Discover Bandit, the specialized static security analyzer for Python. This comprehensive guide covers detecting security vulnerabilities, integrating with CI/CD, and enforcing secure coding practices in Python development.

Unlock the power of Semgrep for modern code security. This comprehensive guide covers static application security testing, supply chain analysis, and AI-assisted vulnerability detection with practical examples.

Discover Safety CLI, the comprehensive Python dependency scanner. This guide covers detecting vulnerabilities, malicious packages, license compliance, and integration with development workflows for robust security.

Master pip-audit for securing your Python projects. This in-depth guide covers installation, usage, integration with CI/CD, and how it helps mitigate supply chain attacks and dependency vulnerabilities.

Discover PostgreSQL extensions and master pgvector for vector search. This comprehensive guide covers installation, basic usage, and advanced vector similarity search techniques with practical examples.

Master the AWS MLS-C01 exam! Complete study guide mapping our SageMaker tutorials to all exam domains with hands-on examples and certification strategies.

Unlock the power of computer vision! Learn image recognition algorithms from traditional ML to cutting-edge deep learning, with practical AWS SageMaker implementations.

Level up your SageMaker skills! Learn professional ML techniques with real datasets, feature engineering, model validation, and deployment best practices.

Learn how I built and maintain my Jekyll blog with automated deployment, AI-powered content creation, and efficient workflows that make technical blogging scalable.

Master AWS SageMaker from scratch! Learn what it is, set up your first ML workspace, optimize costs, automate with Terraform, and build your first ML model with Jupyter notebooks.

Master Domain 5 of AWS Solutions Architect Associate. Learn operational excellence principles including Infrastructure as Code with CloudFormation/Terraform, monitoring with CloudWatch, automation with Systems Manager, and implementing well-architected best practices.

Master Domain 4 of AWS Solutions Architect Associate. Learn cost optimization strategies including reserved instances, savings plans, spot instances, resource right-sizing, storage optimization, and cost monitoring with AWS Cost Explorer and Budgets.

Master Domain 3 of AWS Solutions Architect Associate. Learn to design secure architectures using IAM best practices, encryption strategies, network security, VPC configuration, and compliance frameworks like HIPAA, PCI-DSS, and SOC 2.

Master Domain 4 of the AWS AI Practitioner exam with this deep dive into AI ethics and responsible AI. Understand bias detection, fairness metrics, privacy protection, and ethical AI development practices.

Master Domain 2 of AWS Solutions Architect Associate. Learn to select appropriate database solutions, implement caching strategies, optimize content delivery, and design performant architectures using CloudFront, ElastiCache, and RDS optimization techniques.

Master Domain 3 of the AWS AI Practitioner exam with this deep dive into generative AI. Understand foundation models, prompt engineering techniques, and AWS generative AI services with practical examples.

Master Domain 1 of the AWS Solutions Architect Associate exam. Learn to design resilient architectures using multi-AZ deployments, Auto Scaling groups, elastic load balancing, and fault-tolerant patterns. Understand RTO/RPO and backup strategies.

Master Domain 2 of the AWS AI Practitioner exam with this deep dive into AWS AI services. Understand SageMaker, Rekognition, Comprehend, Polly, and other services with real-world examples and implementation guidance.

Master Domain 1 of the AWS AI Practitioner exam with simple explanations of AI/ML fundamentals. Understand supervised/unsupervised learning, data preparation techniques, common algorithms, and model evaluation metrics with real-world examples.

Master the fundamentals of artificial intelligence from first principles. Learn about machine learning paradigms, neural network architecture, the transformer model revolution, attention mechanisms, and how foundation models power modern AI applications.

Deep dive into advanced AWS concepts including EC2 optimization, RDS performance tuning, Lambda best practices, VPC design patterns, IAM security strategies, and cost management. Learn production-ready architectures and common pitfalls to avoid.

