Sold by: ZSoftly Technologies Inc.
Self-hosted GitLab CI/CD runners on AWS. Cut build times 80%, eliminate minute limits, reduce costs 50%. Fixed 6-week deployment on EC2 with auto-scaling and caching.
Overview
OVERVIEW
Your shared GitLab runners are the bottleneck. Builds queue behind other users. Minutes limits block releases. Your CI/CD bill grows as your team ships more.
ZSoftly deploys enterprise-grade self-hosted GitLab runners inside your AWS account with auto-scaling, multi-layer caching, and full observability. You own the infrastructure. You control the costs.
WHAT WE DELIVER
Runner Infrastructure
- GitLab Runner fleet on EC2 (spot + on-demand mix for cost optimization)
- Auto-scaling from 0 to 100+ runners based on queue depth via GitLab Runner Autoscaler
- Multi-architecture support: AMD64 and ARM64 (Graviton) for up to 40% additional savings
- VPC-native deployment with private subnets and security group hardening
Performance & Caching
- Docker layer cache backed by Amazon ECR
- Dependency cache using Amazon S3 (npm, pip, Maven, Go modules)
- Artifact cache with configurable TTL and automatic cleanup
Security
- IAM role-based access — no long-lived credentials in pipelines
- Amazon ECR for private container image storage
- Secrets via AWS Secrets Manager, not GitLab CI variables
- Optional: VPC-isolated runners for compliance workloads (HIPAA, PCI-DSS)
Observability
- CloudWatch dashboard: queue depth, runner utilization, build duration, cost per pipeline
- Automated cost alerts via AWS Budgets
- GitLab pipeline analytics integration
ENGAGEMENT TIMELINE
Week 1-2: Discovery and architecture design. We review your current runner configuration, pipeline patterns, and AWS account setup. We design the runner fleet for your specific workload mix.
Week 3-4: Infrastructure deployment. Runner fleet deployed via Terraform. Auto-scaling configured. Caching layers active. Initial pipeline migration to self-hosted runners.
Week 5-6: Optimization and handoff. Cache hit rates tuned. Cost dashboard live. Team trained on operations. Runbook delivered. 30-day post-deployment support begins.
RESULTS YOU CAN EXPECT
- Build times: 45 min → 8 min (Docker layer caching eliminates redundant pulls)
- Monthly cost: $12K → $4K (EC2 spot pricing vs. per-minute SaaS)
- Queue wait: Eliminated (dedicated capacity, instant scaling)
- Minute limits: Gone (self-hosted runners have no GitLab minute caps)
WHO THIS IS FOR
- Teams running 500+ GitLab CI pipelines per month
- Organizations hitting GitLab shared-runner minute limits
- Engineering teams where slow builds delay releases
- Companies wanting CI/CD infrastructure inside their AWS security boundary
WHAT IS INCLUDED
Fixed-scope 6-week deployment. Terraform source code. Architecture documentation. Operations runbook. 30-day post-deployment support via shared Slack channel.
Highlights
- 10x faster builds with zero queue time: Self-hosted GitLab runners on EC2 auto-scale from 0 to 100+ based on queue depth. Docker layer cache via Amazon ECR eliminates redundant pulls. Dependency cache on S3 makes repeat builds instant. Your 45-minute build drops to 8 minutes.
- 50% lower CI/CD costs — pay for compute, not per-minute markup: EC2 Spot instances cut runner costs 60-70% versus on-demand. Typical teams spending $12K/month on shared runners drop to $4K. ARM64 Graviton runners add another 20-40% savings on compatible workloads. Cost dashboard in CloudWatch shows spend per pipeline.
- Production-ready in 6 weeks, fully owned by your team: Runner fleet deployed via Terraform in your AWS account — inside your VPC, using your IAM roles, with no long-lived credentials in pipelines. AWS Secrets Manager for pipeline secrets. CloudWatch monitoring dashboard included. 30-day post-deployment support via shared Slack channel.
Details
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Delivery method
Deployed on AWS
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Support Email: operations@zsoftly.com Support URL: