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Infrastructure That Holds
When It Matters.

AWS, Kubernetes, and CI/CD for SaaS teams that outgrew their setup. Production-grade DevOps by an ex-PrivatBank engineer.

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-40%
AWS bill reduction
20M+
Customers on infra I built
4+
Years production DevOps
3x
Faster deploys

What We Fix

Five infrastructure problems SaaS teams hit at scale

01

AWS Cost Optimization

Most SaaS teams overpay AWS by 30-50% without knowing it. Reserved instances bought for the wrong workload, staging environments running 24/7, S3 lifecycle policies never configured. I audit your bill, find the waste, and fix it.

Typical result: 20-40% reduction in 30 days without touching application code. Savings plan migration, right-sizing, storage lifecycle rules, and spot instance adoption where applicable.

Best for: teams spending $3k+/month on AWS who've never done a formal cost review.

02

Kubernetes & Container Infrastructure

Setup, migration, and production hardening. Resource limits, health checks, rolling deployments, HPA. The cluster that doesn't need manual intervention at 3 AM.

03

CI/CD Pipelines

If your deploy takes 45 minutes, that's not a pipeline - it's a liability. I build automated pipelines that run tests, build containers, push to registry, and deploy to production in under 10 minutes. GitHub Actions, GitLab CI, ArgoCD.

04

Observability Stacks

Prometheus + Grafana + Loki + Alertmanager, deployed and configured for your workload. From zero visibility to Telegram alert in one engagement. You know what's breaking before your users do.

05

Infrastructure as Code

Terraform, Helm, ArgoCD - your infrastructure becomes version-controlled and reproducible. No more "it works on staging but not prod." Every environment is identical because it's defined in code.

Production Work

Infrastructure built under real constraints

001

PrivatBank — Production Infrastructure

3 years 9 months building and maintaining core infrastructure for one of Ukraine's largest banks. 20M+ customer operations running on systems I was responsible for. Deployed full observability stack (Prometheus + Grafana + Loki + Alertmanager) for containerized environments, built CI/CD pipelines that reduced deployment time, maintained Kubernetes clusters under financial-grade reliability requirements.

PrivatBank production infrastructure: Terraform IaC → AWS → Kubernetes → ArgoCD → Prometheus + Grafana + Loki + Alertmanager
KubernetesAWSTerraformPrometheusGrafanaLokiArgoCDDockerGitLab CI
20M+ customers 3yr 9mo tenure 99.9% uptime SLA
002

Observability Stack — Zero to Alert

Built complete observability infrastructure for a containerized production environment from scratch. Prometheus metrics collection, Grafana dashboards for engineering and business KPIs, Loki log aggregation, Alertmanager routing to Telegram. Team went from "we find out from users" to sub-5-minute incident detection.

Observability stack: Apps → Prometheus → Grafana + Loki → Alertmanager → Telegram alert in under 5 minutes
PrometheusGrafanaLokiAlertmanagerKubernetesHelm
<5 min detection Zero → full coverage Telegram alerts
003

CI/CD Pipeline Overhaul

Replaced a manual deployment process with fully automated GitLab CI/CD. Parallel test execution, Docker image build and push, automatic deployment to staging on merge request, one-click production promotion with rollback. Deploy time cut from 45+ minutes to under 8 minutes.

CI/CD pipeline: git push → GitLab CI → Docker build → AWS ECR → ArgoCD → Kubernetes production, 45 min to 8 min
GitLab CIDockerKubernetesArgoCDHelmAWS ECR
45min → 8min Zero manual steps 1-click rollback
Discuss Your Infrastructure →

Why It Works

Production experience, not tutorial knowledge

Most DevOps engineers learn Kubernetes by running tutorials on a local cluster. I learned it by keeping payment infrastructure online for 20 million bank customers. The gap between "it works in dev" and "it survives production" is something you only fully understand after a real incident at scale.

Dmytro Hamera Founder, OneX Systems — ex-PrivatBank infrastructure engineer

When I audit an AWS bill, I'm not running a cost tool and reading the output. I'm looking for the same patterns I spent years fixing in banking infrastructure: over-provisioned instances nobody questioned, staging costs that match production, monitoring gaps that hide slow leaks. I know where to look because I've been on the other side.

Dmytro Hamera Founder, OneX Systems

From first call to production in three steps

01

Infrastructure Audit

30-minute call. You describe the problem - slow deploys, AWS bill creep, no visibility, staging that lies. I map the current state and tell you exactly what's broken and why. No pitch deck, no generic recommendations.

02

Fixed-Scope Engagement

Defined scope, defined timeline, defined price. I build the infrastructure, write the Terraform, configure the pipeline, set up the dashboards. You get production-ready work your team can operate - not a system only I understand.

03

Handoff & 30-Day Support

Full documentation, knowledge transfer, and 30 days of monitoring support included. You own the code, the infrastructure, and the runbooks. Most clients stay on retainer for ongoing DevOps work after the initial engagement.

Dmytro Hamera — Founder, OneX Systems

Built by Someone Who's Run Production, Not Read About It

Dmytro Hamera

Founder & DevOps/AWS Engineer

3 years 9 months at PrivatBank — one of Ukraine's largest banks, 20M+ customers. Kubernetes, CI/CD, observability at scale. Every infrastructure decision had real consequences. That's not a background I use for credibility on a website. It's the reason I know exactly where SaaS infrastructure breaks at scale, because I've fixed the same problems in a higher-stakes environment.

I started OneX Systems to bring that same production discipline to SaaS teams that are growing faster than their infrastructure can handle.

AWS Kubernetes Terraform CI/CD Docker Prometheus
LinkedIn Profile

Questions we get every time

Depends on scope. An AWS cost audit with fixes typically takes 1 to 2 weeks. A CI/CD pipeline overhaul is 1 to 3 weeks. A full Kubernetes setup with observability stack is 3 to 5 weeks. You get a specific timeline after the infrastructure audit call — I don't estimate before I understand the current state.

Fixed-scope engagements. An AWS cost optimization audit starts at $800. A CI/CD pipeline build is $1,500 to $3,000 depending on complexity. A full Kubernetes + observability setup is $3,000 to $6,000. Ongoing retainer starts at $1,500/month. Pricing is set before work begins - no surprise invoices halfway through.

For audits, read-only access is sufficient. For build engagements, I work within your existing access control policies - your team grants scoped permissions, nothing broader than needed. I'm comfortable with NDA before the first call. All work is done in your infrastructure, not mine. You own everything at the end.

Full documentation, runbooks, and a knowledge transfer session are included in every engagement. 30 days of post-delivery monitoring support at no extra cost. Your team should be able to operate everything I build without me. Most clients continue on a retainer for ongoing DevOps work - but that's your call, not mine.

Tell me what's breaking.

Describe the infrastructure problem - AWS costs, slow deploys, no visibility, staging that lies. I will review your setup and come back with a concrete assessment - not a generic slide deck.

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