Master AWS Machine Learning and AI services for the AWS Certified ML Specialty exam. Complete guide covering SageMaker, Bedrock, Comprehend, and more with practical examples and exam prep tips.

Master Git with this comprehensive cheatsheet featuring 50 essential commands. From basic operations like git init and git commit to advanced techniques like rebasing and bisecting, each command includes practical examples and explanations.

Prepare for the AWS AI Practitioner certification with this comprehensive study guide. Learn about AI/ML fundamentals, AWS AI services, generative AI, and responsible AI practices with detailed explanations and practical examples.

Complete AWS Glue tutorial covering everything from basic concepts to advanced ETL pipelines. Learn Glue Studio, crawlers, Data Catalog, job authoring, and real-world implementation patterns.

Advanced ETL guide covering real-time data processing, machine learning integration, enterprise architectures, performance optimization, and governance. Learn to build scalable, intelligent data pipelines for modern enterprises.

Comprehensive guide to building ETL pipelines on AWS. Learn to use AWS Glue for managed ETL, Lambda for serverless processing, Step Functions for orchestration, and create complete cloud-based data workflows.

Comprehensive introduction to ETL (Extract, Transform, Load) fundamentals. Learn the core concepts, understand why ETL is crucial for data engineering, and build your first simple ETL pipelines with practical examples.

Master GitLab from the ground up with this comprehensive guide. Learn to set up your own self-hosted GitLab server, implement powerful CI/CD pipelines, and explore advanced features like Kubernetes integration, security scanning, and enterprise workflows.

In-depth guide to running PostgreSQL on Docker containers. Learn container setup, data operations, backup strategies, security best practices, performance tuning, and essential housekeeping commands for database administration.

In-depth guide to running MariaDB/MySQL on Docker containers. Learn container setup, data operations, backup strategies, security best practices, performance tuning, and essential housekeeping commands for database administration.

Comprehensive tutorial for setting up a developer machine for Python and Node.js development on Ubuntu LTS. Covers Python installation with pyenv, Node.js with nvm, development tools like VS Code, databases, Docker, cloud CLIs, security hardening, and common pitfalls to avoid.

Discover FastAPI and Uvicorn - the powerful duo for building high-performance Python APIs. This guide covers setup, routing, validation, and deployment.

Have you ever played the classic arcade game Frogger? You know, the one where you guide a little frog across busy roads and rivers to reach the other side? Well, I recently built a version of this game using Python and Pygame, and then took it a step further by adding artificial intelligence (AI) to train an agent to play it automatically. In this post, I’ll explain what this project is, how to use it, and why a missing feature makes it a bit tricky to work with locally.

Home Assistant is an open-source home automation platform that lets you control smart devices, monitor your home, and integrate with various services. In this post, I’ll show you how to run Home Assistant using Docker Compose, install HACS (Home Assistant Community Store) for community integrations, and add the Octopus Energy integration to track your electricity and gas usage with beautiful graphs.

Transform your Windows desktop into a powerful DevOps development environment! This comprehensive guide covers Windows Subsystem for Linux (WSL) setup, Docker integration, development tools configuration, security hardening, and DevOps workflows. Get the best of both Windows and Linux worlds for modern development.

Master your Windows development environment! This comprehensive guide covers setting up PowerShell with profiles and modules, Git with SSH, Terraform and AWS CLI, VS Code configuration, and Windows package management with Chocolatey and winget. Perfect for Windows-native DevOps workflows.

Secure your Ubuntu LTS server from day one! This comprehensive hardening guide walks beginners through essential security practices including firewall setup, SSH hardening, user management, intrusion prevention with Fail2Ban, and automated security monitoring. Each step explained with clear reasoning and practical scripts.

Set up a secure development environment from the ground up! This comprehensive guide covers Git with SSH keys, Bash configuration, Terraform and AWS CLI setup, VS Code security configuration, and package management across macOS, Windows WSL, and Ubuntu LTS. Includes security-first practices, credential management, vulnerability scanning, and ongoing security maintenance to protect your development environment and production systems.

