Something all architecture astronauts deploying microservices on Kubernetes should try is benchmarking the latency of function calls.
E.g.: call a "ping" function that does no computation using different styles.
In-process function call.
In-process virtual ("abstract") function.
Cross-process RPC call in the same operating system.
Cross-VM call on the same box (2 VMs on the same host).
Remote call across a network switch.
Remote call across a firewall and a load balancer.
Remote call across the above, but with HTTPS and JSON encoding.
Same as above, but across Availability Zones.
In my tests these scenarios have a performance range of about 1 million from the fastest to slowest. Languages like C++ and Rust will inline most local calls, but even when that's not possible overhead is typically less than 10 CPU clocks, or about 3 nanoseconds. Remote calls in the typical case start at around 1.5 milliseconds and HTTPS+JSON and intermediate hops like firewalls or layer-7 load balancers can blow this out to 3+ milliseconds surprisingly easily.
To put it another way, a synchronous/sequential stream of remote RPC calls in the typical case can only provide about 300-600 calls per second to a function that does nothing. Performance only goes downhill from here if the function does more work, or calls other remote functions.
Yet, every enterprise architecture you will ever see, without exception has layers and layers, hop upon hop, and everything is HTTPS and JSON as far as the eye can see.
I see K8s architectures growing side-cars, envoys, and proxies like mushrooms, and then having all of that go across external L7 proxies ("ingress"), multiple firewall hops, web application firewalls, etc...