GitHub Actions vs Google Cloud Build

Overview

GitHub Actions vs Cloud Build at a glance

A quick comparison across the dimensions that affect cost and developer experience.

Pricing

GitHub Actions vs Cloud Build pricing comparison

Both platforms charge per build-minute, but the rate structures and free tiers differ. GitHub Actions includes 2,000 free minutes/month on Free, 3,000 on Team/Pro, and 50,000 on Enterprise. Overage on the standard Linux 2-core runner is $0.006/min. Windows costs $0.010/min and macOS costs $0.062/min. GitHub rounds each job up to the nearest whole minute.

Cloud Build gives every billing account 2,500 free build-minutes/month on the e2-standard-2 machine type in the default pool. After that, pricing varies by machine type and region. The e2-standard-2 (2 vCPU, 8 GB) costs approximately $0.006/min in US regions. Higher-CPU machines like e2-highcpu-8 and e2-highcpu-32 scale linearly. Cloud Build does not offer macOS or Windows runners; it is Linux-only.

On the standard 2-vCPU Linux machine type, the per-minute rate is effectively the same: $0.006/min. At 50 builds/day averaging 8 minutes each, GitHub Actions costs about $35/mo in overage, Cloud Build about $38/mo. The $3 gap comes from GitHub's larger included minutes on Team (3,000 vs 2,500).

One caveat: Cloud Build's pricing is pure compute cost, with no per-seat component for CI itself. GitHub's Team plan adds $4/user/month on top of CI overage. For a team of 10, that is $40/mo before you use a single CI minute. On the other hand, Cloud Build requires a GCP project, and you will pay for Cloud Storage (build logs), Artifact Registry (container images at $0.10/GB/mo over 0.5 GB), and network egress. These surrounding costs add up depending on your image sizes and registry traffic.

Configuration

GitHub Actions YAML vs cloudbuild.yaml

Both platforms use YAML, but the pipeline model is fundamentally different. GitHub Actions uses a workflow → jobs → steps hierarchy, where each job runs on its own VM and jobs execute in parallel by default. Cloud Build uses a flat list of steps that run sequentially on a single machine by default. You can make steps run in parallel with waitFor, but there is no concept of separate jobs running on separate machines within a single build.

Here is the same pipeline (lint, test, build a container, push to a registry) on each platform:

name: CI
on:
  push:
    branches: [main]
  pull_request:

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: npm run lint

  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: npm test

  build-push:
    needs: [lint, test]
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: docker/build-push-action@v5
        with:
          push: true
          tags: ghcr.io/org/app:latest

steps:
  - id: lint
    name: 'node:20'
    entrypoint: npm
    args: ['run', 'lint']
    waitFor: ['-']

  - id: test
    name: 'node:20'
    entrypoint: npm
    args: ['run', 'test']
    waitFor: ['-']

  - id: build
    name: 'gcr.io/cloud-builders/docker'
    args:
      - 'build'
      - '-t'
      - 'us-docker.pkg.dev/$PROJECT_ID/app/app:latest'
      - '.'
    waitFor: ['lint', 'test']

images:
  - 'us-docker.pkg.dev/$PROJECT_ID/app/app:latest'

options:
  machineType: E2_STANDARD_2

The structural difference is significant. In GitHub Actions, lint and test run on separate VMs in parallel by default, then build-push waits for both via needs. In Cloud Build, all steps share the same machine. Parallel execution requires explicit waitFor: ['-'] to tell a step to start immediately rather than waiting for the previous step to finish. The images: key at the bottom tells Cloud Build to push the image to Artifact Registry after the build completes.

Another key difference: GitHub Actions uses marketplace actions (uses: docker/build-push-action@v5) to abstract complex operations. Cloud Build steps are bare container invocations. Each step specifies a container image (name:) and the command to run inside it. Google provides pre-built cloud builders for common tools (Docker, gcloud, kubectl, gsutil), but anything not covered requires you to bring your own container image.

Runners

Runners and machine types compared

GitHub calls them runners. Cloud Build calls them machine types. Both platforms offer managed compute with multiple sizing options, but the range and flexibility differ.

For Linux workloads, per-minute pricing is comparable. Cloud Build's e2-highcpu machines offer more vCPU per dollar than GitHub's larger runners because they have lower RAM ratios (1 GB/vCPU vs GitHub's 4 GB/vCPU). If your builds are CPU-bound but not memory-heavy, Cloud Build's high-CPU types can be cost-effective.

