Building a resilient disaster recovery strategy for self-hosted GitLab CE on AWS

Imagine logging in one morning to find your primary GitLab instance unresponsive. Your development teams are stalled, unable to push code, review merge requests, or trigger CI/CD pipelines. This isn't just an inconvenience, it's a direct hit to productivity and potentially revenue. For organizations leveraging self-hosted GitLab Community Edition on AWS, a robust disaster recovery (DR) strategy is not a luxury, but a fundamental requirement for business continuity. While GitLab CE provides the flexibility of full control over your source code and CI/CD infrastructure, that control comes with the responsibility of ensuring its resilience.

This guide will walk you through the essential components of building a comprehensive disaster recovery strategy for your self-hosted GitLab CE instance on AWS. We'll cover understanding GitLab's architecture, implementing reliable backup mechanisms, leveraging AWS services for offsite storage and automation, and designing a practical recovery plan to minimize your Recovery Time Objective (RTO) and Recovery Point Objective (RPO).

Understanding GitLab CE's architecture for disaster recovery

Before designing a DR plan, it's crucial to understand what components make up a GitLab CE installation and what data needs to be protected. A standard Omnibus GitLab installation, which our Techforce Global GitLab CE AMI for AWS provides as its application layer, bundles several services into a single package. The key components to consider for backup and recovery are:

• Git repositories: The core of GitLab, storing all your project code and version history.
• PostgreSQL database: Stores all GitLab metadata, including users, projects, issues, merge requests, CI/CD pipeline definitions, and more.
• Configuration files: Specifically /etc/gitlab/gitlab.rb and /etc/gitlab/gitlab-secrets.json, which contain critical settings and encryption keys.
• Uploads and LFS objects: User-uploaded files, avatars, and Large File Storage (LFS) objects.
• CI/CD job artifacts: Output from your CI/CD pipelines.
• Container registry images: If you're using GitLab's built-in container registry.

Each of these components holds vital information. Losing any one of them can compromise the integrity or functionality of your GitLab instance. While the base operating system (Ubuntu 24.04 LTS) and the GitLab CE application itself can be easily redeployed, the unique data and configurations are irreplaceable.

Table 1. GitLab CE components and their backup relevance.

Implementing robust backups on AWS

GitLab provides a built-in Rake task for creating backups, which captures most of the critical data. However, for a production-grade DR strategy, simply running this task isn't enough. You need to automate it, store backups offsite, and secure them.

Automating GitLab backups

The primary tool for GitLab backup is the gitlab-rake gitlab:backup:create command. This command generates a tar archive containing all necessary data, excluding repositories by default (they are included if GITLAB_BACKUP_UPLOAD_ENABLED is not set). For a full backup, you'll need to ensure repositories are included, or perform separate Git repository backups if you have specific needs.

A common approach is to schedule this task using a cron job. For example, to run a daily backup at 2 AM:

The CRON=1 flag prevents interactive prompts, making it suitable for automation. Ensure your backup script also handles pruning old backups to manage storage costs.

Offsite backup storage with AWS S3

Storing backups on the same instance as your GitLab installation defeats the purpose of disaster recovery. If the instance fails, you lose both your application and its backups. AWS Simple Storage Service (S3) is an ideal choice for offsite backup storage due to its high durability, availability, and cost-effectiveness.

You can configure GitLab to upload backups directly to S3 by editing /etc/gitlab/gitlab.rb:

Security Best Practice: Do not embed AWS credentials directly in gitlab.rb for production environments. Instead, assign an IAM role to your EC2 instance with permissions to write to the S3 bucket. GitLab will automatically pick up credentials from the instance profile.

Consider S3 storage classes like S3 Standard-IA (Infrequent Access) or S3 Glacier Flexible Retrieval for older backups that you need to retain for compliance but access rarely, optimizing costs.

Table 2. Key AWS services for GitLab disaster recovery.

Developing a disaster recovery plan on AWS

A DR plan isn't just about backups, it's about the entire process of restoring service. Your plan should define your Recovery Point Objective (RPO), the maximum acceptable amount of data loss, and your Recovery Time Objective (RTO), the maximum acceptable downtime.

