Blog
Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
Architecture Review: Linux Performance Baseline Methodology
Linux Performance Baseline Methodology. Practical guidance for reliable, scalable platform operations.
Fine-tuning vs Few-Shot Learning: When to Use Each Approach
Compare fine-tuning and few-shot learning for adapting LLMs. Learn when to use each approach and their trade-offs in terms of cost, performance, and complexity.
Architecture Review: Cloud Disaster Recovery Runbook Design
Cloud Disaster Recovery Runbook Design. Practical guidance for reliable, scalable platform operations.
AI Observability and Monitoring: Tracking Model Performance in Production
Learn how to monitor AI models in production. Track performance, detect drift, and ensure model reliability with comprehensive observability strategies.
Architecture Review: AWS Cost Control with Tagging and Budgets
AWS Cost Control with Tagging and Budgets. Practical guidance for reliable, scalable platform operations.
Multi-Agent AI Systems: Building Collaborative AI Applications
Learn how to build multi-agent AI systems where multiple AI agents collaborate to solve complex tasks. Architecture patterns and implementation guide.
Architecture Review: Ansible Role Design for Large Teams
Ansible Role Design for Large Teams. Practical guidance for reliable, scalable platform operations.
Prompt Engineering Best Practices: Maximizing LLM Performance
Master prompt engineering techniques to get better results from LLMs. Learn about few-shot learning, chain-of-thought, and advanced prompting strategies.
Architecture Review: Terraform State Isolation by Environment
Terraform State Isolation by Environment. Practical guidance for reliable, scalable platform operations.
AI Model Deployment Strategies: From Development to Production
Complete guide to deploying AI models in production. Learn about model serving, containerization, scaling, and monitoring strategies.
Model Quantization Techniques: Reducing LLM Size and Cost
Learn how to reduce LLM model size and inference costs using quantization techniques like Q4, Q8, and GPTQ. Practical guide with benchmarks.
Architecture Review: GitHub Actions Pipeline Reliability
GitHub Actions Pipeline Reliability. Practical guidance for reliable, scalable platform operations.