('Checkout') {
            steps { git branch: 'main', url: 'https://github.com/user/repo.git' }
        }
        stage('Build') {
            steps { sh 'npm install'; sh 'npm run build' }
        }
        stage('Test') {
            steps { sh 'npm test' }
            post { always { junit 'test-results/**/*.xml' } }
        }
        stage('Docker Build') {
            steps { script { docker.build("${DOCKER_IMAGE}:${DOCKER_TAG}") } }
        }
        stage('Deploy') {
            when { branch 'main' }
            steps { sh '''
                docker stop myapp || true
                docker rm myapp || true
                docker run -d --name myapp -p 8080:8080 ${DOCKER_IMAGE}:${DOCKER_TAG}
            ''' }
        }
    }
    post { failure { mail to: '[email protected]', subject: "Build Failed: ${env.JOB_NAME} #${env.BUILD_NUMBER}", body: "Check console at ${env.BUILD_URL}" } }
}

GitLab CI: Pure YAML, Clear and Extensible

# .gitlab-ci.yml
stages:
  - build
  - test
  - deploy
variables:
  DOCKER_IMAGE: myapp
  DOCKER_TAG: $CI_COMMIT_SHORT_SHA

build:
  stage: build
  image: maven:3.8-openjdk-17
  script:
    - mvn clean package -DskipTests
  artifacts:
    paths:
      - target/*.jar
    expire_in: 1 hour

test:
  stage: test
  image: maven:3.8-openjdk-17
  script:
    - mvn test
  artifacts:
    reports:
      junit: target/surefire-reports/TEST-*.xml

docker:build:
  stage: docker
  image: docker:latest
  services:
    - docker:dind
  script:
    - docker build -t $DOCKER_IMAGE:$DOCKER_TAG .
    - docker push $DOCKER_IMAGE:$DOCKER_TAG
  only:
    - main

deploy:production:
  stage: deploy
  script:
    - kubectl set image deployment/myapp myapp=$DOCKER_IMAGE:$DOCKER_TAG
  environment:
    name: production
  only:
    - main
  when: manual

GitHub Actions: YAML + Marketplace, Most User‑Friendly

# .github/workflows/ci.yml
name: CI/CD
on:
  push:
    branches: [main, develop]
  pull_request:
    branches: [main]
jobs:
  build-and-test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-node@v3
        with:
          node-version: 18
          cache: npm
      - run: npm ci
      - run: npm test
      - uses: codecov/codecov-action@v3
  docker:
    needs: build-and-test
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: docker/login-action@v2
        with:
          username: ${{ secrets.DOCKER_USERNAME }}
          password: ${{ secrets.DOCKER_PASSWORD }}
      - uses: docker/build-push-action@v4
        with:
          context: .
          push: true
          tags: |
            ${{ env.DOCKER_IMAGE }}:${{ github.sha }}
            ${{ env.DOCKER_IMAGE }}:latest
  deploy:
    needs: docker
    runs-on: ubuntu-latest
    environment:
      name: production
      url: https://myapp.com
    steps:
      - uses: appleboy/ssh-action@master
        with:
          host: ${{ secrets.SERVER_HOST }}
          username: ${{ secrets.SERVER_USER }}
          key: ${{ secrets.SSH_PRIVATE_KEY }}
          script: |
            docker pull ${{ env.DOCKER_IMAGE }}:${{ github.sha }}
            docker stop myapp || true
            docker rm myapp || true
            docker run -d --name myapp -p 8080:8080 ${{ env.DOCKER_IMAGE }}:${{ github.sha }}
      - uses: 8398a7/action-slack@v3
        with:
          status: ${{ job.status }}
          text: 'Deployment to production completed!'
          webhook_url: ${{ secrets.SLACK_WEBHOOK }}
        if: always()

3. Feature Completeness and Extensibility

Jenkins: Most Features, Largest Plugin Ecosystem

Supports all major SCMs, triggers, distributed builds, fine‑grained permissions, audit logs.

1800+ plugins (Git, Maven, Docker, SonarQube, Slack, etc.).

Pros: extremely flexible, can handle any workflow.

Cons: plugin quality varies, version conflicts, configuration scattered.

GitLab CI: Full‑Feature, Deep GitLab Integration

Native integration with GitLab MR, Issues, Environments, Review Apps.

Built‑in Docker registry, Container Scanning, SAST/DAST (Enterprise).

Pros: unified UI, powerful pipelines, good security features.

Cons: tied to GitLab; self‑hosted runners need management.

GitHub Actions: Marketplace‑Driven, Rapidly Growing

Over 8000 Marketplace Actions, reusable workflows, composite actions.

Built‑in caching, artifact handling, secret management, Dependabot, CodeQL.

Pros: extremely easy to start, huge community, free for open‑source.

Cons: strong lock‑in to GitHub, third‑party Action security risks.

4. Performance and Concurrency

Jenkins Performance

Single master can manage ~100 jobs and 50 agents; beyond that the master becomes a bottleneck.

Typical hardware: 4 CPU 8 GB for small, 8 CPU 16 GB for medium.

