System design practice can become a collection of memorized diagrams. A better target is a repeatable decision process that still works when the prompt changes.
The 30-day HLD Practice roadmap begins with requirements and capacity, then covers load balancing, consistent hashing, consensus, storage, queues, caching, and rate limiting. These are not boxes to include by default. They are tools whose value depends on scale, failure behavior, and the contract the system must keep.
The first week isolates primitives. Designing a load balancer, hash ring, or leader election mechanism in a small exercise makes its assumptions visible. The second week connects distributed components behind the request path. Queue boundaries, storage choices, and real-time messaging now have to work together.
The second half uses full cases: news feed, video streaming, ride sharing, collaborative editing, search, and RAG. A 45-minute answer needs an order. Start by classifying functional and non-functional requirements. Estimate the dominant read, write, storage, and bandwidth dimensions. Choose an initial data model and request path. Then find the bottleneck or failure mode that justifies the next component.
The useful practice happens in the explanations between boxes. Why is this write asynchronous? Which operation needs strong consistency? What becomes stale? Where can an idempotency key stop a duplicate? What metric tells the operator that the design is failing?
A credible interview design is not the one with the most infrastructure. It is the smallest design that meets the stated load and explains how it degrades.
The complete roadmap is at https://learn.significanthobbies.com/curriculum/roadmaps/hld-practice.
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