Scaling up distributed systems
Craig Turner, 22 July 2021
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Article, /Kubernetes is Our Generation's Multics/,

    https://www.oilshell.org/blog/2021/07/blog-backlog-2.html

My comment,

    There is a trap in distributed system design - seeking to scale-up from a
    single-host perspective. An example - we have apache and want to scale it
    up, so we put it in a container and generate its configuration so we can
    run several of them in parallel. This leads to unnecessarily heavy systems
    - you do not need a container to host a server socket.

    Industry puts algorithms and Big O on a pedestal. Most software projects
    start as someone building algorithms, with deployment and interactions
    only getting late attention. This is a bit like building the kitchen and
    bathroom before laying the foundations.

    Algorithm centric design creates mathematically elegant algorithms that
    move gigabytes of io across the network for every minor transaction. Teams
    wrap commodity resource schedulers around carefully tuned worker nodes,
    and discover their performance is awful because the scheduler can't deal
    in the domain language of the big picture problem.

    I think it is interesting that the culture of Big O interviews and
    Kubernetes both came out of Google.