Terraform

I designed and published a professional focused on pipeline reusability, security, and code quality. The project demonstrates real-world DevOps practices such as semantic versioning, reusable CI components, secure container builds with Kaniko, and standardized linting for Python and Django applications. This initiative reflects my approach to building scalable, maintainable CI/CD architectures in enterprise environments.

Key Features:

Native GitLab CI/CD Components Semantic versioning with pinned releases No privileged runners required Enterprise-ready defaults Configurable inputs without pipeline duplication

Included Components:

Kaniko – Secure, daemonless container image builds Pylint – Python static analysis Pylint Django – Django-specific linting rules Flake8 – Python style and code quality checks DjLint – Django template linting and formatting Yamllint – YAML validation and formatting Pytest – Unit testing and code coverage ...

Official GitLab Terraform Provider.

OpenTofu module: a lean GitLab Runner fleeting fleet (manager + scale-to-zero spot workers) for the ops account.

Reusable OpenTofu/Terraform module — AWS KMS OpenPGP encryption identity (certification primary + ECDH subkey) plus split-privilege reader/certifier roles, for receiving encrypted security reports. · https://aws-encryption-kms.iac.phpboyscout.uk

Tharsis Docs contains the documentation for the Tharsis components.

Reusable OpenTofu/Terraform module — AWS KMS asymmetric signing key + GitLab-OIDC signer role for release-binary signing chains. · https://aws-signing-kms.iac.phpboyscout.uk

Opinionated AWS security baseline for OpenTofu / Terraform — account hardening, audit logging, AWS Config, threat detection, alerts, MFA-required operator role. · https://aws-security-baseline.iac.phpboyscout.uk

Minimal, opinionated AWS account bootstrap for OpenTofu / Terraform — state backend, OIDC + automation role, aws-nuke config. · https://aws-bootstrap.iac.phpboyscout.uk

Abstraction for libvirt provider in OpenTofu/Terraform + cloud-init, simplified for easy baremetal cluster creation and management on QEMU and KVM

The purpose of this system is to demonstrably comply with the applicable laws and regulations that apply to your business operations. We achieve this by linking these regulations to a standard control set that is most suitable. We then translate the relevant control set rules into scripts for the implementation tools that best suit your system environment and use these same tools to demonstrate that the required measures are in place and active, based on reports that either confirm this or contain recommendations for improvement.

A highly-available Kubernetes cluster that runs entirely within the always-free tier of Oracle Cloud.

Every non-secret CI variable in the group: artifact version refs, per producer and per consumer.

This repository contains a collection of reusable Terraform modules designed to streamline the provisioning of infrastructure across various projects. Each module is maintained with best practices and aims to be highly reusable and customizable.

GitOps-driven Kubernetes platform on Talos Linux & Proxmox – Fully automated infrastructure with FluxCD, OpenTofu, CSI Proxmox, SOPS, Vault, Cilium, Gateway API (Envoy), Authentik OIDC, Forgejo, and a complete observability stack (Prometheus, Loki, Vector, Grafana).

Tharsis API is a remote Terraform backend that provides state management and a full execution environment for running Terraform modules. It also includes additional capabilities to facilitate the management of Terraform workspaces within an organization.

My fully-automated DevOps homelab.

Homelab infrastructure as code - Proxmox, Docker (dockhost), Kubernetes (kubecluster), Bastion

KubeLaunch is a self-service DevOps platform that I am building to help application teams deploy their applications to Kubernetes without manually setting up AWS infrastructure. It uses Terraform to provision VPC, IAM, ECR, and EKS, Docker for containerization, Helm for Kubernetes application deployment, and CI/CD to automate validation, deployment, and rollback. I am also building the monitoring and observability layer using Prometheus and Grafana, along with separate configurations for non-production and production environments.