- Isolation and compliance: Keep teams, environments, or regions separate to meet security and governance requirements.
- Performance and scale: Allocate resources independently and scale data planes without affecting control-plane availability.
- Cost and ownership: Attribute spend to the teams or business units that own each data plane.
- Reliability boundaries: Limit the affected area of failures and define clear service level objectives (SLO) per cluster.
- Network boundaries and residency: Keep data within specific networks or geographies.
Example
A company operates a single APC control plane and two data plane clusters at the same organization:- Finance data plane cluster: Runs Airflow for data reconciliation and reporting with restricted network access and stricter compliance controls.
- Engineering data plane cluster: Runs Airflow for product analytics and machine learning feature pipelines with more flexible networking.
How the control plane keeps track of a cluster
The control plane keeps a copy of each data plane cluster’s metadata, such as its Kubernetes version and chart versions. Starting in APC 2.2, each data plane sends this metadata over DP-Link, so changes reach the control plane within about 30 seconds. See Data plane metadata sync.Manage clusters
- Register a cluster: Register a data plane cluster.
- Data plane metadata sync: Learn how the control plane keeps a cluster’s metadata current, and which values the data plane owns.
- Override cluster configurations: Update data plane cluster details, like name, labels, connection settings, or credentials, and override cluster default Deployment configurations.
- Deregister a cluster: Deregister a data plane cluster you no longer need.
- Troubleshoot registration: Diagnose and resolve errors during data plane registration.