Openshift Row-Level Security (RLS)

A query hits your database. You don’t trust every eye that will see the rows.

Openshift Row-Level Security (RLS) is the control that decides who sees what. It filters data based on rules. It enforces those rules at the database layer, not in the application code. That means your policy is not optional. Even if a developer forgets to add a WHERE clause, the database still guards the rows.

RLS on Openshift starts with the database engine. PostgreSQL supports CREATE POLICY commands to define visibility. You bind these policies to roles. You define conditions that check user IDs, tenant IDs, or other attributes. Once set, every query obeys the policy. Insert, update, select—every statement is filtered.

Deploying row-level security in Openshift is about isolation and automation. You run your database in a container or cluster on Openshift. You configure RLS in the database schema itself. You keep the logic in version control. When your CI/CD pipeline deploys to Openshift, the database inherits the policies without manual steps.

Common RLS patterns in Openshift clusters:

• Multi-tenant SaaS: each tenant sees only its own rows.
• Team-based access: team_id column matches the logged-in user’s team.
• Compliance enforcement: block or mask sensitive data unless policy allows.

Combine RLS with Openshift secrets and service accounts. Map application roles to database roles with strict bindings. Keep policy checks simple and fast—avoid complex joins that slow every query. Monitor query plans to ensure RLS is not adding hidden overhead.

Securing data at the row level inside an Openshift environment stops leaks before they happen. It gives you a clear, repeatable, container-native way to enforce privacy.

You can see row-level security in action without touching production. Try it at hoop.dev and deploy a live Openshift RLS demo in minutes.