Hello,
my name is Dennis Faas, and I am a
Senior DevOps / Infrastructure Engineer and Platform Systems Architect
specializing in Linux, Windows, automation, infrastructure engineering, and AI-assisted development workflows.

Professional Background

Portfolio Summary

I am a senior infrastructure and systems engineer with over two decades of hands-on experience building, operating, and evolving production systems from the ground up. I have been building and managing dedicated web servers since 2001 and have a deep understanding of both hardware and software architecture, going back to assembling and troubleshooting systems at the component level since the early 1990s. This foundation allows me to approach complex problems methodically, working from first principles rather than relying on assumptions or pre-built solutions.

I specialize in taking loosely defined or high-risk technical problems and turning them into structured, reliable systems. I design and implement complete environments across Linux and Windows, including web infrastructure, databases, DNS, and virtual / networking, with a strong emphasis on security, isolation, and control. I typically build systems inside virtual machines to establish clear boundaries, then further containerize workloads using Docker to enforce tighter execution control, reproducibility, and safe testing environments.

Core Strengths

Infrastructure Architecture - I architect and operate production infrastructure across Linux and Windows, implementing LAMP-based web stacks, Apache virtual host routing, reverse proxy layers, reverse / DNS with dynamic updates (BIND/RFC2136), and automated TLS provisioning using Let's Encrypt wildcard certificates. I design virtual networks with segmentation boundaries and enforce layered isolation through virtual machines and containerized workloads (Docker), integrating security controls such as fail2ban-driven intrusion prevention and firewall automation to ensure hardened, stable, and scalable environments.

Automation and Systems Engineering - I build fully reproducible automation using scripting, while leveraging AI-assisted development to generate, refine, and refactor code across multiple languages, with a focus on eliminating manual processes, reducing code bloat through modular and reusable components, enforcing validation, and implementing reliable provisioning, rollback, backup, and recovery workflows.

Platform Engineering and Execution Systems - I design and implement internal platforms and execution frameworks that standardize how code is built, tested, and deployed through terminal-first workflows, project isolation, workspace orchestration, command wrappers, and reproducible pipelines, with consistent behavior across host systems and Docker containers. These systems enable controlled, parallel execution and incorporate validation gates, staged rollout strategies, and rollback-safe mechanisms, allowing complex changes to be introduced safely into live environments without downtime or unintended impact.

Core Platform Architecture

Education and Certification

I hold a Bachelor of Computer Science degree from the University of Windsor, Windsor, Ontario, Canada.

Experience

Senior DevOps / Infrastructure Engineer, Platform Systems Architect, Infopackets, Inc, Lakeshore, ON | 2008 - Present

I design, automate, and maintain production infrastructure across Linux and Windows environments, with current focus centered on Linux platform engineering (using Almalinux), with full LAMP stack (Linux, Apache, MySQL, PHP). I use virtual machines for testing and deployment, alongside Dockerized images for tightly controlled permissions in order to create reproducible system workflows, with advanced and automated terminal scripts I've developed to make deployment efficient.

I am currently leading a large production migration from Drupal 7 to WordPress 7 (due April, 2026), including custom routing for legacy URLs, redirect map generation, metadata and taxonomy migration, MU-plugin development for customized user experience, and SEO-safe preservation of a long-running publishing platform. This work also includes infrastructure redesign, staged rollout planning, rollback safety, and ongoing validation to protect production continuity.

During the WordPress deployment, I have been using AI (ChatGPT) to analyze and deploy custom scripts, including Codex CLI, Docker sandboxes, custom terminal wrappers, structured Dockerized project switching, and the implementation of Codex CLI paired with a reasoning-agents in order to automate the process even further.

I.T. Consultant, Publisher, Systems Administrator, Web Developer, Computer 411, Windsor, ON | 2001 - 2008

I provided on-site and remote technical consulting, Windows network administration, PC repair, Linux web server administration, server-side programming, and application troubleshooting. During this period I also published technical content daily, authored books on computing, and developed custom web and server-side programs to automate publishing, infrastructure support, and server management workflows.

Skills: Infrastructure / DevOps / Platform Engineering

Skills: Automation / Systems Engineering

Skills: Development Systems / Data / AI Workflow

Resume, Contact

Recent Projects

• 2026 Mar

  Agentic AI Development Platform

  (Reasoning Agent, Codex CLI, Docker Sandboxes, Terminal Tooling)

  I am currently developing an Agentic AI workflow that pairs a reasoning AI agent alongside ChatGPT's Codex CLI (a code-generating agent built into the terminal) to build and refine web-based programs in a well-structured and highly automated way. I developed this system to eliminate the slow, manual trial-and-error process of traditional AI-assisted coding (i.e.: browser-based ChatGPT and similar), where the output is often incorrect (in my experience, roughly 7 out of 10 times), requires constant copy-and-paste from ChatGPT browser to the terminal, which then leads to constant back-and-forth prompting, testing, and refinement that can take days to weeks to complete. The new system removes that bottleneck completely by allowing the AI to continuously execute, test, and iteratively improve its own output in automated loops, self-checking as it goes, and eliminating the need for manual intervention. This can reduce development time down to hours instead of days. This approach represents a best-in-class, next-generation development model, moving beyond traditional prompt-driven tools toward a fully autonomous, closed-loop workflow that is not yet widely available in most current platforms.