Concurrency controlled by executor count per agent; 100 concurrent builds are feasible with enough agents.

GitLab CI Performance

Shared Runner (Docker executor) 4 CPU 8 GB can run 4‑6 concurrent jobs.

10 runners can support a 50‑person team comfortably.

GitHub Actions Performance

Hosted runners: 2 CPU 7 GB (Linux/Windows), 3 CPU 14 GB (macOS).

Free tier: 2000 minutes/month; paid tiers increase concurrency.

Cold start is fastest (pre‑warmed environment).

5. Total Cost of Ownership (TCO) Comparison (10‑person Team, First Year)

Cost Item

Jenkins

GitLab CI (self‑hosted)

GitLab CI (hosted free)

GitHub Actions (free)

GitHub Actions (Team)

Infrastructure

6 k

15.6 k

7.2 k

0

3.2 k

Maintenance Labor

60 k

20 k

20 k

1 k

1 k

Training

30 k

10 k

10 k

5 k

5 k

Total

96 k

46 k

37 k

6 k

9 k

Conclusion: for small teams, GitHub Actions has the lowest cost, followed by GitLab CI; Jenkins is the most expensive mainly due to labor.

6. Security and Compliance

Jenkins Security

Strengths: matrix‑based permissions, audit‑trail plugin, credentials plugin, LDAP/AD/SAML integration.

Weaknesses: frequent plugin vulnerabilities, default insecure configuration, Groovy scripts can execute arbitrary code.

// Security hardening suggestions
// 1. Enable CSRF protection
// 2. Configure a strict authorization strategy
// 3. Regularly update Jenkins and plugins
// 4. Store secrets in Credentials, never hard‑code
// 5. Restrict script permissions via Script Security plugin

GitLab CI Security

Masked and protected CI/CD variables.

Protected runners run only on protected branches/tags.

Full RBAC integrated with GitLab permissions.

Audit logs, built‑in SAST/DAST/Container Scanning (Enterprise).

# Example of protected variable
variables:
  DATABASE_PASSWORD:
    value: "secret"
    masked: true
    protected: true

GitHub Actions Security

Secrets management at repository, organization, and environment levels.

Environment protection rules (approval, wait time, branch restrictions).

Free CodeQL code scanning, Dependabot updates.

OIDC support for short‑lived cloud credentials.

# Deploy job with OIDC to AWS
jobs:
  deploy:
    runs-on: ubuntu-latest
    environment:
      name: production
    permissions:
      id-token: write
      contents: read
    steps:
      - uses: aws-actions/configure-aws-credentials@v2
        with:
          role-to-assume: arn:aws:iam::123456789:role/GitHubActionsRole
          aws-region: us-east-1
      - name: Deploy
        run: |
          aws s3 sync ./dist s3://my-bucket

Security comparison table (summary):

Security Feature

Jenkins

GitLab CI

GitHub Actions

Permission Management

★★★★

★★★★★

★★★★

Credential Management

★★★★

★★★★★

★★★★★

Audit Logs

⭐⭐⭐ (plugin)

★★★★★

★★★★

Code Scanning

⭐⭐⭐ (plugin)

★★★★★ (Enterprise)

★★★★★ (free)

Vulnerability Risk

High (plugins)

Low

Medium (third‑party actions)

Compliance Support

★★★★

★★★★★

★★★★

Practical Cases: Three Real Teams' Selection Stories

Case 1: Startup Chooses GitHub Actions, Two Years Pain‑Free

Company: 12 people, Node.js + React, code hosted on GitHub.

Requirements: Fast (CI/CD ready in 1 week), Cheap (<10 k/year), Simple (developers can manage themselves).

Evaluation: Jenkins (3 days setup) rejected; GitLab CI (needs GitLab instance) rejected; GitHub Actions tried.

Implementation: 2‑hour setup of a workflow file (see code block above).

2‑year results: zero cost (free tier), <5 h total maintenance, zero CI/CD failures, high developer satisfaction.

Case 2: Mid‑Size Company Migrates from Jenkins to GitLab CI

Company: 80 people, Java Spring Boot + Vue, originally using Jenkins for 5 years.

Problems: maintenance difficulty, plugin hell, configuration chaos, high DevOps workload.

Decision: keep GitLab for code, adopt GitLab CI.

Migrate plan: 1‑month setup, 2‑3 pilot projects, 4‑6 months full migration, then decommission Jenkins.

Before/After comparison (key metrics): CI/CD failures reduced from 2‑3/month to <1/quarter; maintenance effort from 20 h/month to 5 h/month; average build time 12 min → 8 min; annual cost 80 k → 30 k.

Case 3: Financial Enterprise Sticks with Jenkins

Company: 500 people, 100+ micro‑services, strict compliance (Regulatory, Tier‑3, PCI‑DSS).

Reasons to stay with Jenkins:

Compliance: audit‑trail plugin satisfies regulator audits.

Complex build requirements across Java, .NET, Python.

Heavy custom plugins (20+) integrate with internal approval system.

