Assuming for a minute that containers aren't in play, then the isolation model becomes that of a server/vm with the associated overhead of each. To make this easier we'll assume there's only a single service, even though we know this to be untrue.

If there are 1M customers that's a minimum of 1M servers. Some customers are obviously larger and would need more. There's also HA. Let's conservatively call it 2.5M servers.

At an absolute bare minimum we'd need to allocate 2.5M GB of ram and 2.5M vCPU. That's a huge amount of resources.

If you could reliably fit 10000 Small customers on a single server at 32gb ram and 8 cpus you can already start to see how many resources can be saved.

Without customer isolation you've got the entire cluster to handle load spikes and HA. With isolation you have to have scheduling monitoring each of the 1M clusters and scaling appropriately by anticipating demand.

Scaling a service is way easier than scaling customers within a service or many services.