Infrastructure & Automation Engineer

Keagan Ball

Healthcare IT ยท Hybrid Infrastructure ยท Cloud Engineering

Infrastructure engineer with a background in enterprise healthcare IT. I automate operations, own hybrid Windows/Linux environments, run PRTG monitoring at scale, and build the tooling that keeps systems observable, reliable, and easier to operate.

// Approach

How I think
about infrastructure

I build systems that reduce operational friction, improve reliability, and give engineers back time to focus on meaningful work. Good infrastructure is mostly invisible - it's observable, automated, and designed to fail gracefully when it does fail.

Coming from healthcare IT, I've learned to respect the weight of uptime. When systems go down in clinical environments, the cost is real. That context has shaped how I think about monitoring, change management, and automation - not as extras, but as first-class engineering concerns.

I'm drawn to the intersection of platform engineering and operations: building the internal tooling, pipelines, and automation layers that make infrastructure teams significantly more effective. I believe the best infrastructure engineers write as much code as they rack hardware.

๐Ÿ–ฅ๏ธ
Infrastructure Engineering

Hybrid Windows/Linux environments, Active Directory, virtualization platforms (Proxmox, Hyper-V, Azure VMs), networking, and the operational systems that enterprise workloads depend on.

โš™๏ธ
Automation & Tooling

PowerShell modules, Python tooling, REST API integrations, user lifecycle automation, and internal platforms that replace manual operational workflows with repeatable, logged code.

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Cloud & Platform

Azure infrastructure, hybrid identity (Entra ID), containerized workloads with Docker and Azure Container Apps, and modernization pathways from on-premises operations toward cloud-native patterns.

// Currently Exploring

What I'm Building & Learning

Active experiments, ongoing lab work, and things I'm spending time on right now.

๐Ÿงช
RAG Pipelines for IT Ops

Building local retrieval-augmented generation systems for surfacing institutional knowledge - runbooks, incident history, documentation - from internal sources.

Active Lab
๐Ÿ—๏ธ
IaC with Bicep / Terraform

Declarative Azure infrastructure - moving from portal-click deployments toward reproducible, version-controlled environments that can be torn down and rebuilt in minutes.

Starting Phase
๐Ÿ“Š
Observability Stack

Self-hosted Prometheus + Grafana + Loki running in the homelab - learning to instrument everything and build dashboards that actually help during incidents.

Starting Phase
๐Ÿ”„
Azure Arc & Hybrid Mgmt

Exploring Azure Arc for projecting on-prem infrastructure into Azure management - consistent policy, RBAC, and monitoring across hybrid environments.

Learning
๐Ÿค–
AI Infrastructure Systems

GPU-backed inference infrastructure, local model serving, and the operational considerations around running AI workloads - not just using AI, but running it.

Experimenting