Notes from building and running the fleet — the CAD pipeline, the data modelling, the agent workflows, the infrastructure underneath. Curated: what is published is what happened.
Eliminate Lambda connection storms and achieve 30-second database failover with RDS Proxy. Production deployment guide with Terraform and monitoring.
Real performance differences between Java and Python in production: concurrency models, GC behavior, and when type safety prevents 2 AM incidents.
Docker and Helm solve different problems—images package applications, charts orchestrate deployments. Learn when you need each.
Replace Redis and S3 with NATS JetStream's built-in KV and Object stores for simplified cloud-native state management.
Evolve GitLab Runners from basic setup to production-grade auto-scaling with real cost analysis, executor trade-offs, and fleet management.
Operational trade-off analysis with runnable Go code showing where NATS and Kafka each break down under real cloud-native workload patterns.
An architectural decision framework comparing JetStream and Kafka across operational complexity, cloud-native fit, and delivery guarantees.
Migrate from ephemeral Core NATS to durable JetStream with production deployment patterns for cloud-native teams—without the Kafka overhead.
Build persistent, replay-capable messaging on NATS JetStream with durable consumers and production Kubernetes deployment via Helm.
Cut cloud logging costs by 85% with production-ready Loki architecture. Real deployment patterns for 100GB+ daily logs on Kubernetes.
A practical guide to evolving GitLab Runner infrastructure from a single server to an autoscaling multi-executor fleet handling thousands of jobs daily.
Transform Spark workloads from imperative spark-submit chaos into declarative, GitOps-ready deployments with Kubernetes Operators and CRDs.
Complete guide to designing secure, cost-effective ECR workflows for EKS with vulnerability scanning, lifecycle automation, and replication strategies
Battle-tested strategies for safe database migrations: expand-contract patterns, lock management, and rollback techniques that work at scale.
Deep dive into Spring Boot's auto-configuration mechanism. Learn how it works, debug issues, and take control when defaults don't fit.
Build a unified container pipeline from local Docker development to production Kubernetes using Rancher Desktop and Rancher Server.
Deploy Rancher to unify Kubernetes cluster management across EKS, GKE, and bare metal with production-ready RBAC, backups, and GitOps patterns.
A hands-on guide to migrating production workloads from Terraform to OpenTofu, covering state management, CI/CD updates, and provider compatibility.
Migrate from ClickUp to a custom kanban system with full AI integration, covering data export, schema design, and MCP server implementation for Claude Code workflows.
Master the kubectl workflows and muscle-memory commands that experienced engineers rely on for daily cluster operations, debugging, and incident response.
Compare Go's goroutines with .NET's async/await through real benchmarks, production case studies, and migration strategies for high-concurrency systems.
Combine GitLab Agent and Rancher Fleet to manage deployments across multiple Kubernetes clusters with unified observability and drift detection.
Implement pull-based GitOps deployments across multiple Kubernetes clusters using GitLab CI/CD, Rancher Fleet, and the GitLab Agent.
A production-ready AKS blueprint built from real failures: security hardening, cost optimization, and operational patterns for Azure Kubernetes.
Master async patterns and performance optimization for FastAPI apps serving high-traffic workloads in production.
Explore how Claude Code and Model Context Protocol (MCP) servers transform software development with AI-powered code generation, task management, and persistent memory.
Migrate from Airflow to Dagster with an asset-centric approach that transforms debugging and testing.
A weighted scoring framework with Terraform examples for platform teams choosing between AWS EKS and Google GKE.
A migration-focused comparison of EKS and GKE examining real switching costs and operational trade-offs for production Kubernetes workloads.
Learn to build Kubernetes-native event pipelines with Argo Events. Connect GitHub webhooks to automated workflows using EventSources, Sensors, and EventBus.
Learn to deploy multi-cluster ML inference using KServe, vLLM, and Karmada for scalable, resilient model serving across regions.
A systematic guide to identifying and eliminating gRPC latency bottlenecks with measurable benchmarks and production-tested configurations.
Create living documentation using Neo4j knowledge graphs to map repository relationships, service dependencies, and API connections across complex codebases.
Production-ready asyncio patterns for debugging silent failures, structured concurrency, graceful shutdowns, and testing async Python code.
Use the Sequential Thinking MCP server to break down complex problems into structured reasoning chains, enabling better debugging, architecture decisions, and research workflows.
Implement secure secrets management using Infisical, an open-source platform for managing API keys, database credentials, and environment variables across development and production.
Design patterns for implementing Auth0 authentication across multiple frontend applications with shared backend services and role-based access control.
Master the art of aggregating data from multiple external APIs with proper error handling, rate limiting, caching, and response normalization strategies.
Design scalable image storage solutions using Supabase Storage, with bucket organization, access policies, image transformations, and CDN optimization.
Build interactive web-based 3D CAD viewers using Three.js, supporting STL, glTF, and STEP formats with optimized performance for engineering models.
A practical comparison of Prisma and Drizzle ORMs for TypeScript projects, covering schema design, query building, migrations, and performance trade-offs.
Build persistent design memory for CAD projects using Neo4j graph database to track component relationships, design decisions, and constraints across sessions.
Learn when and how to migrate session storage from Redis to PostgreSQL, reducing infrastructure complexity while maintaining performance for moderate-scale applications.
Create professional command-line interfaces for CAD automation using Python Click, with subcommands, rich output formatting, and shell completion.
Design robust equipment categorization systems using canonical name mapping, fuzzy matching, and hierarchical taxonomies for fitness applications.
Learn how to use PartCAD as a package manager for CAD components, accessing thousands of standardized parts like fasteners, motors, and electronics through a unified API.
Design adaptive fitness program algorithms that automatically adjust training variables based on user progress, implementing progressive overload and periodization strategies.
Build adapters for the cq_electronics library to integrate Raspberry Pi, connectors, and other electronic components into your parametric CAD workflow.
Build intelligent exercise selection systems that respect equipment availability, balance muscle group coverage, and personalize recommendations based on user goals and history.
Implement robust geometry validation for parametric CAD models to ensure 3D printability, CNC compatibility, and assembly correctness using CadQuery and Open CASCADE.
Design database schemas and algorithms for tracking muscle activation patterns across exercises, enabling balanced workout recommendations and progress analysis.
Learn how to create a unified registry pattern to manage multiple CAD component sources in Python using CadQuery and PartCAD.
Learn data engineering patterns for aggregating exercise data from multiple APIs and datasets, handling inconsistencies, and building a normalized fitness database.
Discover CadQuery, a Python framework for creating parametric 3D CAD models, and explore the rich ecosystem of editors, plugins, and tools built around it.
A detailed guide to creating a hybrid Kubernetes cluster, incorporating script content and explaining each step in depth.
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