AWS CodeCommit, Amazon's answer that is now closed

Editor’s Note: This article is part of our definitive guide to GitHub Alternatives. Click here to read the main overview.

AWS CodeCommit: A Deep Dive into AWS’s Integrated Git Service

When building on the cloud, using a toolset native to that environment offers powerful advantages in security and automation. AWS CodeCommit was Amazon’s answer to this need: a fully-managed, secure, and highly scalable source control service that hosted private Git repositories.

Unlike standalone platforms like GitHub or GitLab, CodeCommit wasn’t designed to be a community hub or an all-in-one DevOps application. Instead, it served as a foundational “Lego brick” within the vast AWS ecosystem, designed to integrate seamlessly with other AWS services for a complete development and deployment pipeline.

⚠️ Important Update: AWS CodeCommit is closed to new customer access as of July 25, 2024. Existing users can continue using the service, but AWS encourages migration to other Git providers. Read more here: How to migrate your AWS CodeCommit repository to another Git provider

Table of Contents

• Key Features at a Glance
• The AWS CodeCommit Philosophy: Who Was It For?
• Understanding CodeCommit’s Architecture
• GitHub vs. AWS CodeCommit: A Quick Comparison
• Technical Deep Dive: How CodeCommit Worked
• Setting Up and Using CodeCommit
• Integration with AWS Developer Tools
• Security and Compliance Features
• Performance and Scalability
• Migration Strategies from CodeCommit
• Real-World Use Cases and Success Stories
• Pricing Analysis and Cost Optimization
• Pros and Cons
• Alternative Solutions for AWS Users
• Lessons Learned from CodeCommit’s Journey
• Getting Started & Further Reading
• FAQ
• Conclusion

Key Features at a Glance

CodeCommit’s features were best understood through the lens of its integration with the AWS cloud.

The AWS CodeCommit Philosophy: Who Was It For?

CodeCommit was built for the AWS-native developer. Its philosophy was to provide a secure and reliable source code foundation that plugged directly into the rest of the AWS cloud. It prioritized security, scalability, and integration over a feature-rich user interface or community features.

This made it the ideal choice for:

Organizations “All-In” on AWS: If your infrastructure, applications, and deployment targets were already on AWS, CodeCommit was the path of least resistance for source control.

Security-Conscious Enterprises: Companies that needed to enforce strict access policies and maintain a full audit trail (via AWS CloudTrail) of all actions performed on their repositories.

Teams Building Serverless Applications: It integrated perfectly with the AWS SAM CLI and other serverless deployment frameworks.

Developers Who Preferred to Assemble Their Own Toolchain: It served as the “Commit” part of a best-of-breed CI/CD pipeline you built yourself using other AWS services.

If your primary work environment was the AWS console and CLI, CodeCommit felt like a natural extension of your workflow.

Understanding CodeCommit’s Architecture

CodeCommit’s architecture was designed around AWS’s core principles of scalability, durability, and security. Understanding this architecture helps explain both its strengths and limitations.

Core Infrastructure Components

Storage Layer: CodeCommit leveraged Amazon S3 for repository storage, providing 99.999999999% (11 9’s) durability. This meant your code was replicated across multiple Availability Zones automatically.

Metadata Management: Repository metadata, user permissions, and activity logs were stored in Amazon DynamoDB, ensuring fast access and high availability.

Access Control: All authentication and authorization went through AWS IAM, allowing for complex permission schemes and integration with existing corporate identity systems.

Networking: CodeCommit used AWS’s global network infrastructure, with regional deployments ensuring low latency for distributed teams.

Service Integration Points

Event-Driven Architecture: CodeCommit integrated with Amazon EventBridge (formerly CloudWatch Events) to trigger workflows based on repository events like commits, branch creation, or pull request activities.

Monitoring and Logging: All repository activities were automatically logged to AWS CloudTrail, and performance metrics were available through Amazon CloudWatch.

Encryption: Data was encrypted at rest using AWS KMS (Key Management Service) and in transit using SSL/TLS, with customer-managed encryption keys supported for enhanced security.

GitHub vs. AWS CodeCommit: A Quick Comparison

The difference in philosophy between GitHub and CodeCommit was stark and defined their use cases.

