Shalini maps system design essentials
- Shalini Goyal pulled core system design topics into one interview-prep map, spanning CAP and PACELC trade-offs, SQL versus NoSQL, sharding, replication, and APIs. - Her course outline pairs fundamentals with production patterns: rate limiting, secure APIs, leader election, unique ID generation, and fault-tolerance decisions at scale. - Simon Willison’s agent notes push the same lesson toward operations: isolate credentials, expect prompt injection, and design backups. (simonwillison.net)
Distributed systems look abstract until a service fails, a database lags, or a retry creates two payments instead of one. Shalini Goyal’s recent system design outline starts with those trade-offs. (maven.com) Her course description groups the basics the way interviewers usually do: consistency versus availability, SQL versus NoSQL, synchronous versus asynchronous work, and the choice between REST, secure APIs, and other interface patterns. (maven.com) The database section goes past buzzwords. Goyal lists ACID versus BASE, sharding, replication, and CAP and PACELC, which are the rules engineers use to explain what a system gives up when networks split or latency rises. (maven.com) That is the heart of system design: every large service is a set of compromises. A team can make reads fast with caches and replicas, but then has to explain stale data, failover behavior, and how much inconsistency users will tolerate. (maven.com) (grokkingsystemdesign.com) The same logic applies to traffic flow. Message queues and event-driven systems move work out of the request path, but they add delivery semantics, retries, and ordering problems that have to be designed on purpose. (grokkingsystemdesign.com) Reliability work starts where interview diagrams usually stop. Idempotency means a repeated request has the same effect as one request, which is how teams prevent duplicate charges, duplicate jobs, or duplicate messages when systems retry after errors. (nnode.ai) Observability is the other half. Service Level Objectives, or SLOs, turn “keep it reliable” into a number, and error budgets tell teams when outages have consumed the month’s room for risky deploys. (backendbytes.com) Simon Willison has been making the same point from the agent side. In his March 14, 2026 notes for The Pragmatic Summit talk, he framed coding agents as systems that need testing, validation, and operational controls, not just better prompts. (youtube.com) (simonwillison.net) His security warning is narrower and sharper: agents become dangerous when they combine private data, untrusted content, and outside communication. That is why credential isolation, scoped access, and recovery plans matter as much as model quality. (hiddenlayer.com) (simonwillison.net) Put together, the interview checklist and the reliability checklist describe the same job. Engineers still need to explain how data is partitioned, how requests are routed, how failures are traced, and what the system is allowed to touch when it goes wrong. (maven.com) (backendbytes.com) (hiddenlayer.com)
