Cloud computing fundamentals and best practices
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Interviews for cloud engineering roles have shifted from "what is a virtual machine" to "design a multi-region disaster recovery architecture with sub-15-second RTO." This post covers 50 questions across three difficulty levels with concise answers and key CLI commands. Whether you are preparing for your first cloud role or aiming for a senior architect position, these questions reflect what real hiring managers actually ask.
Your application works fine with 100 users. At 10,000 users, pages load slowly. At 100,000 users, the database falls over. Performance at scale isn't about buying bigger instances — it's about putting data closer to users, caching aggressively, and removing bottlenecks at every layer. AWS has purpose-built services for each layer of the stack, and knowing when to use which one is what separates a system that scales gracefully from one that catches fire.
Your application works. It passes all tests. Then it goes live and users in Singapore see three-second load times, your database CPU sits at 85% from repeated identical queries, and your static assets are served from a single region. Performance is not a feature you bolt on later — it is an architecture decision you make early. Azure offers a full stack of acceleration services, from edge CDN caching to in-memory data stores to global load balancing. Here is how to use each one and when they overlap.
87% of machine learning models never make it to production. Not because the models are bad, but because the gap between a Jupyter notebook and a reliable production system is enormous. MLOps bridges that gap by applying DevOps principles to the ML lifecycle. Meanwhile, AIOps flips the script — using AI to make operations smarter. Together, they represent the frontier of modern DevOps.
Single point of failure = guaranteed downtime. Your app might be perfect, your code might be clean, but if it runs on one server and that server dies at 3 AM, your customers see a blank page. High availability isn't optional for production -- it's the minimum bar. Let's build infrastructure that survives server failures automatically.
Your company started with one AWS account. Then someone needed a dev environment, so you made a second. Then staging. Then a sandbox for the data team. Now you have twelve accounts, each with different IAM policies, no consistent logging, and a security audit that makes everyone nervous. A landing zone is the fix — it's the foundational structure that makes multi-account AWS actually manageable instead of chaotic.