Moving your source control from SaaS Git to self-hosted GitLab CE on AWS

As organizations scale and their development workflows mature, many reach a point where the constraints of SaaS Git hosting begin to outweigh the conveniences. While SaaS platforms offer ease of use and reduced operational overhead, they often come with limitations on customization, compliance requirements, specific integration needs, or unpredictable per-seat pricing models that escalate quickly. For engineering, DevOps, and security teams, regaining full control over their source code management and CI/CD pipelines becomes a strategic imperative.

This often leads to the decision to migrate to a self-hosted solution. GitLab Community Edition, a powerful open-source platform, combined with the flexibility and scalability of AWS, presents a compelling alternative. However, a successful migration requires meticulous planning and execution to ensure data integrity, minimize downtime, and seamlessly transition developer workflows.

Why consider migrating to self-hosted GitLab CE on AWS?

The primary drivers for moving from a SaaS Git provider to a self-hosted GitLab CE instance on AWS typically revolve around control, cost, and compliance. Organizations seeking deeper customization, needing to meet stringent regulatory requirements, or aiming for more predictable infrastructure costs often find self-hosting to be the optimal path.

Table 1. Decision factors comparing SaaS Git hosting and self-hosted GitLab CE on AWS.

By choosing self-hosted GitLab CE on AWS, teams leverage the robust features of GitLab for source code management, CI/CD, and more, while benefiting from AWS's secure, scalable, and reliable infrastructure. This allows for tailored environments that precisely match an organization's unique technical and business needs.

Understanding the migration process

A migration from a SaaS Git provider to self-hosted GitLab CE on AWS is a multi-phase project. Each phase demands attention to detail to ensure a smooth transition and avoid operational disruptions.

Phase 1: planning and assessment

Before any technical work begins, a thorough assessment and planning phase are crucial. This involves understanding your current landscape and defining the scope of the migration.

• Inventory existing assets: Document all repositories, users, groups, CI/CD pipelines, protected branches, environment variables, LFS objects, and any other configurations or integrations.
• Define migration scope: Decide if you will migrate all data at once, or in stages. Consider migrating only active projects versus historical archives.
• Identify key stakeholders: Engage development, DevOps, security, and project management teams.
• Set success criteria: What does a successful migration look like? Minimal downtime, all critical projects migrated, CI/CD pipelines functional.
• Plan for downtime: Determine an acceptable migration window and communicate it clearly to all affected teams.
• Choose your target environment: Confirm self-hosted GitLab CE on AWS is the right fit. This includes considering your team's operational capabilities for managing the instance post-migration.

Phase 2: setting up the target GitLab CE instance

Once your planning is complete, the next step is to provision and configure your new GitLab CE instance on AWS. This is where a streamlined deployment solution can significantly reduce setup time.

For instance, the Techforce Services Inc GitLab Community Edition AMI for AWS offers a production-ready baseline. This AMI is built on Ubuntu 24.04 LTS and comes pre-wired with essential components like an NGINX reverse proxy for secure web access, OpenSSH for Git operations, and a UFW firewall for initial security hardening. This accelerates the deployment process, allowing your team to focus on the migration itself, rather than spending days on initial server setup and configuration.

When launching your instance, consider the recommended specifications. For most teams, a t3.large instance (8 GB RAM minimum) provides a good balance of performance and cost. Larger teams or those with high CI/CD activity may require more powerful instances like m5 series. Ensure your EBS volumes are adequately sized for your repository data and logs.

Initial configuration steps include:

• DNS setup: Point your chosen domain name to the EC2 instance's IP address or an associated Elastic IP.
• SSL/TLS configuration: Secure your GitLab instance with an SSL certificate.
• Backup strategy: Implement a robust backup and disaster recovery plan. While a detailed strategy is beyond the scope here, ensure you have automated backups of the GitLab data directory and PostgreSQL database.
• User management strategy: Decide on internal GitLab users, LDAP/Active Directory integration, or SAML SSO, and configure accordingly.

Phase 3: data migration

This is the core of the migration, involving the actual transfer of your Git repositories and associated data.