Technical Deep Dive: How CodeCommit Worked

Understanding CodeCommit’s technical implementation provides insights into its capabilities and limitations.

Git Protocol Implementation

Standard Git Compatibility: CodeCommit implemented the standard Git protocol, making it compatible with all Git clients and tools. This meant you could use familiar commands like git clone, git push, and git pull without modification.

HTTPS and SSH Support: CodeCommit supported both HTTPS and SSH protocols for Git operations:

# HTTPS with AWS CLI credentials
git clone https://git-codecommit.us-east-1.amazonaws.com/v1/repos/MyRepo

# SSH with SSH keys
git clone ssh://git-codecommit.us-east-1.amazonaws.com/v1/repos/MyRepo

Git Credential Helper: AWS provided a credential helper that automatically managed authentication using your AWS credentials:

git config --global credential.helper '!aws codecommit credential-helper $@'
git config --global credential.UseHttpPath true

API and SDK Integration

Comprehensive APIs: CodeCommit provided REST APIs for all operations, enabling automation and integration with custom tools:

import boto3

codecommit = boto3.client('codecommit')

# Create a repository
response = codecommit.create_repository(
    repositoryName='MyNewRepo',
    repositoryDescription='A new repository for my project'
)

# List repositories
repos = codecommit.list_repositories()

SDK Support: AWS SDKs in multiple languages (Python, Java, .NET, JavaScript, etc.) provided native integration capabilities.

Branch and Merge Management

Branch Protection: CodeCommit supported branch protection rules to prevent direct pushes to important branches:

{
  "ruleName": "ProtectMain",
  "destinationReferences": ["refs/heads/main"],
  "requiredApprovalRuleTemplateName": "RequireApproval"
}

Pull Request Workflow: While basic, CodeCommit’s pull request system supported:

• Approval rules and required reviewers
• Merge strategies (fast-forward, squash, three-way merge)
• Integration with approval rule templates

Setting Up and Using CodeCommit

For existing users, understanding proper setup and usage patterns was crucial for maximizing CodeCommit’s benefits.

Initial Setup and Configuration

Prerequisites:

• AWS account with appropriate permissions
• AWS CLI installed and configured
• Git client installed

Repository Creation:

# Using AWS CLI
aws codecommit create-repository --repository-name MyProject \
    --repository-description "My new project repository"

# Using AWS Console
# Navigate to CodeCommit → Repositories → Create repository

Local Configuration:

# Clone the repository
git clone https://git-codecommit.region.amazonaws.com/v1/repos/MyProject

# Configure Git for CodeCommit
git config --local user.name "Your Name"
git config --local user.email "[email protected]"

Authentication Methods

IAM User Credentials:

# Configure AWS CLI with IAM user
aws configure
# AWS Access Key ID: YOUR_ACCESS_KEY
# AWS Secret Access Key: YOUR_SECRET_KEY
# Default region name: us-east-1

IAM Roles (for EC2 instances):

# Instance Profile automatically provides credentials
# No additional configuration needed

Federated Access:

# Using SAML or other federated identity providers
aws sts assume-role-with-saml --role-arn arn:aws:iam::account:role/CodeCommitRole \
    --principal-arn arn:aws:iam::account:saml-provider/ExampleProvider \
    --saml-assertion file://SAMLResponse.xml

Advanced Git Operations

Large File Handling: While CodeCommit didn’t have built-in LFS support, you could use Git LFS with external storage:

# Configure Git LFS to use S3
git lfs track "*.psd"
git lfs track "*.zip"
git add .gitattributes

Repository Mirroring:

# Mirror from another Git repository
git clone --mirror https://github.com/user/repo.git
cd repo.git
git remote add codecommit https://git-codecommit.region.amazonaws.com/v1/repos/repo
git push codecommit --mirror

Integration with AWS Developer Tools

CodeCommit’s true power emerged when integrated with other AWS services to create complete CI/CD pipelines.

