Cloud Infrastructure & DevOps Engineering
Deployments that are boring, infrastructure that is written down, and a cloud bill you can explain.
Request a consultationInfrastructure problems rarely announce themselves. They show up as a deploy that everyone dreads, a server only one person knows how to touch, a cloud bill that grew forty percent without anyone deciding it should, or an outage that took a weekend to understand. Each of these is a symptom of infrastructure that lives in people's heads instead of in code.
We fix that. We design cloud environments and build the delivery pipelines around them so every change — application code, configuration, infrastructure — flows through version control, gets reviewed, and deploys automatically. This is the GitOps model: the repository is the source of truth, and the running system converges to it. It is how we run our own production clusters, and it is what we install for clients.
The work spans AWS architecture, Kubernetes, containerization, CI/CD, observability, and cost control. The goal is not sophistication for its own sake; it is a system your team can operate confidently and a bill that matches what you actually use.
This is for you if
- Deployments are manual, infrequent, and stressful.
- One engineer is the single point of failure for production.
- Your cloud costs are growing faster than your business and nobody can say why.
- You are moving from a single server or a PaaS to something that needs to scale, and want to do it once.
Cloud Infrastructure & DevOps: what's included
Cloud architecture and migration
Designing AWS (or Azure/GCP) environments with the right account structure, networking, security boundaries, and cost controls — and migrating existing workloads onto them with minimal downtime.
Kubernetes and containers
Containerizing applications and running them on managed Kubernetes (EKS) or lightweight distributions (K3s) with proper resource limits, health checks, autoscaling, and secrets management.
CI/CD pipelines
Automated build, test, and deployment pipelines with GitHub Actions or your existing tooling, so a merged pull request becomes a production deploy without anyone logging into a server.
GitOps and infrastructure as code
Terraform for cloud resources, Flux or Argo CD for cluster state, and everything reviewable in pull requests. Drift is detected and corrected automatically.
Observability and on-call readiness
Metrics, logs, and traces with Prometheus, Grafana, and Loki or your cloud provider's tooling; alerts that mean something; and runbooks for the ones that page a human.
Cost optimization
Rightsizing, reserved capacity, storage tiering, and eliminating the resources nobody remembers creating. Typically pays for the engagement within a few months.
How an engagement works
Assessment
A review of your current environment, deployment process, and cloud spend, with a written list of risks ranked by likelihood and impact.
Target design
The architecture, the pipeline, and the migration plan — with what changes for your developers day to day spelled out.
Incremental migration
One service at a time, with the old path kept alive until the new one is proven. No big-bang cutovers.
Handover
Documentation, runbooks, and working sessions with your engineers until they are comfortable operating it without us.
What you walk away with
- Every deploy triggered by a merged pull request and completed without manual steps.
- Infrastructure fully described in code and rebuildable from a repository.
- Dashboards and alerts that show what production is doing and tell you when it is not.
- A cloud bill broken down by service, with a plan for reducing it.
Frequently asked questions
Which cloud providers do you work with?
AWS primarily, with Azure and GCP as needed. We also design hybrid setups where some workloads run on-premises hardware, which is increasingly common for AI and data-heavy systems.
Do we need Kubernetes?
Not always, and we will say so. A single application with modest traffic is often better served by a simpler container platform. Kubernetes earns its complexity when you have several services, need scheduled jobs and autoscaling, or want portability between environments.
How do you handle secrets and credentials?
Secrets live in a managed store such as AWS Secrets Manager and are injected into workloads at runtime. Nothing sensitive is committed to a repository, and rotation does not require a redeploy.
What does ongoing support look like?
A monthly agreement covering monitoring, patching, capacity changes, and a response commitment for incidents. Many clients keep us on retainer after the initial build for exactly that.
Can you work with our existing DevOps team?
Yes, and it is usually the best arrangement. We bring the design and the initial build; your team owns it going forward, with us available for review and escalation.
Related services
Talk to us about Cloud Infrastructure & DevOps
Start with a free 30-minute discovery call. We'll tell you honestly whether this is the right fit.
Request a consultation