Keycloak Replication
You set up keycloak replication by linking multiple server nodes to a shared database. You also enable a distributed cache so nodes share user session states. Engineering teams build this setup to keep identity services online during server outages. Still, many admins grant broad database and server roles to set up these clusters. Broad permissions leave production systems open to mistakes and data exposure. How keycloak replication works in a cluster A single identity server creates a single
Keycloak + Database Replication Security: the complete guide
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You set up keycloak replication by linking multiple server nodes to a shared database. You also enable a distributed cache so nodes share user session states. Engineering teams build this setup to keep identity services online during server outages. Still, many admins grant broad database and server roles to set up these clusters. Broad permissions leave production systems open to mistakes and data exposure.
How keycloak replication works in a cluster
A single identity server creates a single point of failure for your team. If that machine stops working, nobody can log in to your apps. To fix this, teams run multiple server instances at the same time. These instances work together as a cluster to handle user traffic.
The cluster relies on two main layers to share data across nodes. The first layer is a shared relational database for permanent records. This database holds realms, users, roles, and client settings. Every node in the cluster reads from and writes to this central store.
The second layer is a distributed memory cache for fast state sharing. This cache tracks active user sessions, login failures, and short-lived tokens. When a user logs in on one node, the cache shares that session. If that node fails, another node reads the cache and keeps the user logged in.
Teams also place a load balancer in front of the server nodes. The load balancer routes incoming login requests to healthy nodes in the cluster. Nodes discover each other over the private network and sync cache updates. When you run clusters across data centers, nodes forward cache events over site links.
What keycloak replication solves and what it misses
Running a replicated identity cluster solves uptime and login scale problems. Your team gets central user management and steady single sign-on across apps. If one server crashes during peak hours, users still log in without issues. The setup verifies who a person is before granting a session token.
Still, an identity cluster only decides who can log in to a system. It does not control what engineers do inside databases or servers after login. Once an engineer authenticates, they often receive a full role on the target system. They can run raw queries or shell commands with no further checks.
Keycloak + Database Replication Security: architecture patterns and best practices
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Maintaining the cluster itself also creates access risks for the platform team. Admins need direct access to the backing database to fix sync errors. If an admin runs a bad update query, that mistake hits every node right away. One wrong command can lock out users or expose sensitive tables.
Standard identity roles cannot inspect individual SQL statements or terminal commands in flight. They also cannot mask sensitive fields like emails, phone numbers, or card numbers in query results. Teams need controls that check every single command and rewrite sensitive fields in results.
Best practices for managing cluster operations
Start by separating admin access from daily user traffic on your network. Do not expose the admin console to the public internet under any circumstance. Route admin traffic through private networks and require strong multi-factor login checks.
Monitor the health of both your database and your memory cache. Network delays between nodes can break cache sync and log users out early. Keep all server nodes on the exact same software version during updates. Mixed versions in one cluster often cause cache errors and corrupted session data.
Finally, restrict how engineers interact with the backing database during maintenance. Replace broad database passwords with command-level checks and approvals for risky write queries. Masking rules should rewrite national IDs and card numbers in query outputs by default.
Govern statements and responses across databases and APIs
Good config and scoped roles are needed setup. They do not check single queries in flight or mask sensitive fields in returned rows. Across Postgres, MySQL, SQL Server, MongoDB, ClickHouse, Kubernetes APIs, SSH, and internal HTTP endpoints, hoop.dev runs beside each supported service as an open-source proxy, a sidecar for your database or API.
First, hoop.dev guardrails block banned queries before they run. Then hoop.dev data masking rewrites matched sensitive values in responses in memory. The audit trail records every statement and verdict per resource. Furthermore, hoop.dev holds SOC 2 Type II and is open source on GitHub.
Frequently asked questions
What data gets shared across a replicated Keycloak cluster?
Nodes share permanent records like users and roles through a shared relational database. They also share active login sessions and login failure counts through a distributed memory cache.
Do I need sticky sessions for my identity cluster?
Yes, sticky sessions on your load balancer improve speed by routing a user to the same node. If that node fails, the distributed cache lets another node take over the session.
Does identity replication protect the backing database from bad queries?
No, replication copies all data changes across the cluster right away, including bad writes. You need query-level controls and data masking to prevent accidental damage and data leaks.