The biggest gap is platform coverage. Cloud Build is Linux-only. If you build iOS apps, Electron desktop apps, or anything requiring macOS or Windows, Cloud Build is not an option for those workloads. GitHub Actions covers all three operating systems with managed runners, plus ARM64 Linux at $0.005/min.

Cloud Build's advantage is private pools: fully managed workers with VPC peering that can access private GKE clusters, internal databases, and other resources behind your firewall. GitHub Actions requires you to operate your own self-hosted runners for private network access. Cloud Build's private pools give you the network access without the infrastructure management.

Caching

How caching works on each platform

Caching is one of the sharpest differences between these two platforms. GitHub Actions has a first-class dependency cache. Cloud Build has Docker layer caching for container builds, but no native mechanism for caching npm, pip, or other dependency managers.

steps:
  - uses: actions/checkout@v4
  - uses: actions/cache@v4
    with:
      path: ~/.npm
      key: npm-${{ hashFiles('**/package-lock.json') }}
      restore-keys: npm-
  - run: npm ci

# No native dependency cache.
# Docker layer cache via Kaniko:
steps:
  - name: 'gcr.io/kaniko-project/executor:latest'
    args:
      - '--destination=us-docker.pkg.dev/$PROJECT_ID/app/app:latest'
      - '--cache=true'
      - '--cache-ttl=72h'

GitHub's actions/cache handles arbitrary file paths keyed on a hash of your lockfile. The cache lives in Azure Blob Storage, is scoped to the repository, and entries expire after 7 days of no access. The 10 GB per-repository limit can be exceeded on a pay-as-you-go basis ($0.07/GiB/month).

Cloud Build has no equivalent. For Docker image builds, you can use Kaniko's cache flag to store intermediate layers in Artifact Registry, which can speed up rebuilds when only the final layers change. For non-Docker dependency caching, you need to build a custom solution using Cloud Storage: upload a tarball of node_modules or .pip at the end of a build, download it at the start of the next one. This works but adds build steps and complexity that GitHub Actions handles with a single action.

Triggers

Build triggers and event handling

GitHub Actions triggers are defined inline in the workflow YAML and cover a wide range of GitHub events: pushes, pull requests, releases, issue comments, scheduled cron, manual dispatch, and more. Path filters and branch filters are part of the trigger definition. Cloud Build triggers are configured in the GCP Console (or via Terraform/gcloud) as separate objects that point to a cloudbuild.yaml file.

on:
  push:
    branches: [main]
    paths-ignore:
      - 'docs/**'
  pull_request:
    branches: [main]
  schedule:
    - cron: '0 6 * * 1'
  workflow_dispatch:

# Create a push trigger via gcloud:
gcloud builds triggers create github \
  --repo-owner=my-org \
  --repo-name=my-app \
  --branch-pattern="^main$" \
  --build-config=cloudbuild.yaml \
  --included-files="src/**"

# PR trigger requires separate config
# Scheduled triggers use Cloud Scheduler
# Manual triggers via Console or API

GitHub Actions' advantage is that triggers live with the code. When you rename a branch or add a path filter, you update the workflow file in the same commit. Cloud Build triggers are external resources managed through the GCP Console, gcloud CLI, or Terraform. This means trigger configuration is decoupled from the build configuration, which can make it harder to track changes and keep things in sync.

Cloud Build supports triggers for GitHub repos, Bitbucket Cloud, and Bitbucket Server. It also supports Pub/Sub and webhook triggers for event-driven builds from external systems. GitHub Actions triggers are GitHub-only, though workflow_dispatch can be called via API from any system. Cloud Build has built-in manual approval on triggers, gated via IAM roles, for production deployment gates.

Ecosystem

GCP integration vs marketplace actions

Cloud Build's core value proposition is native GCP integration. Builds run with automatic GCP credentials (via the build service account), so deploying to Cloud Run, GKE, or App Engine requires no credential setup. GitHub Actions can authenticate to GCP via OIDC (using google-github-actions/auth), but it requires explicit configuration.

steps:
  - uses: actions/checkout@v4
  # OIDC auth to GCP
  - uses: google-github-actions/auth@v2
    with:
      workload_identity_provider: projects/123/locations/...
      service_account: deploy@project.iam
  - uses: google-github-actions/deploy-cloudrun@v2
    with:
      service: my-app
      image: us-docker.pkg.dev/project/app/app

steps:
  # No auth step needed.
  # Build service account has IAM access.
  - name: 'gcr.io/cloud-builders/gcloud'
    args:
      - 'run'
      - 'deploy'
      - 'my-app'
      - '--image=us-docker.pkg.dev/$PROJECT_ID/app/app'
      - '--region=us-central1'

The Cloud Build version has no authentication boilerplate. The build service account inherits IAM permissions automatically. On GitHub Actions, you need to set up Workload Identity Federation (a one-time setup per GCP project) and add the auth step to every workflow that touches GCP.

