Metering leverages a SQL database called Presto. Presto does not store the data itself. Instead, its storage is decoupled from it, often in the form of object storage. This means at a minimum you need to configure persistent storage to hold reporting data, and the Hive metastore to hold metadata about database tables managed by Presto and Hive.
Metering requires the following components:
A StorageClass for dynamic volume provisioning. Metering supports a number of different storage solutions.
4GB memory and 4 CPU cores available cluster capacity and at least one node with 2 CPU cores and 2GB memory capacity available.
The minimum resources needed for the largest single Pod installed by metering are 2GB of memory and 2 CPU cores.
Memory and CPU consumption may often be lower, but will spike when running reports, or collecting data for larger clusters.