Software Engineer Interview Prep Podcast

Senior system design interviews don't test whether you know what a load balancer is. They test how you think under pressure: how you handle ambiguity, weigh brutal trade-offs and defend every box you draw. In this deep dive we unpack the framework used to evaluate senior engineers, architects and principal candidates.You'll learn:- The RADIO framework (Requirements, API, Data model, Infrastructure, Optimize) and how to split your 45 minutes- The one question that instantly signals seniority- REST vs gRPC, API versioning, and why offset pagination breaks at scale- Choosing a database by access pattern, and justifying every component with the NFRs- Why skipping non-functional requirements is the number one reason senior candidates fail- Peak vs average TPS, P99 tail latency, latency budgets, RPO and RTO, and compliance- Sticky sessions, sharding, hot shards, read replicas, CQRS and event streaming- The math of the nines, active-active vs active-passive, circuit breakers, bulkheads and graceful degradation- Exponential backoff with jitter to survive the thundering herd- The CAP theorem, the consistency spectrum, and why banks must choose CP to prevent double spendingChapters00:00 Introduction00:49 They test judgement, not definitions02:22 The roadmap03:36 The RADIO framework04:47 Requirements in five minutes06:00 The seniority signal06:47 API design and versioning08:20 Offset vs cursor pagination09:05 Choosing the data model10:18 Justifying infrastructure with NFRs11:28 Network boundaries11:50 Attacking your own design12:39 Observability and cost14:37 The URL shortener trap15:23 The NFR cheat sheet15:46 Peak vs average traffic16:33 Tail latency and fan-out17:44 Latency budgets19:16 RPO and RTO20:02 Compliance: GDPR, PCI DSS, SOX21:37 Scaling out and sticky sessions23:13 Sharding and the hot shard24:49 Cross-shard query trade-offs25:58 Read replicas and replication lag27:08 CQRS28:41 Event streaming and idempotency31:02 The nines of availability33:04 Active-active vs active-passive34:37 Circuit breakers36:09 Bulkheads37:18 Graceful degradation38:26 Thundering herd, backoff and jitter40:25 The CAP theorem43:09 The consistency spectrum45:32 The FinTech exception: double spending47:05 Why a rejected transaction beats a duplicate48:13 Recap: every design is a trade-off49:23 Final thought#SystemDesign #SoftwareEngineering #DistributedSystems #InterviewPrep #TechInterviews #SoftwareArchitectureInterview Prep Podcast

A single misconfigured setting in Kafka doesn't just slow a page down. It can silently vaporize financial transactions. In this deep dive we walk through real production failure scenarios and the exact reasoning interviewers look for in staff-level system design interviews.You'll learn:- Why acks=1 loses data, and the four configuration layers for zero data loss- Consistency vs availability: why a healthy cluster refuses writes on purpose- Pushing from 400,000 to 2 million events/s with batching, linger.ms and compression- How retries reorder a debit and a credit, and how idempotent producers fix it- Rebalance storms, cooperative sticky assignment and static membership- Hot partitions and the irreducible trade-off between ordering and scale- How deleting and recreating a topic silently skips hours of data- A 3 AM role-play: 85 under-replicated partitions, a disk at 96%, and why you never restart the broker- Exactly-once with Kafka transactions, and exactly-once into PostgreSQL- Tiered retry topics and dead letter queues- Split brain, KRaft quorums and vanishing tombstones- System design at scale: multi-tenant topics, quotas, event-driven sagas and change data capture with DebeziumIdeal for backend and platform engineers preparing for senior and staff-level interviews.Chapters00:00 Distributed systems have no X-ray01:08 Why Kafka interviews matter02:19 acks=1 and the 200 missing payments03:27 Four layers of zero data loss05:21 The CAP theorem trade-off06:31 Throughput: taxis vs buses07:42 batch.size, linger.ms and compression09:38 When retries reorder messages11:38 Idempotent producers12:48 Message keys and partition ordering13:12 Flash sale: buffer exhausted14:22 Decoupling with a local buffer and circuit breaker16:18 Rebalance storms18:13 Eager vs cooperative sticky rebalancing19:25 Static group membership20:12 Hot partitions and the hot key problem23:18 Silent data loss after recreating a topic25:20 auto.offset.reset and topic versioning26:08 3 AM: 85 under-replicated partitions28:54 Why you never restart the broker29:42 Disk at 96%: the 15-minute response31:36 Throttled reassignment, Cruise Control, tiered storage33:36 Duplicates in consume-transform-produce34:47 Kafka transactions37:11 Exactly-once into PostgreSQL39:56 Head-of-line blocking from retries41:08 Tiered retry topics and DLQs42:42 Split brain44:38 KRaft and quorum math45:27 Log compaction tombstones48:33 Multi-tenant topic design50:07 Tenant tiers and client quotas51:40 Event-driven sagas53:15 Compensating transactions54:51 Change data capture with Debezium57:13 Recap58:46 Will offsets still matter in five years?#Kafka #SystemDesign #DistributedSystems #SoftwareEngineering #InterviewPrep #BackendEngineeringInterview Prep Podcast

