nky@devops:~$

Hello, world. I'm

Nkechi Anna Ahanonye

Cloud & DevOps Engineer / AWS · Ansible · Terraform · K8s

I turn manual, 3 AM-breaking deployments into 1-min automated pipelines with AWS + Ansible + Terraform.
No more SSH-ing into prod. Featured: 15-Module Ansible Lab with real terminal.
Training 30+ African DevOps engineers. Open to Remote Roles.

1m 18s Deploy Time (was manual)
40+ IaC Repos Audited
DMI DevOps Mentor
.github/workflows/ansible-ci.yml
name: Ansible CI/CD Pipeline
on: [push]
jobs:
  lint-and-dry-run:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: yamllint
        run: yamllint .
      - name: ansible-lint
        run: ansible-lint
      - name: syntax-check
        run: ansible-playbook --syntax-check site.yml
      - name: dry-run
        run: ansible-playbook --check --diff site.yml
  deploy:
    needs: lint-and-dry-run
    runs-on: ubuntu-latest
    steps:
      - run: ansible-playbook site.yml
# Stop SSH-ing into prod.
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Nkechi Ahanonye — Cloud & DevOps Engineer
📍 Lagos, Nigeria
Open to work
🚀 1-min Automated Pipelines
🛠 Infrastructure as Code (IaC)
Kubernetes Orchestration
📝 Mentor-Grade Docs

Engineering reliability. Automating growth.

My journey in tech started 15 years ago running a high-pressure cybercafe. That experience taught me a fundamental truth: real users don't care about your stack—they care that the system works. Downtime = lost revenue immediately.

I moved from physical hardware to cloud, obsessed with one thing: Reliability. Today I help teams stop SSH-ing into prod. I build 1-min automated pipelines: Lint → Dry-Run → Deploy with GitHub Actions + Ansible + Terraform.

My approach:

  • Efficiency: Terraform + Ansible slash setup from hours to minutes. Cut deployment time by 60%.
  • Stability: 6 checks before prod — yamllint, ansible-lint, shellcheck, syntax-check, --check --diff. No more 3 AM firefights.
  • Documentation: Mentor-grade runbooks that cut new member ramp-up by 30%.

Beyond engineering, I co-mentor 30+ engineers at DevOps Micro Internship (DMI) across Africa and audited 40+ IaC repos for production-grade quality.

If your team needs an engineer who can architect, automate, and document production infrastructure that scales without the stress — I am open to Remote roles.

Lint → Dry-Run → Deploy Template reused as team standard
🐳
Containerization Docker · Kubernetes (k3s)
🎓
Technical Leadership DMI Mentor · 30+ Engineers Trained
Download CV

The stack I
deploy with.

Ansible

Playbooks, roles, inventory, Vault, Galaxy — 15-Module Lab

Advanced
🏗

Terraform

Multi-tier AWS, VPC, state, modules, 33 resources

Advanced

AWS

EC2, S3, VPC, IAM, RDS, ALB, Route 53, Lambda

Advanced
🚀

GitHub Actions

Lint → Dry-Run → Deploy, 2m 11s → 1m 18s proof

Advanced

Kubernetes

k3s, 3-node cluster, self-healing, ingress

Advanced
🐳

Docker

Dockerfiles, Compose, multi-tier

Advanced
🐧

Linux

Ubuntu, Nginx, MySQL, shell scripting

Advanced
🔁

CI/CD & Monitoring

Datadog, Prometheus, Grafana, ArgoCD

Intermediate
📝

Technical Docs

Architecture, SOPs, runbooks, DMI training

Expert
🧠

Agentic Workflows

Claude, LangChain, MCP, Groq — applied to DevOps docs

Intermediate - Real projects

Solutions I've
delivered.

Kubernetes k3s Self-Healing

K8s Cluster Deployment & Scaling

Challenge: High availability during traffic spikes.
Solution: 3-node cluster (1 control + 2 workers), pod scheduling, service routing.
Result: Resilient, self-healing, auto-scaling.

✅ HA ✅ 3-Node ✅ Self-Healing
ArgoCD Prometheus Grafana

Observability & GitOps Platform

Challenge: No visibility into microservices health.
Solution: GitOps with ArgoCD + Prometheus, Grafana, Zipkin tracing.
Result: Full observability, proactive incident detection.

✅ GitOps ✅ Monitoring ✅ Tracing
🧠
Python Groq Llama 3.3 Notion API Real Project

DevOps KB Auto-Builder — Real AI Tool

Challenge: After incidents, docs get skipped, mistakes repeat.
Solution: Python tool takes raw incident report → auto-generates structured Notion KB entry using Groq Llama 3.3 70B. Runs on free tools.
Result: Hours of docs → 30-second workflow. Submitted to Notion MCP Challenge.

✅ Real & Working ✅ Free Tools Only ✅ Closes Knowledge Gap

Other builds: GEORGEL Cancer Foundation (NGO) · Book Review App on EKS · Ultimate DevOps Hub

My deployment
pipeline.

Stop SSH-ing into prod. Every project follows Lint → Dry-Run → Deploy. Same template that went 2m 11s ❌ → 1m 18s ✅

🔍

Lint

Catch errors before prod

yamllint . && ansible-lint && shellcheck *.sh
🧪

Dry-Run

See what would change, without changing

ansible-playbook --syntax-check --check --diff site.yml
🐙

Git Push → GitHub Actions

Automated guardrails on every push

git push origin main
🏗

Terraform Provision

VPC, SG, IAM, ALB — 33 resources

terraform apply -auto-approve

Ansible Deploy

Idempotent config, zero SSH

ansible-playbook site.yml

Production Live — 1m 18s

No 3 AM calls. Runbook in Notion.

https://github.com/nkydigitech/ansible_practical/actions

Let's build
something reliable.

I help teams stop SSH-ing into prod. If you need 1-min pipelines that don't break at 3 AM, let's talk. Open to remote roles.