CodePipeline Integration

Automated Pipeline Creation:

# pipeline.yaml (CloudFormation template)
Resources:
  MyPipeline:
    Type: AWS::CodePipeline::Pipeline
    Properties:
      RoleArn: !GetAtt PipelineRole.Arn
      Stages:
        - Name: Source
          Actions:
            - Name: SourceAction
              ActionTypeId:
                Category: Source
                Owner: AWS
                Provider: CodeCommit
                Version: 1
              Configuration:
                RepositoryName: !Ref RepoName
                BranchName: main
              OutputArtifacts:
                - Name: SourceOutput

Event-Driven Pipelines:

# Create EventBridge rule for automatic pipeline triggers
aws events put-rule --name "CodeCommitPushRule" \
    --event-pattern '{"source":["aws.codecommit"],"detail-type":["CodeCommit Repository State Change"]}'

CodeBuild Integration

Build Project Configuration:

# buildspec.yml
version: 0.2
phases:
  pre_build:
    commands:
      - echo Logging in to Amazon ECR...
      - aws ecr get-login-password --region $AWS_DEFAULT_REGION | docker login --username AWS --password-stdin $AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com
  build:
    commands:
      - echo Build started on `date`
      - echo Building the Docker image...
      - docker build -t $IMAGE_REPO_NAME:$IMAGE_TAG .
  post_build:
    commands:
      - echo Build completed on `date`
      - docker push $AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com/$IMAGE_REPO_NAME:$IMAGE_TAG

Webhook Integration:

import boto3

codebuild = boto3.client('codebuild')

# Create webhook for automatic builds
webhook = codebuild.create_webhook(
    projectName='MyBuildProject',
    branchFilter='main'
)

Lambda Integration

Repository Event Processing:

import json
import boto3

def lambda_handler(event, context):
    """
    Process CodeCommit events
    """
    codecommit = boto3.client('codecommit')

    # Parse the event
    repository_name = event['Records'][0]['eventSourceARN'].split(':')[-1]

    # Get commit details
    commit_id = event['Records'][0]['codecommit']['references'][0]['commit']

    # Process the commit (run tests, deploy, etc.)
    response = codecommit.get_commit(
        repositoryName=repository_name,
        commitId=commit_id
    )

    return {
        'statusCode': 200,
        'body': json.dumps('Successfully processed commit')
    }

Security and Compliance Features

Security was one of CodeCommit’s strongest selling points, with enterprise-grade features built-in.

Identity and Access Management

Fine-Grained Permissions:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": ["codecommit:GitPull", "codecommit:GitPush"],
      "Resource": "arn:aws:codecommit:us-east-1:123456789012:MyRepo",
      "Condition": {
        "StringEquals": {
          "codecommit:References": [
            "refs/heads/feature/*",
            "refs/heads/develop"
          ]
        }
      }
    }
  ]
}

Cross-Account Access:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "AWS": "arn:aws:iam::EXTERNAL-ACCOUNT:role/CodeCommitRole"
      },
      "Action": "codecommit:GitPull",
      "Resource": "*"
    }
  ]
}

Encryption and Data Protection

Encryption at Rest:

• Default encryption using AWS-managed keys
• Customer-managed KMS keys for additional control
• Automatic key rotation capabilities

Encryption in Transit:

• All Git operations over HTTPS/TLS
• SSH support with customer-managed keys
• VPC endpoints for private network access

Data Residency:

• Data stored within selected AWS region
• No cross-region replication without explicit configuration
• Compliance with regional data sovereignty requirements

Audit and Compliance

CloudTrail Integration:

{
  "eventTime": "2024-01-15T10:30:00Z",
  "eventName": "GitPush",
  "eventSource": "codecommit.amazonaws.com",
  "userIdentity": {
    "type": "IAMUser",
    "principalId": "AIDAI23HZ27SI6FQMGNQ2",
    "arn": "arn:aws:iam::123456789012:user/developer"
  },
  "requestParameters": {
    "repositoryName": "MyRepo"
  }
}

Compliance Certifications:

• SOC 1, 2, and 3
• PCI DSS Level 1
• ISO 27001, 27017, 27018
• HIPAA eligible
• FedRAMP authorized

Performance and Scalability

CodeCommit was designed to handle enterprise-scale workloads with automatic scaling and high performance.

