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An AWS bill with zero governance. 28 On-Demand nodes. No observability. 3 months later: 70–88% cost reduction, 100% IaC coverage, full GitOps pipeline, and an AI agent trained to handle future infrastructure changes. The project pays for itself in about 5 months.
NONO Soluciones operates the HunterX platform — a background-check service used by companies across multiple countries. When CAMTECH AI reviewed their AWS infrastructure, 28 On-Demand EKS nodes were running in Ohio with 33 Lambda functions across three environments, and 30% of resources lived outside Terraform. The setup had grown organically over years without governance.
These are the operational bottlenecks that AI automation eliminates in a 2-week pilot.
Runaway AWS costs — 28 On-Demand EKS nodes, an unused staging environment billing monthly with its own VPC and NAT Gateway, and orphaned resources nobody knew still existed. Infrastructure was the second-largest cost behind payroll.
No infrastructure governance — 30% of resources not in Terraform. No remote state, no state locking. Infrastructure changes were made manually. 15+ duplicated Terraform files with no module structure.
Blind operations — no CloudWatch alarms, no metrics dashboards, no alerting. If EKS pods crashed or Lambda throttles spiked, the team learned about it from users calling support.
Unmanaged workloads in other regions — a payroll application running in Virginia with no IaC, no monitoring, and no documentation. Resources existed but nobody owned them.
A full AWS infrastructure rebuild executed across 8 weeks with immediate cost impact. EKS cut from 28 On-Demand nodes to ~6-8 Spot instances via Karpenter, delivering savings within 3 weeks. Terraform/Terragrunt now governs 100% of resources — S3+DynamoDB remote state with locking, modular environment separation, and naming convention standardization. 83 Lambdas migrated from Serverless Framework to Terraform with per-function metrics and centralized dashboards. RDS MySQL migrated to Aurora Serverless v2. 12 Route53 zones consolidated to 2 AWS apex zones. DNS, SES, DKIM, SPF, and DMARC configured for both domains. GitOps pipeline deployed: CodeCommit → CodePipeline → CodeBuild → ECR → Argo CD with immutable commit-SHA tags giving full pod→commit→author traceability. Lambda-based notifications router with SQS dead-letter queue and DynamoDB deduplication delivers alerts to the team via SES across 3 severity streams. SSM Session Manager for all remote access — no bastions, no open SSH. The delivery included an AI agent trained in .github/ to assist future infrastructure changes without CAMTECH dependency.
Every technology in this stack is production-proven across CAMTECH AI client engagements.
Ohio to us-east-1. Monorepo Terraform/Terragrunt. 2 VPCs with 3-tier subnets. 13 microservices on EKS Karpenter+Spot. 83 Lambdas on Terraform. Argo CD GitOps with commit-SHA tags. CloudWatch → SNS → SES email alerts. Every change is a git commit. Nothing is manual.
Architecture diagram coming soon
The project pays for itself in approximately 5 months — from month 6 onward, every dollar saved is recurring net savings. 100% of resources governed by code. Full observability: alarms on every critical component, alerts delivered across 3 severity streams. Infrastructure changes that used to happen manually from a laptop are now git commits with AI assistance.
Every CAMTECH AI engagement starts with a scoped 2-week pilot and a measurable outcome. Book a discovery call and we'll scope your first project.
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