Olowookere Precious | DevOps & Cloud Engineer

Background

A different path
to infrastructure

I graduated with a Doctor of Veterinary Medicine from the University of Ibadan in 2023. Most people would not connect that to a career in cloud infrastructure. But the skills that make a good diagnostician: systematic thinking, following a problem to its root cause, not guessing when you can test. These translate directly into DevOps.

I am self-taught. Everything I know about AWS, Terraform, Docker, Kubernetes, and CI/CD pipelines came from building real things, breaking them, and understanding why they broke. That process has made me careful about how I build and honest about what I do not yet know.

I believe that when someone hires an engineer, they are not just paying for time. They are exchanging resources for expertise, effort, and responsibility. I take that seriously. I show up prepared, I research before I build, and I do not stop at "it works." I stop when I understand why it works and what would break it.

🎯

I finish what I start

When I commit to learning or building something, I see it through. Even when it is slow or confusing.

📈

1% better every day

Small improvements compound. I try to get slightly better at something every single day.

🔍

Root cause, not symptoms

I do not reset a service and move on. I find out why it needed resetting in the first place.

⚡

Value over hours

I prepare so that when I contribute to a project, I am bringing real thinking, not just time.

Technical Skills

What I work with

Built through hands-on projects, not just courses. Every tool below has been used in a real deployment.

Cloud Platform

AWS EC2 RDS Multi-AZ ALB S3 IAM VPC CloudWatch CodeDeploy Auto Scaling

Infrastructure as Code

Terraform CloudFormation HCP Terraform Remote State Modules

CI/CD & Automation

GitHub Actions AWS CodeDeploy GitLab CI/CD SonarCloud Nexus

Containers & Orchestration

Docker Docker Compose Kubernetes Meshery

Monitoring & Observability

Prometheus Grafana CloudWatch Node Exporter Alerting

Security & OS

Linux (Ubuntu) SSL/TLS Security Groups IAM Roles Secret Management Bastion Host

Certifications

🟣

Terraform Associate (003)

HashiCorp Certified

🔵

KCNA

Kubernetes & Cloud Native Associate

🔵

LFS250

Kubernetes & Cloud Native Essentials

⚫

GitHub Foundations

GitHub Certified

Case Studies

Projects that prove
what I can build

Real deployments with real results. Every number here came from an actual test run against a live system.

Project 01

AWS 3-Tier Java Architecture

Production-grade infrastructure with load testing, auto-scaling, and full observability

EC2 RDS Multi-AZ ALB GitHub Actions CodeDeploy CloudWatch Artillery SonarCloud

Feb 2026 6 Days

The Story

The goal was to build a production-grade 3-tier architecture. Not just get it running, but make it hold up under pressure. Nginx instances in public subnets routing to Tomcat application servers in private subnets, backed by RDS MySQL Multi-AZ across two availability zones.

Once everything was deployed, I loaded 9,000 concurrent requests into it using Artillery. The system struggled. Worst-case response times hit nearly 5 seconds. Connection timeouts started piling up.

I dug into why. The Auto Scaling Groups were reacting to CPU alone. Too slow for traffic spikes. I added a second metric: ALB RequestCountPerTarget. The system now scales before it is overwhelmed, not after.

I ran the test again. Everything changed.

Results

93%

p99 latency reduction
4,770ms → 314ms

100%

Request success rate
Zero timeouts

85s

End-to-end deployment
Code push → live

~60s

RDS failover recovery
3 tests, zero data loss

Key Decisions

Dual-metric Auto Scaling: CPU alone reacts too slowly. Adding RequestCountPerTarget made scaling proactive.

RDS Multi-AZ over single instance: 2-minute automatic failover vs 20-minute manual restore. Worth the cost.

Two ALBs: Public-facing for Nginx, internal for Tomcat. Backend completely isolated from the internet.

Transit Gateway + Bastion: Single secure entry point for admin access with full audit trail.

Project 02

FusionPact DevOps Challenge

Full 3-tier application deployed on AWS in 48 hours: automated, monitored, and production-ready

Terraform EC2 Docker Compose GitHub Actions Prometheus Grafana Let's Encrypt

Oct 2025 48 Hours

The Story

A timed technical assessment: deploy a production-ready 3-tier application on AWS in 48 hours. The constraint was intentional. No clicking in the AWS console. Everything had to be defined in code.

Terraform provisioned all 8 AWS resources. Docker Compose orchestrated 5 services with 3 persistent volumes ensuring zero data loss on container restart. SSL/TLS via Let's Encrypt with auto-renewal handled encryption. GitHub Actions automated every deployment.

The project was completed end-to-end in 48 hours: infrastructure, application, monitoring, CI/CD, and security all in place. Every bug encountered along the way became a documented lesson.

What Was Built

AWS resources via Terraform
Zero manual steps

Docker services running
3 persistent volumes

15s

Prometheus scrape interval
3 targets monitored

48h

Total delivery time
Full production stack

Key Decisions

Terraform over console: Reproducible, version-controlled, zero configuration drift.

Named Docker volumes: Data, metrics history, and dashboard configs survive every restart.

Auto-provisioned Grafana datasource: No manual setup on every fresh deployment.

GitHub Secrets for all credentials: Zero sensitive values in the codebase.

How I Work

What working with me
actually looks like

Not a list of soft skills. The actual way I approach a project from start to finish.

I understand before I build

I do not start writing code or configuration until I understand what the system needs to do, what could go wrong, and why each decision matters. Preparation is not a delay. It is the work.

I document everything

Every project I build is documented: the architecture decisions, the bugs I hit, the fixes I found, and the lessons. If something breaks after I hand it over, the person picking it up can understand exactly what I built and why.

I test under pressure

I do not call something production-ready until it has been tested under real load. I use tools like Artillery to stress-test systems, validate failover scenarios, and confirm that monitoring actually fires when something goes wrong.

I communicate clearly

I write technical documentation that non-engineers can follow. I explain decisions in plain language. I ask questions when requirements are unclear rather than making assumptions that cost time later.

I own problems fully

If something I built breaks, I do not point at the environment or the tools. I dig in, find the root cause, fix it, and document what I learned. That is what makes infrastructure reliable over time.

I keep getting better

I am building in public, documenting my projects on LinkedIn and Hashnode, contributing to open-source, and pursuing certifications. Every project teaches me something the last one did not.

OlowookerePrecious

A different pathto infrastructure

What I work with

Projects that provewhat I can build

AWS 3-Tier Java Architecture

FusionPact DevOps Challenge

What working with meactually looks like

Let's build somethingthat holds up.

Olowookere
Precious

A different path
to infrastructure

Projects that prove
what I can build

What working with me
actually looks like

Let's build something
that holds up.