Scalability is the turning point between a smooth identity layer and a bottleneck that chokes every other service. Keycloak can handle millions of requests, but only if you know how to scale it right. That means understanding where latency starts, how clustering works, and why persistence and cache performance decide everything.
The first wall many teams hit is database contention. Keycloak leans heavily on its database for user sessions, tokens, and state. If your DB is slow or poorly tuned, no amount of horizontal scaling will save you. Start with a high-performance Postgres cluster or equivalent, optimize connection pooling, and watch query plans. Database performance is your foundation.
Next comes clustering. Running multiple Keycloak nodes is simple. Running them well is not. You need a shared Infinispan cache that can keep up with authentication volume. Misconfigured caches turn into hotspots and stale sessions. Tune eviction policies and replication strategies for your workload profile. Make sure inter-node communication is fast and predictable.
Session handling is where scalability strategies diverge. Some architectures push for long session lifetimes to cut down on token refreshes. Others go short to reduce memory pressure. Both work—until your real traffic patterns and compliance needs set the rules. Measure. Adjust. Repeat. High availability is meaningless if user logins lag by seconds.
API endpoints and service integrations bring another scaling challenge. OAuth and OpenID Connect flows are chatty by nature. Under load, small timeout misalignments cascade into queues. Control them. Keep endpoints behind a fast ingress. Terminate TLS close to the node. Use health checks that reflect true node capacity, not just "up"status.