Implement GitOps practices in your Kubernetes clusters using ArgoCD and Flux. Learn how to automate deployments, manage configurations, and implement continuous delivery patterns.

Implement comprehensive monitoring and observability in your Kubernetes clusters using Prometheus, Grafana, and other powerful tools. Learn how to set up dashboards, alerts, and troubleshooting workflows.

Master Kubernetes security! Learn about Pod Security Policies, RBAC, Network Policies, and security best practices for production environments.

Master local AWS development with LocalStack! Learn how to install and configure LocalStack, create AWS resources locally, understand pricing tiers, and integrate with CI/CD pipelines. Includes practical examples and best practices.

Master production-grade Kubernetes deployments! Learn about StatefulSets, persistent storage, service mesh implementation, and advanced monitoring techniques for enterprise applications.

Discover how to use Checkov, Terragota, and Atlantis to streamline infrastructure migrations, optimize costs, and implement GitOps workflows. This comprehensive guide covers security scanning, infrastructure analysis, and automated workflows for your Terraform deployments.

Dive into platform-specific implementations of Terraform pipelines! Learn how to set up and optimize Infrastructure as Code pipelines in Jenkins, GitLab CI, and CircleCI with detailed, production-ready examples.

Level up your Kubernetes skills! Learn about ConfigMaps, Secrets, resource management, and deployment strategies. Perfect for developers ready to move beyond the basics.

Discover how to build robust CI/CD pipelines for your Terraform code! This comprehensive guide covers pipeline design principles, security considerations, and best practices for automating infrastructure deployments safely and efficiently.

Level up your Terraform workflow with advanced tooling! Learn how to use Terragrunt for DRY configurations, implement pre-commit hooks for code quality, set up automated testing, and explore enterprise-grade features. Essential knowledge for maintaining large-scale Terraform deployments.

Explore OpenTofu, the community-driven fork of Terraform! Learn everything about migrating from Terraform, key differences between the tools, and how to maintain compatibility while ensuring your infrastructure remains truly open source.

Scale your infrastructure with advanced Terraform concepts! Dive deep into creating reusable modules, managing multiple environments with workspaces, and implementing robust state management strategies. Essential knowledge for managing enterprise-level infrastructure deployments.

Take your Terraform skills to the next level! Learn how to write flexible and reusable configurations using variables, outputs, and data sources. Discover best practices for structuring your Terraform projects and managing different environments effectively.

Start your Infrastructure as Code journey with Terraform! This beginner-friendly guide covers installation, basic concepts like providers and resources, and walks you through creating your first Terraform configuration. Perfect for DevOps engineers and cloud practitioners looking to automate their infrastructure deployment.

Master the most important Linux commands for DevOps and system administration. A comprehensive guide covering file operations, process management, networking, monitoring, and automation.

Explore the intricate architecture of Kubernetes, from control plane components to worker nodes. Learn how each component works together to orchestrate your containerized applications.

Learn how to use Helm to manage Kubernetes applications. From basic concepts to creating your own charts, discover how Helm simplifies application deployment and management in Kubernetes.

Master Azure CLI with this comprehensive command reference. Includes practical examples for managing resources, VMs, AKS, storage, and more. Perfect for DevOps engineers working with Azure!

A comprehensive collection of essential AWS CLI commands for DevOps engineers. Includes practical examples and use cases for EC2, S3, ECS, Lambda, and more!

Take your Ansible skills to the next level with roles, variables, and templates. Learn how to create reusable and flexible automation for complex deployments.

Learn the fundamentals of Ansible automation with a practical example of configuring web servers. Perfect for beginners starting with infrastructure as code.

Master advanced Ansible features with custom modules, dynamic inventory management, and complex orchestration patterns. Ideal for enterprise-level automation.

