Advertising dashboards are read-heavy, bursty, and expensive to compute. A single page can ask for spend, sales, ACOS, ROAS, campaign status, budget pacing, placement breakdowns, and search-term trends. Without caching, the database becomes the place where every product decision is paid for repeatedly. The hard part is not adding Redis. The hard part is deciding what can be cached, for how long, and how to invalidate it when advertisers expect fresh numbers. Cache Data Products, Not SQL Rows A common mistake is caching low-level query results. That leaks implementation details into the cache and makes invalidation painful. I prefer caching data products: the exact response shape used by the dashboard card or API endpoint. type DashboardCacheKey struct { CompanyID int64 ProfileID int64 DateRange string Marketplace string Card string Version int } The `Version` field is important. When the calculation changes, bump the version and old entrie...