Deep dives into system architectures, complex bug fixes, and lessons learned while building scalable software.
What I learned building a production AI observability platform - from 1-line SDK design to hallucination detection, compliance architecture, and the hard tradeoffs between latency, cost, and safety.
Honest cost breakdowns for building a SaaS MVP in India — from landing pages to full platforms — with real project examples, tech stack decisions, and what actually drives the price.
Hiring a frontend developer, a backend developer, and a DevOps engineer for your MVP is expensive and slow. Here is why one experienced full-stack developer can ship faster, cheaper, and better — with real architecture examples.
Moving from a VPS to AWS is not just a hosting change — it is an architecture decision. Here is a practical guide to migrating startups to AWS, with real cost comparisons, serverless patterns, and lessons from production.
Manual cloud cost optimization is tedious and error-prone. Here is how I built an AI-powered pipeline that analyzes AWS infrastructure, computes health indices, and generates safe optimization recommendations — saving 35% on cloud spend.
Cold starts, connection pooling, IAM lockdowns, and event-driven architectures. Here is a battle-tested guide to scaling serverless applications.
How I built a pipeline that aggregates AWS resource usage metrics, computes cloud health indices, and leverages LLMs to propose safe cleanup recommendations without breaking production.
Why secret sprawl happens and how I designed a zero-knowledge local environment variable locker and synchronizer using Node.js, PBKDF2 key derivation, and AES-256-GCM.
Building an uptime monitor is easy; scaling one to check thousands of URLs, detect DNS drift, and parse SSL certifications dynamically with custom DNS overrides is not. Here's the engineering breakdown.
Traditional logging told me the API call succeeded, but the logic inside my agent failed. Here is how I built an observability tool to trace reasoning chains.