Start your Kubernetes journey with Kind (Kubernetes in Docker). Learn how to set up a local cluster, understand core concepts, and deploy your first application in under an hour!

Discover how to leverage GitHub Actions for your CI/CD needs. This guide covers setup, pricing tiers, best practices, and advanced features to help you automate your development workflow effectively.

Learn how to build a real-world CI/CD pipeline using GitHub Actions. This practical guide covers building, testing, deployment, manual approvals, and securing your workflow with GitHub Secrets.

A thoughtful exploration of what AGI and ASI might mean for humanity, examining both the potential benefits and risks of superintelligent AI systems.

A comprehensive look at AI safety concerns, from current challenges to future risks, with practical approaches to building safer AI systems.

Learn how Mixture of Experts (MoE) works like a team of specialists, each handling what they do best, to solve complex problems.

Discover how Chain of Thought prompting helps AI break down complex problems into simple steps, just like humans do.

Dive into the world of neural networks and deep learning, from basic concepts to practical implementation, with clear examples and intuitive explanations.

Learn why accuracy alone isn't enough and discover the key metrics for properly evaluating machine learning models.

Discover how to transform raw data into meaningful features that improve your model's performance, with practical examples and best practices.

Learn how to properly validate your machine learning models and avoid the pitfalls of overfitting.

A complete guide to moving your Jekyll blog from GitHub Pages to Netlify, with tips for DNS configuration, deployment settings, and maintaining your blog's functionality.

Learn how unsupervised learning algorithms discover hidden patterns and group similar items together, with real-world examples and applications.

Explore how machines learn through trial and error, just like humans do, with practical examples from gaming to robotics.

Understand how regression works in machine learning through practical examples, from predicting house prices to estimating sales.

Discover how classification in machine learning works through simple examples, from email spam detection to image recognition.

A beginner-friendly introduction to machine learning concepts, explained with real-world examples and minimal technical jargon.

A comprehensive guide to running Jenkins in Docker, with a focus on easy setup, security, and maintainability. Includes a custom installation script and best practices for DevOps teams.

Learn about data cleaning, deduplication, and how to split your data properly to build effective machine learning models.

Learn how to set up a complete Azure development environment on macOS using Python, including authentication methods, CLI tools, and best practices for development.

A comprehensive guide to understanding, installing, and using ArgoCD for GitOps workflows, including troubleshooting tips and CLI commands.

Discover how to deploy Python serverless functions on Netlify's generous free tier instead of paying for AWS Lambda or Azure Functions. Perfect for hobby projects and MVPs!

Build your own AI chatbot on free-tier services: Learn how to create a chatbot using Netlify Functions and Together AI's powerful models in just 4 hours, with minimal costs!

A step-by-step guide on creating a retro gaming-inspired scrolling header animation for your Jekyll blog using pure CSS and the Press Start 2P font.

Learn how to structure your prompts for better responses from AI. This guide covers techniques, examples, and common pitfalls so you can master the art of talking to machines.

Setting up this blog was simpler than you’d think — and completely free. Here’s how I did it:

I’ve used a lot of note-taking apps over the years, but none has felt quite as natural — or as powerful — as Obsidian.

Writing blog posts in Markdown is great. But what if you could write, version, and publish your posts to GitHub Pages — without switching apps or running Git commands?

Thoughts on AI Today – Why Persistence Matters

Retrieval-Augmented Generation (RAG) is a powerful technique that combines the strengths of large language models with external knowledge sources. In this post, we'll build a complete local RAG system using Ollama, Python, and a few PDFs. You'll learn how to index documents, enhance a model with your data, and create a simple GUI for interactive searching.

Retrieval-Augmented Generation (RAG) is a powerful technique that combines the strengths of large language models with external knowledge sources. In this post, we'll build a complete local RAG system using Ollama, Python, and a few PDFs. You'll learn how to index documents, enhance a model with your data, and create a simple GUI for interactive searching.