Existing investment: 200+ person‑days of custom development, skilled DevOps staff.

Network isolation: cannot use SaaS CI/CD.

Risk‑averse philosophy: "If it isn’t broken, don’t fix it".

Solutions: standardised shared pipeline library, automated weekly cleanup scripts (see code block above), regular security hardening.

Conclusion: Jenkins remains the "ancestral system" but works well; migration cost outweighs benefits.

Best Practices: How to Make the Right Choice

Decision Matrix – Five Key Questions

Where is your code hosted? GitHub → GitHub Actions; GitLab → GitLab CI; Others → Jenkins or GitLab CI.

Team size and skill? <20 people → GitHub Actions; 20‑100 people → GitLab CI or GitHub Actions; >100 people with DevOps → Jenkins or GitLab CI.

Budget? <5 万 ¥/year → GitHub Free or self‑hosted GitLab CI; 5‑20 万 ¥ → paid GitHub or GitLab; >20 万 ¥ → any.

Technology stack complexity? Single language → any; multi‑language (common) → GitHub Actions or GitLab CI; legacy/heterogeneous (e.g., .NET Framework) → Jenkins.

Compliance requirements? None → any; full audit & RBAC → GitLab CI or Jenkins; strict financial/government → Jenkins (enterprise plugins).

Recommended Decision Tree

Where is your code hosted?
├─ GitHub
│   ├─ Team <20 → **GitHub Actions**
│   ├─ 20‑50 → **GitHub Actions** (primary) or GitLab CI
│   └─ >50, migration cost considered → **GitHub Actions** (low migration) or Jenkins (full features)
├─ GitLab
│   ├─ Team <50 → **GitLab CI** (first choice)
│   ├─ 50‑100 → **GitLab CI** (primary) or Jenkins (if needs complex customisation)
│   └─ >100 → **GitLab CI** (recommended) or Jenkins (existing investment)
└─ Other (Bitbucket, self‑hosted SVN)
    ├─ Sufficient budget, complex stack → **Jenkins**
    ├─ Willing to migrate to GitLab → **GitLab CI**
    └─ Willing to migrate to GitHub → **GitHub Actions**

Scenario‑Based Recommendations

Startup (10‑30 people) : GitHub Actions (95%) or GitLab CI (5%). Fast, cheap, zero maintenance.

Growth stage (30‑100 people) : GitLab CI (60%) or GitHub Actions (30%) or Jenkins (10%). Need richer features, still manageable maintenance.

Mature enterprise (100‑500 people) : Jenkins (50%) or GitLab CI (40%) or hybrid (10%). Complex pipelines, dedicated DevOps.

Large enterprise / finance / government (>500) : Jenkins (70%) or GitLab CI Enterprise (30%). Strict compliance, network isolation.

Open‑source project : GitHub Actions (90%) or GitLab CI (10%). Community familiarity, generous free tier.

Common Pitfalls and How to Avoid Them

Pitfall 1: "We need the newest technology" – Choosing a tool just because it’s trendy leads to cost overruns (e.g., Windows runners on GitHub Actions are expensive).

Pitfall 2: "Jenkins is old, we must switch" – Migration should have clear ROI; otherwise you waste time and reduce release frequency.

Pitfall 3: "GitHub Actions is free, so it’s cheapest" – Minute consumption can explode; calculate expected usage.

Pitfall 4: "We need the most powerful tool" – Small teams should avoid Jenkins unless they truly need its extensibility.

Pitfall 5: "GitLab CI needs self‑hosted runners, too hard" – Runner setup is quick; maintenance is minimal compared to Jenkins.

Migration Strategies

From Jenkins to GitLab CI / GitHub Actions

Assess all existing jobs, estimate migration effort.

Run a proof‑of‑concept with 2‑3 projects.

Prepare migration guides and train the team.

Migrate in batches, keep Jenkins running for fallback.

After successful migration, decommission Jenkins after a monitoring period.

Tools: GitLab CI provides a Jenkins Converter; GitHub Actions offers an Importer.

From GitLab CI / GitHub Actions to Jenkins (rare)

Only when requirements exceed SaaS capabilities or massive customisation is needed.

Perform a cost‑benefit analysis; migration risk is high.

Summary and Outlook

Core conclusion : Use GitHub Actions if code is on GitHub, GitLab CI if on GitLab, Jenkins for complex, compliance‑heavy environments.

Tool positioning : GitHub Actions – simplest; GitLab CI – balanced; Jenkins – most powerful.

2025 trends : SaaS CI/CD growth, AI‑assisted pipelines, stronger security scanning, GitOps mainstream, cloud‑native CI/CD (Tekton, Argo) emerging.

Final advice for decision makers :

Avoid over‑engineering; pick the simplest tool that meets needs.

Calculate total cost of ownership (license + labor).

Prioritise team happiness; CI/CD should be invisible.

Iterate gradually; start small, evolve as requirements grow.

Base decisions on data (POC results, actual minute usage, cost).

Personal insight : No tool is universally best; the right tool is the one you barely notice because it works flawlessly.