Recovery options and considerations

1. Restore to a new EC2 instance in the same region: This is the most common and straightforward DR scenario. You launch a new EC2 instance, install GitLab CE, and restore your latest backup. When using the Techforce Global GitLab CE AMI for AWS, this process is streamlined. You simply launch a new t3.large instance (or larger, ensuring at least 8 GB RAM) from the AMI, which provides Ubuntu 24.04 LTS with GitLab CE and pre-wired components (NGINX, OpenSSH, UFW firewall) ready for your data. This significantly reduces the setup time compared to a manual installation.
2. Restore to a new EC2 instance in a different region: For regional disasters, you'll need cross-region backups. S3 bucket replication can automatically copy your backups to another AWS region, providing geographical redundancy. The restoration process is similar to option 1, but involves retrieving backups from the replicated S3 bucket.
3. EBS snapshot restore: If your RPO is very tight and you want to recover the entire instance state, you can take regular EBS snapshots of your GitLab EC2 instance's root volume. While this captures the entire disk, including OS, application, and data, it doesn't guarantee application-consistent backups without careful orchestration (e.g., stopping GitLab services before snapshotting). It's more suitable for quick recovery of the entire environment rather than granular data restore.

The restore process walk-through

Regardless of the recovery option, the core restore steps for GitLab CE remain similar:

1. Provision a new EC2 instance: Launch a new instance (e.g., t3.large) using the Techforce Global GitLab CE AMI for AWS in your chosen region. Ensure it has sufficient disk space.
2. Configure networking and access: Assign the appropriate security groups, elastic IP (if needed), and SSH access.
3. Install dependencies (if not using AMI): If you're not using our AMI, you'd manually install GitLab CE and its dependencies. Our AMI handles this, saving significant time.
4. Copy configuration files: Restore /etc/gitlab/gitlab.rb and /etc/gitlab/gitlab-secrets.json from your backup to the new instance.
5. Configure S3 access: Ensure the new instance has an IAM role allowing access to your S3 backup bucket.
6. Download the backup file: Retrieve the latest GitLab backup tar archive from S3 to the new instance.
7. Stop GitLab services (for restore): Run sudo gitlab-ctl stop unicorn and sudo gitlab-ctl stop puma to stop web services.
8. Restore the backup: Use the GitLab Rake task: sudo gitlab-rake gitlab:backup:restore BACKUP=1678888888_2024_03_15_17.0.5 (replace with your backup file timestamp).
9. Reconfigure and restart GitLab: Run sudo gitlab-ctl reconfigure and sudo gitlab-ctl restart.
10. Verify: Access your GitLab instance, log in, and verify that all projects, users, and CI/CD data are present and functional.

This process highlights the value of starting with a consistent base like the Techforce Global GitLab CE AMI. It ensures that step 1-3 are largely handled, allowing your team to focus directly on data restoration and verification.

Table 3. Disaster recovery strategy comparison for self-hosted GitLab CE on AWS.

Testing and maintaining your disaster recovery strategy

A DR plan is only as good as its last test. Regular testing is crucial to identify weaknesses, validate recovery procedures, and ensure your team is familiar with the process. Consider these points:

• Scheduled DR drills: Periodically perform full recovery drills to a separate test environment. Document any issues and update your plan.
• Backup validation: Regularly verify that your backup files are not corrupt and can be successfully restored. A full restore test once a quarter is a good cadence.
• Monitoring: Set up CloudWatch alarms for backup job failures, S3 bucket size, or other indicators that might impact your DR readiness.
• Documentation: Maintain clear, concise documentation of your DR plan, including all steps, contact information, and AWS resource details.
• Review and update: As your GitLab instance evolves or AWS services change, review and update your DR plan accordingly.

By integrating the Techforce Global GitLab CE AMI into your DR plan, you ensure that the foundational setup of your recovery instance is consistent and well-understood. This allows your team to focus their precious DR time on the unique data restoration and verification, rather than troubleshooting base system configurations.

Table 4. Disaster recovery plan checklist for GitLab CE on AWS.

Building a robust disaster recovery strategy for self-hosted GitLab CE on AWS is a critical investment in your development operations. It protects your most valuable asset, your code, and ensures that unforeseen outages don't translate into extended downtime or irreversible data loss. By combining GitLab's native backup capabilities with the resilience and scalability of AWS services like S3 and EC2, and leveraging a consistent base like the Techforce Global GitLab CE AMI for AWS, you can create a highly effective and manageable DR plan. Remember, the true value of a DR plan lies in its regular testing and ongoing maintenance, ensuring that when the unexpected happens, your team is prepared to recover swiftly and efficiently.