We have apps like this, also. For straight Cassandra, I think it is just the nature of how it works. DataStax provides some interesting solutions in different directions: BigNode (for handling 10-20 TB nodes) or Astra (cloud-based/container-driven solution that DOES separate read, write, and storage into separately scaled aspects of Cassandra). I suppose that you could do some similar work on your own with k8cassandra and StarGate.
Sean Durity – Staff Systems Engineer, Cassandra From: onmstester onmstester <onmstes...@zoho.com> Sent: Monday, November 15, 2021 12:56 AM To: user <user@cassandra.apache.org> Subject: [EXTERNAL] Separating storage and processing Hi, In our Cassandra cluster, because of big rows in input data/data model with TTL of several months, we ended up using almost 80% of storage (5TB per node), but having less than 20% of CPU usage which almost all of it would be writing rows to memtables and compacting sstables, so a lot of CPU capacity wasted. I wonder if there is anything we can do to solve this problem using Cassandra or should migrate from Cassandra to something that separates storage and processing (currently i'm not aware of anything as satble as cassandra)? Sent using Zoho Mail [zoho.com]<https://urldefense.com/v3/__https:/www.zoho.com/mail/__;!!M-nmYVHPHQ!aA8YLrua2y_MKLoE-rwgqJ2lmRpWZqA2OVmfzExaUCPBJcsoxCWf6EMMerjdE-RL2sa7MIM$> INTERNAL USE
