Cerbos deployment patterns
This documentation is for a previous version of Cerbos. Choose 0.39.0 from the version picker at the top right or navigate to https://docs.cerbos.dev for the latest version. |
Cerbos can be deployed as a service or as a sidecar. Which mode to choose depends on your requirements.
Service model
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Central policy decision point shared by a group of applications.
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Cerbos can be upgraded independently from the applications — reducing maintenance overhead.
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In a busy environment, careful capacity planning would be required to ensure that the central Cerbos endpoint does not become a bottleneck.
Sidecar model
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Each application instance gets its own Cerbos instance — ensuring high performance and availability.
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Upgrades to Cerbos would require a rolling update to all the application instances.
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Policy updates could take slightly longer to propagate to all the individual application instances — resulting in a period where both the old and new policies are in effect at the same time.
DaemonSet model
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Each cluster node gets its own Cerbos instance — ensuring high performance and efficient resource usage.
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Policy updates must roll out to nodes individually — resulting in a period where both the old and new policies are in effect at the same time.
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When deployed as a daemonset the service
internalTrafficPolicy
defaults toLocal
. This causes all requests to the service to be forced to the local node for minimum latency. Upgrades to Cerbos could result in application seeing a short outage to the cerbos instance on their own node, client retries may be neccessary. If this is unacceptable you can setservice.internalTrafficPolicy
toCluster
. You may be able to improve availability via theservice.kubernetes.io/topology-mode: Auto
annotation.