Building My Cloud, DevOps/MLOps, Platform Engineering Portfolio
Why I Built This Engineering Portfolio
This site exists for one reason: to show how I build real systems.
I’m a senior Linux and infrastructure engineer transitioning into Cloud, DevOps/MLOps, Platform engineering through hands-on projects, structured training, and production-style implementations. Rather than keeping that work private, I’m documenting it in public — not as a learning diary, but as a working technical portfolio.
The DataTalksClub Data Engineering Zoomcamp is one of the structured programs guiding this journey, but the scope of this blog goes far beyond a single course. Here you’ll find cloud infrastructure, CI/CD pipelines, data platforms, automation workflows, and AI experiments built on Linux-based systems.
The Platform Behind This Site
This site itself is a real DevOps project.
It is built and deployed using:
- Jekyll — static site generator used in production environments
- Chirpy — a developer-focused theme with CI/CD and SEO built in
- GitHub Actions — full CI/CD pipeline for automated builds and deployments
- GitHub Pages — cloud hosting with automated publishing
Every commit triggers a build, dependency resolution, static site compilation, and deployment — just like a production delivery pipeline.
What I Solved to Make It Work
Getting this site live wasn’t just clicking “enable GitHub Pages.” It required:
- Understanding Jekyll’s configuration model and project structure
- Integrating the Chirpy theme into a GitHub Pages–compatible pipeline
- Configuring GitHub Actions to handle Ruby dependencies and builds
- Debugging YAML, bundler, and CI failures caused by small syntax and config issues
- Rebuilding broken pipelines and restoring stable deployments
These are the same types of problems that appear in real DevOps and platform engineering work: dependency conflicts, CI failures, environment mismatches, and brittle configuration.
Fixing them required careful debugging, reproducibility, and automation — exactly the mindset needed for cloud engineering.
What This Blog Will Contain
This is not a course notebook.
This is a portfolio of working systems.
Here you’ll see:
- Cloud infrastructure built with Terraform
- Data platforms using BigQuery, Spark, Mage, and dbt
- CI/CD pipelines and automation with GitHub Actions
- Linux-based deployments
- MLOps and AI workflow experiments
Some projects will be guided by the DataTalks Zoomcamp. Others will be independent builds designed to mimic production engineering environments.
My Posts
Every post here will tie back to:
- Architecture
- Automation
- Reliability
- Reproducibility
- Real engineering decisions
This blog is how I demonstrate technical skills in Linux infrastructure, Cloud, Platform engineering with public, verifiable work.
What’s Next
The first major build starts with containerized data pipelines and infrastructure as code — using Docker and Terraform to deploy real cloud-hosted systems.
From there, this portfolio will grow into full cloud platforms, CI/CD pipelines, and AI-driven workflows.
This is the first commit in that journey.