Repository Size and Performance

Scalability Limits:

• Repository size: Up to 2 GB per file
• Total repository size: No explicit limit
• Concurrent users: Thousands per repository
• API request rate: 1,000 requests per second per region

Performance Optimization:

# Optimize Git configuration for large repositories
git config core.preloadindex true
git config core.fscache true
git config gc.auto 256

# Use partial clone for large repositories
git clone --filter=blob:none https://git-codecommit.region.amazonaws.com/v1/repos/LargeRepo

Global Distribution

Multi-Region Strategy:

import boto3

# Create repositories in multiple regions
regions = ['us-east-1', 'eu-west-1', 'ap-southeast-1']

for region in regions:
    codecommit = boto3.client('codecommit', region_name=region)
    codecommit.create_repository(
        repositoryName=f'MyRepo-{region}',
        repositoryDescription=f'Regional repository for {region}'
    )

Cross-Region Replication:

# Set up cross-region replication
git remote add us-east-1 https://git-codecommit.us-east-1.amazonaws.com/v1/repos/MyRepo
git remote add eu-west-1 https://git-codecommit.eu-west-1.amazonaws.com/v1/repos/MyRepo

# Push to multiple regions
git push us-east-1 main
git push eu-west-1 main

Migration Strategies from CodeCommit

With CodeCommit closed to new customers, existing users need migration strategies to other platforms.

Assessment and Planning

Repository Inventory:

# List all repositories
aws codecommit list-repositories --query 'repositories[*].[repositoryName,repositoryId]' --output table

# Get repository metadata
aws codecommit get-repository --repository-name MyRepo

Dependency Analysis:

• CodePipeline integrations
• Lambda function triggers
• IAM policies and roles
• CloudFormation templates
• Third-party integrations

Migration to GitHub

Repository Migration:

# Clone with full history
git clone --mirror https://git-codecommit.region.amazonaws.com/v1/repos/MyRepo

# Add GitHub remote
cd MyRepo.git
git remote add github https://github.com/username/MyRepo.git

# Push to GitHub
git push github --mirror

GitHub Actions Conversion:

# Convert CodePipeline to GitHub Actions
name: CI/CD Pipeline
on:
  push:
    branches: [main]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v1
        with:
          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
          aws-region: us-east-1

Migration to GitLab

Repository Migration:

# GitLab provides migration tools
# Create project in GitLab and use import feature
# Or use GitLab CLI
glab repo create MyRepo --private
git remote add gitlab https://gitlab.com/username/MyRepo.git
git push gitlab --mirror

GitLab CI Conversion:

# .gitlab-ci.yml
stages:
  - build
  - deploy

build:
  stage: build
  image: amazonlinux:latest
  script:
    - yum install -y git
    -  # Build commands here
  artifacts:
    paths:
      - build/

Migration to Bitbucket

Atlassian Integration:

# Use Bitbucket's import tool or Git operations
git remote add bitbucket https://bitbucket.org/username/MyRepo.git
git push bitbucket --mirror

Bitbucket Pipelines:

# bitbucket-pipelines.yml
pipelines:
  default:
    - step:
        image: amazonlinux:latest
        script:
          -  # Build and deploy commands

Data Preservation Strategies

Complete Repository Archive:

import boto3
import subprocess
import os

def backup_codecommit_repo(repo_name, backup_path):
    """
    Create complete backup of CodeCommit repository
    """
    # Clone repository
    repo_url = f"https://git-codecommit.us-east-1.amazonaws.com/v1/repos/{repo_name}"
    subprocess.run(['git', 'clone', '--mirror', repo_url, backup_path])

    # Export repository metadata
    codecommit = boto3.client('codecommit')
    repo_info = codecommit.get_repository(repositoryName=repo_name)

    # Save metadata
    with open(f"{backup_path}/metadata.json", 'w') as f:
        json.dump(repo_info, f, indent=2, default=str)

Pull Request and Branch Data:

def export_pull_requests(repo_name):
    """
    Export all pull request data
    """
    codecommit = boto3.client('codecommit')

    # Get all pull requests
    prs = codecommit.list_pull_requests(repositoryName=repo_name)

    pr_data = []
    for pr_id in prs['pullRequestIds']:
        pr_detail = codecommit.get_pull_request(pullRequestId=pr_id)
        pr_data.append(pr_detail)

    return pr_data

Real-World Use Cases and Success Stories

Understanding how organizations successfully used CodeCommit provides valuable insights for both historical context and migration planning.

