Deployment and Management of GitLab on AWS EKS Cluster
Implemented a highly available, scalable GitLab instance on AWS EKS with RDS and S3 integration to support a growing development team.
The Challenge
The client needed a robust, self-hosted GitLab instance to support their growing development team of 50+ engineers. Their existing solution was unstable, suffered from performance issues during peak usage, and lacked proper backup and disaster recovery procedures. They required high availability, scalability, and integration with their existing AWS infrastructure and CI/CD pipelines.
The Solution
I designed and implemented a containerized GitLab deployment on AWS EKS (Elastic Kubernetes Service) using Helm charts for orchestration. The solution leveraged AWS RDS PostgreSQL for the database tier, S3 buckets for artifact storage, and integrated with AWS IAM for authentication. I configured auto-scaling at both the pod and node levels to handle varying workloads efficiently. The implementation included GitLab Runners deployed as a separate EKS workload with node affinity rules to optimize CI/CD performance.
Results & Impact
- Achieved 99.9% uptime with the Kubernetes-based GitLab infrastructure
- Reduced page load times by 60% through optimized container configuration and caching
- Implemented automated daily backups with point-in-time recovery using S3 and RDS snapshots
- Scaled CI/CD capacity automatically based on demand, reducing build queue times by 75%
- Reduced operational overhead through infrastructure as code and Kubernetes-native management
Architecture Overview
The GitLab deployment was architected with the following components:
- Container Orchestration: AWS EKS cluster deployed across multiple availability zones for high availability and fault tolerance.
- GitLab Application: Containerized GitLab deployment using official Docker images and Helm charts with customized configurations for enterprise workloads.
- Database Tier: AWS RDS PostgreSQL with Multi-AZ deployment for high availability and automated backups.
- Object Storage: S3 buckets for artifacts, LFS objects, registry images, and backups with appropriate lifecycle policies and versioning.
- Caching Layer: Redis deployed as StatefulSet within the EKS cluster for session management and caching.
- Load Balancing: AWS Application Load Balancer with SSL termination, integrated with Kubernetes Ingress resources.
- CI/CD Infrastructure: GitLab Runners deployed as a separate workload with auto-scaling capabilities and resource quotas to prevent resource contention.
- Monitoring and Logging: Prometheus and Grafana for monitoring, with CloudWatch for centralized logging and alerting.
Implementation Highlights
Key aspects of the implementation included:
- Infrastructure as Code: Used Terraform to provision and manage all AWS resources, including the EKS cluster, RDS instances, and S3 buckets.
- GitOps Workflow: Implemented ArgoCD for continuous deployment of GitLab and related services, ensuring configuration consistency.
- Security: Configured network policies, pod security policies, and IAM roles for service accounts to implement defense-in-depth security.
- Backup and Disaster Recovery: Implemented automated backup solutions using Velero for Kubernetes resources and integrating with RDS snapshots and S3 versioning.
- Performance Optimization: Fine-tuned resource requests and limits, implemented horizontal pod autoscaling, and configured node affinity rules to optimize performance.