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Source channel @githubtrending · Post #15104 · Aug 30

#shell#alpine#alpine_linux#boot#distro#grub#installer#iso#linux#linux_distribution#liveos#netboot#netinst#netinstall#operating_systems#os#reinstall#shell_script#vps#windows You can use a powerful script to easily reinstall Linux or Windows on your server with just one command. It supports 19 popular Linux versions and all Windows versions from Vista to Windows 11, automatically downloading official ISO files and drivers. It works for switching between Linux and Windows, handles different network setups without manual IP input, and supports BIOS, EFI, and ARM servers. The script is lightweight, safe, and fetches all resources live from official sources. This saves you time and effort in system installation or reinstallation, especially on low-memory or cloud servers. You can also customize passwords, SSH keys, and ports during installation. https://github.com/bin456789/reinstall

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Go

@golang · Post #58 · 04/22/2018, 08:22 PM

Why are goroutines not lightweight threads? Kartik Khare shows us his meaning about goroutines, lightweight threads and their difference in GoLang. There are no code examples inside but good thoughts about parallelism, threads and useful links at the end of the article :) #development#runtime#language https://codeburst.io/why-goroutines-are-not-lightweight-threads-7c460c1f155f

Go

@golang · Post #64 · 06/21/2018, 04:17 PM

Hi there! Which ways do you use to avoid memory leaks for REST API? In the following article by Iman Tumorang describes an excellent example of memory leaks, his solution, and results. Must have to read for everyone 😉 #development#runtime#architecture https://hackernoon.com/avoiding-memory-leak-in-golang-api-1843ef45fca8

GitHub Trends

@githubtrending · Post #15382 · 01/01/2026, 12:30 PM

#jupyter_notebook#agent#agentic_ai#agents#authentication#bedrock#core#gateway#identity_management#memory_management#production_code#runtime Amazon Bedrock AgentCore lets you build, deploy, and run AI agents securely at scale with any framework like CrewAI or LangGraph and any model, without managing complex infrastructure. It offers serverless runtime for long tasks up to 8 hours, gateway to connect tools like Slack or APIs easily, memory for personalized experiences, identity management, built-in code interpreter and browser tools, plus observability. This saves time by skipping heavy setup, speeds prototypes to production, cuts costs with pay-per-use, and boosts security—helping you create powerful agents faster for real business needs. https://github.com/awslabs/amazon-bedrock-agentcore-samples