Connection Pool

Prerequisite: Part 4 of the System Design Masterclass. Read Part 3: Caching Strategies to understand the cache layer before examining storage. Answer-first: Database sharding distributes data horizontally across independent partitions (shards) based on a shard key, reducing write contention and enabling linear storage growth. Choosing the wrong shard key leads to hot spots that can be worse than no sharding at all. Vertical vs Horizontal Scaling — When to Switch? Answer-first: Vertical scaling (scale-up) increases resources on a single server — simple but has a hard physical ceiling and non-linear cost growth. Horizontal scaling (scale-out) adds more servers — no theoretical ceiling, linear cost, but significantly higher operational complexity. ...

← Previous | Series hub | Next → Chapter 5: Unlocking Database Performance via Connection Pooling If your Golang system processes business logic blazingly fast but chokes at the Database layer, 90% of the time, it is due to an incorrectly configured *sql.DB. 1. Understanding *sql.DB Answer-first: In Golang, sql.Open() does NOT create a direct database connection. It instantiates a thread-safe Connection Pool manager. You must initialize the db variable only once during app startup. ...