REST APIs from the Inside
Between the TCP socket and your handler, a REST framework does a surprising amount of work: routing, method dispatch, deserialization, validation, and middleware. This video traces one request through every stage and shows where the time actually goes, including the reflection cost hidden inside JSON decoding.
Topics covered:
- The request lifecycle from socket to handler
- Routing and method dispatch inside the framework
- Deserialization: JSON to structs and reflection cost
- Validation: where it runs and what it protects
- Middleware order: auth, logging, and timeouts
- Response encoding and connection reuse
Related articles
WebSocket vs SSE vs Polling: Real-Time Transport Compared
WebSocket frames, SSE event streams, and HTTP polling compared: latency, bandwidth, server costs, keepalives, and the case where each is the right answer.
REST vs gRPC vs GraphQL: Choosing Your API
The real tradeoffs between API protocols: serialization overhead, streaming, type safety, and tooling for each approach.
Connection Pools Aren't Free
Pool sizing, exhaustion, idle connections, and the hidden queue — why 'just add a pool' is incomplete advice.
More in Backend Engineering
Pagination Strategies
Offset, keyset, and cursor pagination compared by database cost, consistency, and behavior when rows are inserted mid-page.
DetailsCaching for the Service Layer
Service-layer caching done right — cache keys, invalidation, TTLs, and the stampede problem that brings services down.
DetailsWebhooks vs Polling
Webhooks and polling compared at the delivery level — delivery guarantees, retries, and when push is worse than pull.
DetailsDatabase Transactions in Practice
ACID in a real database — write-ahead logs, locks, undo and redo, plus isolation levels and what they change about reads.
DetailsRate Limiting Algorithms, Visualized
Token buckets, leaky buckets, and sliding windows compared by memory, precision, and what they do under burst load.
DetailsAPI Idempotency Keys
How idempotency keys work at the storage level — dedupe tables, unique constraints, and making retries safe for clients.
DetailsBackground Job Processing
Queues, workers, and retries — how background jobs actually execute, from enqueue to acknowledgment, and why they fail.
DetailsMessage Queues in Practice
Brokers, producers, and consumers — what a queue does at the protocol level and why it decouples services from availability.
DetailsConnection Pooling Explained
What a connection pool actually does — the handshake cost it hides, checkout and release mechanics, and how pool size changes latency.
DetailsDepth, delivered weekly
One technical dispatch a week — articles and episode notes before they go public.
One technical dispatch per week. No noise.