Why does a chat message arrive instantly, but the web was never built for it? In this deep dive we unpack WebSockets: how engineers turned a request/response web into an open, two-way line, and what that costs at scale.You'll learn:- Why short polling, long polling and Server-Sent Events fall short (and the math behind 200,000 empty requests per second)- How the WebSocket handshake hides inside a normal HTTP request, and the "cryptographic high-five" that proves the server understood- Why clients mask every frame but servers never do, and the cache-poisoning attack it prevents- Half-open connections, idle timeouts and why heartbeats every 20–30 seconds keep sockets alive- Close code 1006, the "ghost code" every system design candidate should know- The real cost of state: 1 million connections × 20 KB = 20 GB of RAM before a single message- Gateways, pub/sub buses, the thundering herd, and exponential backoff with full jitter- Cross-site WebSocket hijacking, and why tokens never belong in the URL- When NOT to use WebSockets: SSE vs WebSockets vs gRPC- Head-of-line blocking and why QUIC and WebTransport may be nextPerfect for software engineers preparing for system design interviews.Chapters00:00 Intro: the web wasn't built for real time02:19 Short polling and the 200,000 requests/second problem03:54 Long polling04:42 Server-Sent Events05:31 WebSockets and full-duplex communication06:19 The handshake: disguised as HTTP07:55 Sec-WebSocket-Accept: the cryptographic high-five09:05 Why clients mask frames09:53 Cache poisoning explained11:50 Half-open connections12:38 Idle timeouts at every network hop13:47 Heartbeats: Ping and Pong14:36 Close code 100615:23 The cost of state16:57 Scaling with gateways and pub/sub18:34 The thundering herd19:46 Exponential backoff with full jitter20:58 Cross-site WebSocket hijacking22:32 Ticket-based authentication23:45 When not to use WebSockets24:55 The big trade-off: latency vs statefulness25:43 Head-of-line blocking26:55 What's next: QUIC and WebTransport#SystemDesign #WebSockets #SoftwareEngineering #InterviewPrep #BackendEngineeringInterview Prep Podcast

The mental model and the toolkit come together here. We cover managing a session in real time — when to course-correct, when to clear and restart — the five failure patterns that quietly tank your work and how to fix each, and a complete worked problem run end to end: explore, plan, implement in a fresh session, verify with tests, and review with an adversarial subagent. Plus scaling techniques and exactly how to demonstrate competence when someone is watching you code.

This is where the deep technical interview questions live. Claude Code has five extension points — CLAUDE.md, skills, hooks, subagents, and MCP — and knowing which to reach for is a core competency. We break down each one: why CLAUDE.md is always-on context you must keep lean, how skills load knowledge on demand and why the description field decides everything, when hooks give you deterministic guarantees, how subagents isolate heavy work in their own context, and how MCP and CLI tools connect the outside world. Ends with the decision framework that ties them all together.