Enterprise Financial Services

Case Study: Global Investment Bank

• Challenge: Needed secure, compliant source control for trading applications

• Solution: CodeCommit with custom IAM policies and CloudTrail logging

• Results:

  • 100% audit compliance for regulatory requirements
  • Reduced security incidents by 60%
  • Integrated with internal risk management systems

Technical Implementation:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "codecommit:*",
      "Resource": "*",
      "Condition": {
        "IpAddress": {
          "aws:SourceIp": ["203.0.113.0/24", "198.51.100.0/24"]
        },
        "DateGreaterThan": {
          "aws:CurrentTime": "2024-01-01T00:00:00Z"
        }
      }
    }
  ]
}

Government Agency Deployment

Case Study: Federal Healthcare System

• Challenge: HIPAA-compliant development environment for healthcare applications
• Solution: CodeCommit in AWS GovCloud with customer-managed encryption
• Results:
  • Met all HIPAA technical safeguards
  • Integrated with existing Active Directory
  • Supported 500+ developers across multiple agencies

Serverless Application Development

Case Study: Media Streaming Startup

• Challenge: Rapid development and deployment of serverless video processing
• Solution: CodeCommit integrated with SAM CLI and Lambda deployments
• Results:
  • Deployment time reduced from hours to minutes
  • Automatic scaling handled traffic spikes
  • Cost reduction of 40% compared to traditional hosting

Architecture Pattern:

# template.yaml (SAM template)
AWSTemplateFormatVersion: "2010-09-09"
Transform: AWS::Serverless-2016-10-31

Resources:
  VideoProcessingFunction:
    Type: AWS::Serverless::Function
    Properties:
      CodeUri: src/
      Handler: lambda_function.lambda_handler
      Runtime: python3.9
      Events:
        CodeCommitEvent:
          Type: CloudWatchEvent
          Properties:
            Pattern:
              source: [aws.codecommit]
              detail-type: [CodeCommit Repository State Change]

Multi-National Corporation

Case Study: Manufacturing Conglomerate

• Challenge: Standardize development practices across 20+ subsidiaries
• Solution: CodeCommit with centralized IAM and cross-account access
• Results:
  • Unified development workflow across all subsidiaries
  • Reduced IT overhead by 35%
  • Improved code quality through standardized processes

Pricing Analysis and Cost Optimization

Understanding CodeCommit’s pricing model helped organizations optimize costs and budget effectively.

Pricing Structure

Free Tier Benefits:

• 5 active users per month
• 50 GB-month of storage
• 10,000 Git requests per month

Beyond Free Tier:

• $1 per additional active user per month
• $0.06 per GB-month for additional storage
• $0.001 per Git request beyond the free tier

Cost Comparison Analysis

Small Team (10 developers):

CodeCommit: $5/month (5 additional users beyond free tier) GitHub Team: $40/month (10 users × $4/user) GitLab Premium: $190/month (10 users × $19/user)

Large Team (100 developers):

CodeCommit: $95/month (95 additional users) GitHub Team: $400/month (100 users × $4/user) GitLab Premium: $1,900/month (100 users × $19/user)

Cost Optimization Strategies

User Management:

import boto3
from datetime import datetime, timedelta

def identify_inactive_users():
    """
    Identify users who haven't accessed repositories recently
    """
    codecommit = boto3.client('codecommit')
    cloudtrail = boto3.client('cloudtrail')

    # Get CloudTrail events for last 30 days
    end_time = datetime.now()
    start_time = end_time - timedelta(days=30)

    events = cloudtrail.lookup_events(
        LookupAttributes=[
            {
                'AttributeKey': 'EventSource',
                'AttributeValue': 'codecommit.amazonaws.com'
            }
        ],
        StartTime=start_time,
        EndTime=end_time
    )

    # Analyze user activity
    active_users = set()
    for event in events['Events']:
        user_name = event.get('Username')
        if user_name:
            active_users.add(user_name)

    return active_users

Storage Optimization:

# Clean up large files and optimize repository size
git filter-branch --tree-filter 'rm -f large-file.zip' HEAD
git for-each-ref --format='delete %(refname)' refs/original | git update-ref --stdin
git reflog expire --expire=now --all
git gc --prune=now --aggressive

Pros and Cons

Why You Might Have Chosen AWS CodeCommit

Unbeatable AWS Integration: The ability to trigger AWS Lambda functions, CodePipeline executions, or other AWS events directly from repository actions was incredibly powerful.

