Christer Eliasi-Swahn’s Post

Serverpod 2.2, code-named "Futurism," is now out. 🚀 It brings a fully featured testing framework plus two cool experimental features. 🧪 Links below. ⬇️ 📺 Keynote: https://lnkd.in/dPX5Jjcd ✍️ Blog post: https://lnkd.in/dwiPSheJ

Day 6 of #100DaysofNoCode Today I learned how to build a resource directory using @softr_io This new resource directory is organized, efficient, It will serve as a valuable tool for our team and users, providing easy access to essential resources and information.

How does Fair Launch System work on Datnoid? There are 3 different ways to launch a token on Datnoid- Random selection, FCFS, or instant launch. Random Selection The pre orders are shuffled and executed in the new random order. If you are the last person to preorder, you still have a chance of getting the first buy (best price quote). First Come First Served No shuffling and the earlier you are, the better price quote you will receive. Instant Launch Skip the scheduling entirely and as soon as you create your token it is available for anyone and everyone to start swapping. When viewing the pre orders tab on a token, it will display which type of launch the dev chose. Regardless of the launch type, being one of the first to place a preorder will earn you the most points.

XTable really shines, yet it's still not easy to use and transparent as it can be. Currently, data producers must anticipate compatible table formats for consumers or dive into technical specifics like Iceberg catalogs. My vision? A unified protocol where producers and consumers converge seamlessly, sharing data effortlessly with minimal feature dependencies. That's why we're building Whitefox, a (truly) open-source solution facilitating easy sharing of table format data through a single protocol. Embracing the mantra of "Write once, query everywhere". (Whitefox will use XTable behind the scenes soon, because well, I said it is a brilliant project) Keen on shaping Whitefox's journey, offering insights, or eager to explore? Join us on GitHub! (link in the first comment) #DataSharing #OpenSource #XTable #Whitefox #GitHub #TableFormat #dataeng #dataplatform

I added a regular proxmox module for normal VM deployment using cloudinit. This module utilizes count for a more efficient module declaration. #terraform #proxmox #cloudinit #homelab

I published on my GitHub the Lab for deploy Rancher K3s in Docker with self-signed Certificates, and using virtual machines to configure the bind DNS and RKE2 Downstream Cluster. https://lnkd.in/dzryWFHG

 🎥 I finally recorded a quick overview of Bugsink! If you’ve ever wondered: 👉 What is error tracking? When something breaks on your server, error tracking notifies your developers and gives them a detailed view of what went wrong. 👉 Why Bugsink? This demo highlights how Bugsink provides clear, detailed stack traces with all the context you need to fix issues fast. 👉 At 1:30, I’ll show how easy it is to install and get started. I’d love to hear your thoughts—check it out and let me know what you think!

Fair solutions on Datnoid. There are 3 different ways to launch a token on Datnoid. Random Selection, FCFS, or instant launch. Random Selection The pre orders are shuffled and executed in the new random order. If you are the last person to preorder, you still have a chance of getting the first buy (best price quote). First Come First Served No shuffling and the earlier you are, the better price quote you will receive. Instant Launch Skip the scheduling entirely and as soon as you create your token it is available for anyone and everyone to start swapping. When viewing the pre orders tab on a token, it will display which type of launch the dev chose. Regardless of the launch type, being one of the first to place a preorder will earn you the most points.

Let's unpack some key insights from StackOverflow's 2024 Developer Survey and see how they can help you make better decisions about your Tech strategy.

Recently, I was working building in-memory cache and after some research, I decided to go with BadgerDB (a key-value store built in Go) because it allows for easy switching between in-memory and disk storage. The real surprise came when I started testing which data format would be the fastest for serialization/deserialization. For simplicity, I chose to focus on MessagePack and Gob. HashiCorp offers a solid package for handling MessagePack encoding/decoding, and I was blown away by how fast it was while keeping memory usage impressively low—staying under 5 allocations per byte