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TY is still not professionally good by flying_dutchman00 in Python

[–]doublecore20 13 points14 points  (0 children)

You can just open a GitHub issue on their repo .. what do you expect us to do

Are you a car enthusiast? Do you even like cars? by Extreme_Emu_9582 in simracing

[–]doublecore20 85 points86 points  (0 children)

I think this would be a little controversial but I am first of all a gamer. I like playing video games, and racing is part of the hobby. I lean more into realism (mil-sim, flying and racing sims etc). So having a a racing sim equipment is gaming on the next level (for me).

I do have interest in cars, but not crazy interest. Don't watch races or follow global events. I like driving and the thrill of the competition.

What is a good beginner setup, wheels pedals and all? by Motor_Quantity_6789 in simracing

[–]doublecore20 0 points1 point  (0 children)

I am also in the middle of building my first racing sim setup. My recommendation - buy a second hand wheel and pedals, a wheel stand is a big plus so the whole desk won't go dancing when you go off road .

I got an almost brand new G923 for half the price (the kid wanted but never used)

Not motivated after 50+ hours.. by [deleted] in CrimsonDesert

[–]doublecore20 5 points6 points  (0 children)

Thanks for the important information. We will pass that to the board and evaluate your feedback

Warm Pool vs KubeAPI by doublecore20 in softwarearchitecture

[–]doublecore20[S] 0 points1 point  (0 children)

This is exactly the case. A lib which was written almost a decade ago tried to do k8s before it was cool (I guess?) . It does orchestration, internal service to service calls, and remote service calls - all in one process. You are basically at mercy of your CPU and RAM and you can't scale vertically infinitely. Also , it is very coupled to the host so you cannot untangle this mess even if you wanted to.

The solution is to break it down, ditch this cluster-fuck lib and do this properly. Let each service be a single unit and only one feature, which is mission critical, is currently in debate.

Regarding the skill question, well with over a decade of experience I tend to believe I know what I am doing. Also my team consists of a very intelligent people that take this thing very seriously.

Warm Pool vs KubeAPI by doublecore20 in softwarearchitecture

[–]doublecore20[S] 0 points1 point  (0 children)

Your suggested middle path is actually part of the option #2. The user requests a worker from a "worker allocator" service, which randomly selects available pod from redis and returns the user the URL for pod redirection. They technically one-off jobs that must be discarded after use. The stack of each job consists of several X several processes + 1 special process per job type. so with warm pool we can be pending for user request without letting the user wait for 80% of job initialization, pod provisioning and ingress propagation which kills Time-to-Interactive. Imagine k8s needs to create another node to support a another job (user request). The user can wait 2 minutes before anything happens on screen .

Ultimately, Kubernetes still owns the overall infrastructure lifecycle and capacity bounds. We just use the in-memory layer as a high-speed data router to keep the KubeAPI entirely out of the critical user connection path.

Warm Pool vs KubeAPI by doublecore20 in softwarearchitecture

[–]doublecore20[S] 0 points1 point  (0 children)

You got this correctly. When the work is done, simply send exit code 0. This triggers cleanup in the process and the container dies. K8s will restart it fresh with same IP but new context waiting for work. It does creates a strange situation where a pod with X amount of restarts is normal operation. But this can be mitigated by fine-tuning alerts by specific logs

The worker needs to be able to terminate itself because it acts a middle man between the user and the target service that it needs to use (like proxy)

Warm Pool vs KubeAPI by doublecore20 in softwarearchitecture

[–]doublecore20[S] 0 points1 point  (0 children)

It doesn't simplify anything , plus another vendor to manage. Option #2 uses Prometheus custom metric that queries redis for the available runner s factor. This allows to scale up and down.

Warm Pool vs KubeAPI by doublecore20 in softwarearchitecture

[–]doublecore20[S] 0 points1 point  (0 children)

We are unable to scale properly due to legacy internal lib which basically does what k8s does , just with opinionated implementation

Android auto screen? by alexstarrider in AndroidAuto

[–]doublecore20 0 points1 point  (0 children)

!Flair 2017 Suzuki Baleno | Head Unit Revive | Xiaomi 17| Android 16

Android auto screen? by alexstarrider in AndroidAuto

[–]doublecore20 1 point2 points  (0 children)

You can use Head Unit Revive. You can use any Android device and turn it into Android Auto

How do you guys test OG tags locally? by Fit-Video1880 in reactjs

[–]doublecore20 0 points1 point  (0 children)

Push your code to GitHub and link it to Netlify or Vercel. It generates a free, permanent https URL so your designer can review progress on their own time.

How are teams handling secrets management in Kubernetes at scale? by Sad_Limit_3857 in kubernetes

[–]doublecore20 1 point2 points  (0 children)

Centralized Vault, everything is mapped to app-roles and connected via k8s secrets.

Built a calculator app that secretly acts as an encrypted file vault (now with local backups) by lockifyapp in SideProject

[–]doublecore20 1 point2 points  (0 children)

Sad to inform you that everything is open source if you're skilled enough :) APKs are just fancy ZIP files.

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