How do we handle caching and performance optimization?

[khamidkhanov-7]

With growing traffic, caching strategy matters.
Should we integrate Redis or use built-in caching at the ORM/API layer?

[khasanbayev-7]

Great question — caching can dramatically improve performance if designed thoughtfully.

Here’s a quick breakdown:

🔹 Built-in ORM/API caching

✅ Easy to implement (no extra infra).

✅ Works well for lightweight projects or single-node setups.

⚠️ Limited flexibility — cache invalidation and TTL control can be tricky.

⚠️ Doesn’t scale well if you add multiple backend instances.

🔹 Redis-based caching

✅ Centralized, fast (in-memory), and scalable.

✅ Supports fine-grained control (per-query, per-endpoint, or custom TTLs).

✅ Ideal for distributed environments and API-heavy workloads.

⚠️ Requires additional setup, hosting, and monitoring.

💡 Recommendation:

If you’re starting to see increased concurrent traffic or repeated queries, Redis is worth integrating — especially for session storage, rate limiting, and API-level caching.

For smaller teams or simpler apps, ORM-level caching is fine short-term, but plan for Redis as traffic continues to grow.

Bonus tip:
Combine both — use ORM caching for micro-level optimization and Redis for global cache + invalidation control.