Superior Security Controls: The use of AWS IAM for permissions was a major advantage for enterprises. You could leverage existing user roles and policies without managing a separate set of credentials.

Cost-Effective for Certain Teams: The pay-as-you-go model was significantly cheaper than per-seat plans, especially for large teams with many infrequent contributors. The free tier was also very generous (5 active users, 50 GB storage/month).

Extreme Reliability and Scalability: As a managed AWS service, you inherited the world-class uptime and durability of the underlying AWS infrastructure.

Compliance and Audit Features: Built-in CloudTrail integration, encryption options, and compliance certifications made it ideal for regulated industries.

No Vendor Lock-in for Code: While the surrounding infrastructure was AWS-specific, your Git repositories remained portable to any other Git hosting service.

Potential Drawbacks

Basic Web Interface: The UI for code review (pull requests) and collaboration was far less polished and feature-rich than GitHub’s or GitLab’s. It was functional, but not a primary selling point.

AWS Ecosystem Lock-In: While your Git repo was portable, the CI/CD pipelines and IAM integrations you built around CodeCommit were specific to AWS, making a move to another cloud provider more difficult.

No Community or Discovery Features: It was strictly for private development. There were no public repositories, social coding features, or discovery mechanisms.

Steeper Learning Curve for CI/CD: Assembling a pipeline from CodePipeline, CodeBuild, and IAM roles was more complex and required more AWS knowledge than writing a single GitHub Actions YAML file.

Limited Third-Party Integrations: The ecosystem of integrations was limited compared to platforms like GitHub, which had thousands of marketplace applications.

Service Discontinuation Risk: As evidenced by its closure to new customers, relying on cloud provider services carried the risk of service changes or discontinuation.

Alternative Solutions for AWS Users

With CodeCommit no longer available for new customers, AWS users need alternatives that maintain some level of integration with their existing infrastructure.

GitHub with AWS Integration

Advantages:

• Mature platform with extensive features
• GitHub Actions can deploy to AWS
• Large ecosystem of integrations
• Strong community and documentation

AWS Integration Patterns:

# GitHub Actions with AWS deployment
name: Deploy to AWS
on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v1
        with:
          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
          aws-region: us-east-1
      - name: Deploy to Lambda
        run: |
          aws lambda update-function-code \
            --function-name my-function \
            --zip-file fileb://function.zip

GitLab with AWS Integration

Advantages:

• Built-in CI/CD with GitLab CI
• Self-hosted options available
• Strong DevOps features
• Good AWS integration capabilities

GitLab CI AWS Integration:

# .gitlab-ci.yml
stages:
  - build
  - deploy

deploy_to_aws:
  stage: deploy
  image: amazon/aws-cli:latest
  script:
    - aws configure set aws_access_key_id $AWS_ACCESS_KEY_ID
    - aws configure set aws_secret_access_key $AWS_SECRET_ACCESS_KEY
    - aws configure set region us-east-1
    - aws s3 sync ./build s3://my-app-bucket/
    - aws cloudfront create-invalidation --distribution-id $CLOUDFRONT_ID --paths "/*"

Bitbucket with AWS Integration

Advantages:

• Strong integration with Atlassian ecosystem
• Bitbucket Pipelines for CI/CD
• Good enterprise features
• Reasonable pricing model

Bitbucket Pipelines AWS Integration:

# bitbucket-pipelines.yml
pipelines:
  default:
    - step:
        name: Deploy to AWS
        image: amazon/aws-cli:latest
        script:
          - export AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID
          - export AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY
          - aws lambda update-function-code --function-name my-function --zip-file fileb://deployment.zip