• Project export and import: GitLab provides robust project export/import functionality. This is often the most straightforward method for migrating individual projects, including repositories, issues, merge requests, and project settings. You'll export projects from your SaaS provider (if supported, or use Git mirror/clone for just repos) and import them into your new GitLab CE instance.
• User mapping: Create users on the new GitLab instance that correspond to your existing users. Ensure user IDs or usernames are mapped correctly to preserve commit history authorship and access permissions.
• CI/CD pipeline migration: This is often the most complex part.
  • Recreate runners: Deploy and register new GitLab Runners on AWS that are configured to communicate with your self-hosted GitLab CE instance. Consider different runner types (EC2 instances, Docker, Kubernetes) based on your workload.
  • Migrate CI/CD variables: Manually re-enter or script the migration of project and group-level CI/CD variables.
  • Review pipeline logic: Test existing .gitlab-ci.yml files to ensure compatibility with the new environment, especially if specific tools or services were only available in the SaaS environment.
• Large File Storage (LFS): If you use Git LFS, ensure your LFS objects are also migrated and correctly linked.

Phase 4: post-migration and cutover

With data transferred, the final phase involves thorough testing and switching over to the new system.

• Comprehensive testing:
  • Verify repository access and cloning for all projects.
  • Run key CI/CD pipelines to ensure they execute successfully.
  • Test user authentication, permissions, and group memberships.
  • Check integrations with other tools (e.g., Jira, Slack).
• DNS cutover: Once confident in the new setup, update your DNS records to point to the new GitLab CE instance.
• Developer communication: Inform all developers about the switch, any new URLs, and provide clear instructions for updating their Git remotes.
• Decommission old system: After a stabilization period and confirming all data is successfully on the new instance, safely decommission the old SaaS Git hosting to avoid confusion and ongoing costs.

Table 2. Key phases and tasks for GitLab CE on AWS migration.

Key considerations for self-hosted GitLab CE on AWS

Migrating to self-hosted GitLab CE on AWS is not just a one-time effort, it's a shift in operational responsibility. Understanding these ongoing considerations is vital for long-term success.

Instance sizing and performance

Choosing the right EC2 instance type and EBS volume configuration is critical for performance. GitLab is a resource-intensive application, particularly under heavy CI/CD loads. While a t3.large (8 GB RAM minimum) is a good starting point, adjust based on your team size and usage patterns.

Table 3. Recommended instance sizing for self-hosted GitLab CE on AWS.

CI/CD runner management

Self-hosting offers unparalleled flexibility for CI/CD runners. You can deploy runners directly on EC2 instances, within ECS/EKS clusters, or even on-premises. This allows for specific hardware requirements, network access, or custom build environments. Plan for runner scalability, potentially using AWS Auto Scaling Groups to spin up and down runners based on demand.

Operational overhead

With self-hosting, your team assumes responsibility for system administration tasks, including:

• Operating system updates: Regularly apply security patches and updates to the Ubuntu 24.04 LTS base OS.
• GitLab application updates: Stay current with GitLab CE releases to benefit from new features and security fixes.
• Monitoring: Implement robust monitoring for instance health, disk space, and application performance.
• Backups and disaster recovery: Maintain a consistent backup schedule and test your recovery procedures regularly to ensure business continuity.

Security and access control

AWS provides a strong foundation for securing your GitLab instance. Leverage Security Groups for network ingress/egress control, IAM for access to AWS resources, and the pre-configured UFW firewall on the AMI for host-level protection. Regularly review GitLab's built-in security features, such as protected branches, audit logs, and access permissions.

Cost management

While self-hosting offers cost predictability, it requires active management. Your AWS bill will reflect EC2 instance hours, EBS storage, data transfer, and any other AWS services consumed (e.g., S3 for backups, Route 53 for DNS). The Techforce Services Inc AMI has a transparent pricing model: a $0.10/hour AMI fee is added to standard AWS EC2 instance costs, with no minimum commitment. This allows for flexible scaling without unexpected per-user charges as your team grows.

Common migration pitfalls and mitigations

Even with careful planning, migrations can encounter unexpected challenges. Being aware of common pitfalls can help you prepare for and mitigate them.

Table 4. Common migration pitfalls and mitigation strategies.

Migrating from a SaaS Git hosting provider to self-hosted GitLab Community Edition on AWS is a significant undertaking that offers substantial rewards in terms of control, customization, and cost predictability. By following a structured approach, leveraging tools that simplify deployment like the Techforce Services Inc GitLab CE AMI, and understanding the ongoing operational responsibilities, engineering and DevOps teams can successfully transition to a more powerful and flexible source control and CI/CD platform.