intermediateCaching — Second-Level Cache, Query Cache & Redis

Why is an in-process cache like EHCache or Caffeine risky in a multi-instance deployment?

Each application instance holds its own separate copy of the cache — an update on one instance doesn't invalidate another instance's stale cached copy, since there's no shared state between them. A distributed cache like Redis solves this by giving every instance a single shared view.

This is a Pro chapter

Sign in, then upgrade to Pro or Power to unlock this and the full Spring Ecosystem Mastery library.

Why is an in-process cache like EHCache or Caffeine risky in a multi-instance deployment?

Next Step

Continue to Why can Hibernate's query cache be less effective than expected on a frequently-written table?← Back to all Spring Data JPA & Hibernate Mastery questions