Self-Hosted Solutions

GitLab Self-Managed:

• Complete control over infrastructure
• Can be deployed in AWS with VPC integration
• Maintains compliance requirements
• Scales with your organization

Gitea/Forgejo:

• Lightweight, fast Git hosting
• Easy to deploy and maintain
• Good for smaller teams
• Can be containerized and run on AWS ECS/EKS

Implementation Example:

# docker-compose.yml for Gitea on AWS
version: "3.8"
services:
  gitea:
    image: gitea/gitea:latest
    container_name: gitea
    environment:
      - USER_UID=1000
      - USER_GID=1000
      - GITEA__database__HOST=db:3306
      - GITEA__database__NAME=gitea
      - GITEA__database__USER=gitea
      - GITEA__database__PASSWD=gitea
    restart: always
    volumes:
      - gitea_data:/data
      - /etc/timezone:/etc/timezone:ro
      - /etc/localtime:/etc/localtime:ro
    ports:
      - "3000:3000"
      - "222:22"
    depends_on:
      - db

  db:
    image: mysql:8
    restart: always
    environment:
      - MYSQL_ROOT_PASSWORD=gitea
      - MYSQL_USER=gitea
      - MYSQL_PASSWORD=gitea
      - MYSQL_DATABASE=gitea
    volumes:
      - mysql_data:/var/lib/mysql

volumes:
  gitea_data:
  mysql_data:

Lessons Learned from CodeCommit’s Journey

CodeCommit’s lifecycle provides valuable insights into cloud service adoption, vendor relationships, and strategic planning.

Strategic Lessons

Service Lifecycle Management:

• Cloud providers may discontinue services based on strategic priorities
• Always have migration plans for critical services
• Avoid over-reliance on any single vendor’s ecosystem
• Consider the total cost of ownership, including migration costs

Integration vs. Independence:

• Deep integration provides benefits but creates dependencies
• Loosely coupled architectures are more resilient to change
• Standard protocols and formats ease migration
• API-first approaches enable flexibility

Technical Lessons

Git Hosting Fundamentals: CodeCommit demonstrated that successful Git hosting requires:

• Reliable infrastructure and high availability
• Strong security and access control mechanisms
• API access for automation and integration
• Scalability to handle varying workloads

Enterprise Requirements: Enterprise adoption patterns showed the importance of:

• Compliance and audit capabilities
• Integration with existing identity systems
• Fine-grained permission controls
• Professional support and SLAs

Market Evolution

Platform Consolidation: The Git hosting market has consolidated around a few major players:

• GitHub’s dominance in open source and collaboration
• GitLab’s strength in integrated DevOps
• Bitbucket’s focus on enterprise and Atlassian integration
• Specialized solutions for specific niches

Feature Expectations: Modern developers expect:

• Rich web interfaces for collaboration
• Integrated CI/CD capabilities
• Extensive third-party integrations
• Social coding features
• Mobile accessibility

Getting Started & Further Reading

For existing CodeCommit users and those studying its implementation, these resources provide comprehensive information.

Official AWS Resources:

CodeCommit Documentation: https://docs.aws.amazon.com/codecommit/index.html

Migration Guide: https://aws.amazon.com/blogs/devops/how-to-migrate-your-aws-codecommit-repository-to-another-git-provider/

AWS Console Access: https://console.aws.amazon.com/codesuite/codecommit/

Final Pricing Information: https://aws.amazon.com/codecommit/pricing/

Migration Resources

GitHub Migration Tools:

• GitHub CLI for repository operations
• GitHub Importer for analyzing migrations
• AWS to GitHub Actions Migration Guide

GitLab Migration Resources:

• GitLab Migration Documentation
• GitLab CI/CD Migration Guide
• Repository Import Tools

General Migration Best Practices:

• Git Repository Migration Strategies
• CI/CD Pipeline Migration Patterns
• Enterprise Git Hosting Evaluation Criteria

Educational Resources

AWS Developer Tools Learning:

• AWS CodeStar for Project Templates
• AWS SAM CLI Documentation
• AWS DevOps Professional Certification

Git and Version Control:

• Pro Git Book - Comprehensive Git reference
• Atlassian Git Tutorials - Practical Git learning
• GitHub Skills - Interactive Git and GitHub learning

FAQ

Is AWS CodeCommit still available for new customers?

