1,956 karma · joined February 3, 2013
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Is there maybe a Zig wrapper for Google soy around?
I am probably looking for something like the request context with timers and cancellation signals propagating through the call chain like in gRPC but more fine granular.
So you could implement arbitrary response times of functions. So you could say like:
This whole request must finish in 5 seconds, otherwise abort.
And these 5 seconds can be made very low so that you reach latency of NUMA vs Single CPU.
I don't know how you call this, maybe "latency budget"
Zig has the feature that you can drop in your allocator from the caller. Now with 0.16 you also "bring your own IO" implementation with you.
And for my understanding this looks like the pattern Go uses with its Context package, where you pass in transitive data, cancellation signals and timers to for example stop an SQL query in server B, since a user canceled a web request in their browser before hitting server A, whilst all elements delegate the Context.
Then yesterday was total unrelated article about NUMA architecture, and I remember somewhere that the creator of Erlang mentioned (Joe Armstrong) that you cannot get around physics and it takes time to call a function between servers, therefore so not try to hide the latency between the calls.
And now to my question:
Would that in any way make sense for zig to go even more in this direction, where you pass in your allocator, IO, but now with something similar to Google Go context, but have it even more fine grained?
So that your functions could actually in their interface expose somehow the time in between CPU cores (NUMA) up to the request cancellation as Google go context is used for timeout signals, cancellation signals.
Also probably making time an external dependency as well.
So in essence , every function would be treated as a remote procedure calls, whereas remote would mean: "other cpu", other server/service
I have stumbled on this project while dabbling around how to launch many firecracker VMs on a MacBook with >= M3 cpu to isolate agents.
What do others do to isolate agents?
regarding …“One was the realization that a purely mechanical computer can, in principle simulate the laws …“
As far as I unterstood,there is no theory of quantum gravity and therefore this is not being simulated on a computer. I think he makes other arguments.
So you cannot say for sure that you can simulate a human brain on a computer
But I don’t fully understand what you meant with content adressed :)
Maybe one has to ensure in the host cluster that the image pull policy is set to Always or all references to images have to be based on the shasum rather than Tags.
I understood from the host cluster perspective you won’t see the child cluster pods. And what is the perspective on nodes?
Can you have like a host cluster spawning on host nodes and the host cluster has control over spawning separate physical nodes which contain the child cluster (api server) + workload pods ?
Sure when I started Go there were Go routines plastered everywhere. And now I think harder: “do I really need a go routine here?”
Therefore my middle ground is devbox.
It is like python vietualenv but backed by Nix. So I have a devbox.json file to define packages and devbox will do the Nix part for me.
I am getting a MacOS and Linux setup from this for aarch64 and x86
It's lua, so you can get creative with https://fennel-lang.org/
But how do you quality check this part? I am proofreading all these transformations and I am not sure if this is really faster than actually recording a VIM macro, which will do the steps I need.
source "utm-cloud" "this" { iso_url = "${path.root}/dev_images/al2023-kvm-2023.6.20250303.0-kernel-6.1-x86_64.xfs.gpt.qcow2" iso_checksum = "sha256:0dc2797fe19847f6c75878dd344ab478ac0657077d9a15f2907bb2df41d8c3de" vm_arch = "x86_64" cpus = 2 memory = 4096 display_nopause = true boot_nopause = true export_nopause = true skip_nat_mapping = true communicator = "ssh" ssh_clear_authorized_keys = true ssh_private_key_file = data.sshkey.this.private_key_path ssh_host = "192.168.64.100" ssh_port = 22 ssh_username = "ec2-user" shutdown_command = "echo 'packer' | sudo -S /sbin/halt -h -p" use_cd = true cd_label = "cidata" cd_content = { "meta-data" = <<EOF local-hostname: vm-hostname EOF "user-data" = <<EOF #cloud-config ssh_sftp: enabled: true password: ec2-user ssh_pwauth: True chpasswd: expire: False users: - default - name: ec2-user lock_passwd: false plain_text_passwd: ec2-user ssh_authorized_keys: - ${data.sshkey.this.public_key} EOF "network-config" = <<EOF #cloud-config version: 2 ethernets: enp0s1: # dhcp4: yes addresses: - 192.168.64.100/24 gateway4: 192.168.64.1 nameservers: addresses: - 10.0.2.2 enp0s2: dhcp4: no state: down EOF } }
For grafana cloud and Loki you can close to a good usability with LBAC (label based access control) but you still need have many data sources to map onto each “team view” to make it user friendly.
What is missing for me is like in elastic a single datasource for all logs which every team member across all teams can see and you scope out the visibility level with LBAC
But you get to control the keyboard/clipboard and it can add apparently watermarks to the vnc session for DLP functionality and you have a web http to take screenshots of your vnc sessions.
This way with libcosmopolitan, you could just checkin a copy of your build tool in a project, to be self sufficient. Think of it like gradlew( the gradle bash/bat wrapper) but completely self contained and air gapped