For multi-cloud teams, the tradeoff reverses. GitHub Actions' 21,000+ marketplace actions cover AWS, Azure, GCP, and dozens of SaaS tools. Cloud Build has no equivalent marketplace. If you deploy to AWS and GCP from the same repo, GitHub Actions can handle both in one workflow. Cloud Build would require separate AWS credential management using Secret Manager and custom build steps.

Decision framework

When to choose GitHub Actions

• You need macOS or Windows builds. Cloud Build is Linux-only. If you build iOS apps, .NET projects, or Electron desktop apps, GitHub Actions is the only option between these two.

• You deploy to multiple clouds. GitHub Actions can deploy to AWS, Azure, and GCP from one workflow using OIDC and marketplace actions. Cloud Build is designed around GCP. Deploying to AWS from Cloud Build requires manual credential management.

• You want triggers-as-code. GitHub Actions triggers live in the workflow file alongside the build logic. Changes are version-controlled in the same commit. Cloud Build triggers are external resources managed through the Console or Terraform, adding a layer of indirection.

• You rely on dependency caching. GitHub's actions/cache is a mature, built-in solution for npm, pip, Maven, and other package managers. Cloud Build has no native equivalent; you have to build custom caching with Cloud Storage.

• You run open-source projects. GitHub Actions is free for public repos with no minute limits. Cloud Build has no equivalent open-source program; all builds consume quota.

Decision framework

When to choose Google Cloud Build

• You deploy exclusively to GCP. Cloud Build's zero-config GCP authentication, native Artifact Registry push, and built-in gcloud builder make GKE and Cloud Run deployments trivial. No OIDC federation setup, no marketplace actions to maintain.

• You need private network access for builds. Cloud Build's private pools provide VPC peering, private IP ranges, and access to internal resources without you managing any runner infrastructure. On GitHub Actions, equivalent network access requires operating your own self-hosted runners.

• Your pipeline is primarily container builds. Cloud Build was designed from the start to build and push container images. The images: key, Kaniko integration, and Artifact Registry are first-class. If your CI pipeline is "build image, push image, deploy image," Cloud Build does this with less configuration than GitHub Actions.

• You want to avoid per-seat CI costs. Cloud Build charges only for build-minutes. There is no per-seat plan fee for CI itself. For larger teams where GitHub Team ($4/user/mo) or Enterprise ($21/user/mo) plan costs are significant, Cloud Build eliminates this line item (though GCP project costs still apply).

• Your source code is not on GitHub. Cloud Build supports triggers from GitHub, Bitbucket Cloud, and Bitbucket Server. It also supports Pub/Sub and webhook triggers for custom integrations. If your repositories live on Bitbucket, Cloud Build can connect directly.

Migration

What to know before switching

Moving between these platforms is not a direct YAML translation. The pipeline models are structurally different. Here are the primary friction points:

• Jobs become steps. GitHub Actions jobs run on separate VMs. Cloud Build steps run on the same machine. A GitHub workflow with 5 parallel jobs needs to be restructured as 5 parallel steps (via waitFor) on a single, larger machine type, or split into separate Cloud Build trigger configurations.

• Marketplace actions have no Cloud Build equivalent. Every uses: line in your GitHub workflow needs to be replaced with either a pre-built cloud builder, a custom container image, or inline script. Some common actions (like actions/setup-node) translate to using the official node: Docker image directly. Others (like dorny/paths-filter) have no Cloud Build counterpart.

• Secrets management differs. GitHub uses repository, environment, and organization-level secrets accessed via ${{ secrets.NAME }}. Cloud Build uses Google Secret Manager, accessed via availableSecrets in the config or the secretEnv field on steps. You will need to migrate every secret to Secret Manager and update the access pattern.

• Concurrency and cancellation work differently. GitHub Actions' concurrency: key with cancel-in-progress has no direct Cloud Build equivalent. Cloud Build queues builds up to the concurrency limit and processes them FIFO. There is no built-in mechanism to cancel superseded builds on the same branch.

• Many teams use both. A common pattern is to keep GitHub Actions for general CI (lint, test, caching) and trigger Cloud Build only for GCP deployments. GitHub Actions can call gcloud builds submit as a step, giving you the best of both ecosystems.

Google provides a trigger setup guide for GitHub repositories, and there are community-maintained examples of calling Cloud Build from GitHub Actions workflows. The Cloud Build config file schema documents all available fields and options.