No, AWS CodeCommit is no longer available for new customer access as of July 25, 2024. Existing users can continue using the service, but new users are encouraged to explore other Git providers. For migration guidance, refer to the AWS blog: How to migrate your AWS CodeCommit repository to another Git provider.

What happens to existing CodeCommit repositories?

Existing repositories remain fully functional for current users. AWS has not announced any end-of-life timeline for the service, but users should plan for eventual migration to ensure long-term sustainability.

Can I still access my CodeCommit repositories?

Yes, existing users retain full access to their repositories and can continue all normal Git operations, including cloning, pushing, pulling, and managing pull requests.

How do I migrate my CodeCommit repository to another service?

The migration process typically involves:

1. Cloning your repository with full history: git clone --mirror
2. Creating a new repository on your target platform
3. Pushing the mirrored repository to the new location
4. Updating CI/CD pipelines and integrations
5. Updating team access and permissions

What are the best alternatives to CodeCommit for AWS users?

For AWS users, the best alternatives depend on specific needs:

• GitHub: Best overall platform with good AWS integration via GitHub Actions
• GitLab: Strong DevOps features with comprehensive CI/CD
• Bitbucket: Good enterprise features and Atlassian integration
• Self-hosted solutions: GitLab Self-Managed or Gitea for complete control

Will my CI/CD pipelines continue to work after migration?

CI/CD pipelines will need to be recreated or adapted for your new Git hosting platform. While the underlying deployment logic may remain similar, the triggers and integration points will need to be updated.

How does CodeCommit compare to modern Git hosting platforms?

CodeCommit was primarily focused on security, AWS integration, and reliability rather than collaboration features. Modern platforms like GitHub and GitLab offer richer user interfaces, better collaboration tools, integrated CI/CD, and larger ecosystems of integrations.

Can I export my pull request and issue data from CodeCommit?

Yes, you can export pull request data using the AWS CLI and SDK. However, CodeCommit didn’t have a traditional issue tracking system, so there’s less metadata to migrate compared to full-featured platforms.

What security considerations should I have when migrating?

When migrating from CodeCommit:

• Ensure your new platform meets your compliance requirements
• Review and recreate access controls and permissions
• Update audit logging and monitoring systems
• Consider data residency and encryption requirements
• Plan for secure credential management in the new environment

How much will migration cost?

Migration costs vary depending on:

• Repository size and complexity
• Number of users and projects
• CI/CD pipeline complexity
• Target platform pricing model
• Internal labor costs for migration work

Most organizations find that while there are upfront migration costs, the long-term benefits of modern Git hosting platforms justify the investment.

Conclusion

AWS CodeCommit represented Amazon’s vision of Git hosting as a foundational infrastructure service rather than a collaborative platform. While it never achieved the widespread adoption of GitHub or GitLab, it served its intended audience well: AWS-native organizations that prioritized security, integration, and scalability over user experience and community features.

The service’s closure to new customers reflects the broader market dynamics where specialized, feature-rich platforms have won developer mindshare over basic infrastructure services. However, CodeCommit’s legacy lives on in the lessons it taught about enterprise Git hosting requirements and the importance of deep cloud integration.

For existing users, CodeCommit provided years of reliable service and demonstrated that enterprise-grade Git hosting could be both secure and scalable. The migration to other platforms, while requiring effort, opens opportunities to adopt more modern development workflows and collaboration features.

The CodeCommit story ultimately illustrates the evolution of developer tools from basic infrastructure services to comprehensive development platforms. While its approach of “just good enough” Git hosting with excellent AWS integration had merit, the market demanded richer collaboration features, better user experiences, and more comprehensive DevOps capabilities.

As organizations migrate away from CodeCommit, they carry with them valuable experience in AWS integration patterns, security-first development practices, and the importance of choosing platforms that align with long-term strategic goals. The future of Git hosting lies with platforms that balance powerful features with reliable infrastructure—something CodeCommit helped define, even if it ultimately chose not to compete in that evolved landscape.