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Source channel @githubtrending · Post #15033 · Aug 6

#shell#buildroot_external_tree#firmware#ingenic#ip_camera#ipc#ipcamera Thingino is free, open-source firmware designed specifically for IP cameras using Ingenic SoC chips. It customizes the software to fit each supported camera model, making the camera easier to use and more efficient. You can build the firmware yourself using the provided instructions and tools, and there is a helpful web interface to control camera features like pan, tilt, night mode, and streaming. This gives you more control and flexibility over your camera without relying on proprietary software. It supports many camera models, and the community offers resources like a wiki, chat groups, and development guides to help you get started and customize your device. This benefits you by providing a customizable, transparent, and community-supported alternative to closed camera firmware. https://github.com/themactep/thingino-firmware

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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