Hey Folks,
I am currently on the lookout for job opportunities that align with my expertise and would appreciate any leads.
- I have been a DevOps/Platforms Engineer for the past 4 years.
- My experience spans the Fintech and Financial Industry domains, where I have set up, managed, maintained, and scaled infrastructure with a focus on safety and cost-effectiveness.
- I have extensive experience in building infrastructure using Terraform (IaaC) and have managed and set up Terraform Cloud for an organization.
- Kubernetes has been a key part of my DevOps career, and I hold a CKA certification.
- I actively contribute to Open Source and possess strong programming skills in Golang (check my GitHub here: https://t.co/L3pF8LUEp3).
- I am also skilled in technical writing and maintain a blog at https://t.co/ituwo2UPpj.
If you know of any roles that might suit my skill set, I would greatly appreciate any information you can share.
Thank you for your time, and have a great day!
Hey Folks,
I am currently on the lookout for job opportunities that align with my expertise and would appreciate any leads.
- I have been a DevOps/Platforms Engineer for the past 4 years.
- My experience spans the Fintech and Financial Industry domains, where I have set up, managed, maintained, and scaled infrastructure with a focus on safety and cost-effectiveness.
- I have extensive experience in building infrastructure using Terraform (IaaC) and have managed and set up Terraform Cloud for an organization.
- Kubernetes has been a key part of my DevOps career, and I hold a CKA certification.
- I actively contribute to Open Source and possess strong programming skills in Golang (check my GitHub here: https://t.co/L3pF8LUEp3).
- I am also skilled in technical writing and maintain a blog at https://t.co/ituwo2UPpj.
If you know of any roles that might suit my skill set, I would greatly appreciate any information you can share.
Thank you for your time, and have a great day!
What are iximiuz Labs Playgrounds? ๐ค
The simplest playground is a single virtual machine that runs on a remote server. It starts instantly, runs for up to 24h, and gives you full SSH access, so you can experiment with Linux, Docker, Kubernetes, or run agents in an isolated environment.
But a single Linux VM only scratches the surface of the platform. You can also:
- Create VMs with multiple drives using different Linux flavors and filesystems
- Set up complex network topologies by connecting up to 5 VMs to an arbitrary number of bridge networks
- Run Firecracker, Cloud Hypervisor, QEMU, Kata containers, and whatever shiny new agent sandbox project you want to try - nested virtualization is fully supported
- Persist your changes - VM drives are snapshotted and offloaded for remote storage so that you can keep your progress across playground runs
- Fork playground runs to instantly replicate bug reproductions and demo environments
- Create your custom playground presets, including bringing your own rootfs images
- Share playgrounds, including running session links, with friends and colleagues - for learning and debugging purposes
And more!
https://t.co/tk9NfgeUtE
How Servers Work: A Hands-On Introduction to TCP Sockets ๐งโโ๏ธ
Hot off the press! Learn how servers actually work by building a tiny TCP server and client from scratch. Traditionally, with a bunch of visual explainers and practical challenges:
https://t.co/9VzdxjTv5t
Mumbai builders ๐ค Codex
A little group photo from the @OpenAI Codex Community Meetup Mumbai;
Had a great time meeting fellow builders and seeing what everyoneโs shipping;
Thanks Yogesh for hosting ๐
I've got an agent in a loop optimizing a renderer with the goal to minimize frame times (and tests to measure). It got times down from 88ms to 2ms and allocations down from ~150K to 500. Sounds good, right? Wrong. This is exactly why agent psychosis is a big fucking problem.
As an experiment, I rewrote the Ghostty core render state in Go, with access to identically laid out data structures as Ghostty and the exact same validation tests. I made a purposely naive renderer (simple, correct, but slow). 88ms per frame with 150,000 allocations (horrendous, lol)!
I then kickstarted a Ralph loop to bring the frame times down. I told it it can't modify input data structures or the public API or tests (they're correct), but it can do anything else it wants. It got to work.
It has worked for about 4 hours. I've spent around $350 on this experiment so far. The results?
88ms => 1.5ms
150K allocs => ~500 allocs
Incredible right? Nope.
My hand-written renderer I ported has frame times (same benchmark) of ~20us (0.020ms) and 0 allocations in the update path.
This is the problem with psychosis and lacking systems understanding. If you don't understand the system, you're going to accept that this is an incredible result. If you understand the system, you'll see better solutions immediately and can do roughly 75x better on throughput.
The people who blindly trust agent output are in the former camp. They're sheeple, overdrinking from a fountain of mediocrity.
Standard disclaimer: I use AI all the time. I like AI. The point I'm making is to not blindly accept results. Think. Analyze. Learn.
along with the ads now you have to fight gemini to make sure you are getting appropriate and correct information. How can google let such a hallucinating product be at the top of results? Does it not breach any of their terms of service? DO they even have any such terms which holds them accountable for the results that they showcase at the top.
For context - I searched for ssh-askpass-tui. it (gemini) showed me steps on how to install and use it at the top of the page, the first actual result was somewhat that made me realise that it does not exists, I asked gemini to confirm that it exists or not and gemini said, Ah, you caught me lackin!
Comeon, there needs to be some accountability.