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Source channel @githubtrending · Post #15174 · Sep 27

#typescript#actions#authentication#gcp#github_actions#google_cloud#google_cloud_platform#iam#identity#security You can securely connect GitHub Actions to Google Cloud using the Google GitHub Action called `auth`. It supports two main ways: the recommended Workload Identity Federation (WIF), which uses short-lived tokens and avoids long-lived service account keys, and the older Service Account Key JSON method. WIF improves security by creating a trust link between your GitHub workflow and Google Cloud without exposing permanent credentials. To use it, you set up a Workload Identity Pool and Provider in Google Cloud, then configure your GitHub workflow to authenticate with these. This lets your workflows access Google Cloud resources safely and easily, reducing risks and simplifying credential management. https://github.com/google-github-actions/auth

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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