• 2026 Feb

  Content Similarity and Relevance Ranking Engine

  (Cosine Similarity, Keyword Overlap, Category Weighting)

  I am developing a custom relevance engine for related content discovery using keyword overlap scoring, cosine similarity, phrase validation, category weighting, and explainable ranking reports. The system is designed to improve internal linking quality and content relevance on a production publishing platform. This project is a continuation of the Keyword-Core project.

• 2026 Feb

  Multi-Project Docker Sandbox Platform

  (Developer Platform, Automation, Reproducible Environments)

  As I began working across multiple projects using Docker and AI tools like ChatGPT and Codex CLI, I found that too much time was being lost repeatedly provisioning and configuring environments for each new project. This created a need to standardize environments and automate project switching so each project could run independently without constant manual setup. To solve this, I engineered a multi-project containerized development platform with isolated workspaces, shared base images, custom project orchestration, terminal wrappers, and reproducible initialization scripts. This environment allows safe switching between projects while maintaining consistent shared code across all projects and the host system and significantly improving reliability and development speed.

• 2026 Feb

  Keyword-Core Analytics Engine

  (Content Analysis, Weighted Scoring, Explainable Output)

  I built a custom content analysis engine to extract meaningful keywords and phrases from an online article, which is then used to intelligently interlink related articles in the current article in order to improve search engine optimization and promote the current article as a topical authority. Instead of relying on simple keyword matching to interlink articles, the system analyzes content in context, groups related terms to produce phrases (subtract commonly used words), then ranks each keyword relevance using a scoring model, resulting in true topic similarity. This strengthens internal linking structure, improves search visibility, and helps search engines better understand an article's content, as well as related content.

• 2026 Jan

  Drupal 7 to WordPress Platform Migration

  (AlmaLinux, Apache, MariaDB, URL Preservation, MU Plugins)

  I am leading a large-scale migration of a long-running production publishing platform from Drupal 7 to WordPress 7, including migration of 11,000+ articles, taxonomy and metadata preservation, custom plugin development, SEO-safe redirect mapping, legacy path handling, and staged infrastructure modernization using AlmaLinux. This project is ongoing because I am also building an autonomous artificial intelligence coding agent that is capable of operating inside the virtual machine that runs the website in order to aid with automated custom programming development. The goal is to use ChatGPT in the browser to define structured specifications and pseudo-algorithms, then use custom AI-integrated tooling that bridges the host environment and Docker containers to orchestrate code generation, execution, and refinement in a streamlined, automated workflow.

Selected Engineering Projects

• 2026

  Lightweight Code Synchronization and Snapshot Deployment System

  (Push/Pull Workflows, Dry Runs, Timestamped Backups, Safe Rollback)

  I developed a custom synchronization and deployment framework (`bak`) to promote code safely between live systems and Docker-based development environments without depending on external version-control platforms. While tools like Git provide strong source control, they do not natively handle live deployment safety, environment-aware synchronization, or pre-deployment rollback of production state, which were critical requirements for my workflow.

  The system supports project-aware push/pull workflows, dry-run execution, mirrored sync, centralized parameter files, and automatic timestamped backups of the target environment before deployment. Each project defines approved source and destination paths, along with include/exclude rules, ensuring only vetted files are synchronized.

  Every operation is logged, backup snapshots are created prior to changes, and rollback can be performed immediately from archived states. This approach provides a controlled, lightweight deployment pipeline optimized for rapid iteration, reduced risk, and safe code promotion across host and container boundaries, while maintaining capabilities not typically addressed by traditional version-control systems.

• 2026

  AI Execution Safety and Sandboxing Framework

  (Docker Isolation, Permission Gating, Execution Control, Audit Logging)

  Allowing AI systems to generate and execute code introduces risk if not properly contained. I designed a sandboxing framework using Docker to isolate execution, combined with permission gating, logging, and controlled workflows to ensure all actions are traceable and safe. This allows AI-driven automation to operate within strict boundaries while still enabling iterative development, effectively balancing autonomy with system security.

• 2026

  AI-Orchestrated Development and Execution Framework

  (ask CLI, Docker Integration, Shared Tooling, AI Execution Pipeline)

  I developed a terminal-based orchestration framework (`ask.sh`) that interfaces with Dockerized environments to enable structured, AI-assisted development workflows. It bridges host and container layers using a shared Bash tooling library (/root/.bash_functions) that is bind-mounted into containers, ensuring consistent execution across environments.

  This allows AI agents to invoke validated host-level commands inside isolated Docker workspaces for controlled code generation, execution, testing, and refinement. The result is a repeatable, observable workflow that reduces environment drift and minimizes manual intervention while maintaining reliability and execution safety.

Achievements

$2.5M+ Revenue Generated Through Self-Engineered Platform, Infopackets, Inc | 2001 - present

I designed, built, and operated a fully self-managed publishing platform that generated over $2.5 million in revenue through advertising, affiliate systems, and software distribution. This includes end-to-end ownership of infrastructure, automation, content delivery, SEO strategy, and platform scalability.