Most teams manage their application infrastructure as code but still create databases by clicking through a dashboard. The database becomes the one piece of production infrastructure that has no audit trail, no PR review, and no reproducible setup. When someone asks "why is the production database on tier-4 instead of tier-6?" the answer is usually "someone changed it last year."

The FoundryDB Terraform provider closes that gap. You declare your database services, users, and firewall rules in HCL, version them in git, and apply changes through the same CI/CD pipelines you use for everything else.

Most applications hit a performance wall that has nothing to do with their code. The database query that takes 50ms works fine until you are serving 10,000 requests per minute and your connection pool is saturated. Adding an in-memory caching layer drops that response time to under a millisecond and takes the read load off your primary database.

Valkey is the open-source, Redis-compatible in-memory data store that the community rallied behind after Redis changed its license in 2024. It is wire-compatible with Redis, which means your existing Redis clients, libraries, and tooling work without modification. No license concerns, no vendor lock-in, and active development under the Linux Foundation.

This guide walks through provisioning a managed Valkey instance on FoundryDB and implementing common caching patterns in Python, Node.js, and Go.