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Source channel @githubtrending · Post #14880 · Jun 28

#go#github_actions#kubernetes#operator Actions Runner Controller (ARC) is a tool that helps you automatically manage and scale self-hosted GitHub Actions runners using Kubernetes. It creates runner scale sets that grow or shrink based on how many workflows you are running, making your CI/CD process more efficient and cost-effective. ARC uses containers for runners, so new instances can start or stop quickly and cleanly. You can install ARC easily with Helm on Kubernetes and customize runners with features like custom images, volumes, and scripts. This automation saves you time and resources by matching runner capacity to your actual workload needs[1][2][3]. https://github.com/actions/actions-runner-controller

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The Devs

@thedevs · Post #1159 · 06/29/2018, 06:52 PM

A plain English introduction to JSON web tokens (JWT): what it is and what it isn’t. #article#jwt#security#coding#js @thedevs https://kutt.it/ibVW1N

djangoproject

@djangoproject · Post #389 · 07/21/2017, 03:12 PM

https://thinkster.io/topics/django Looking to build #fullstack apps with #Django? Looking to build a production ready Django #JSON#API? Building a Production Ready Django JSON API 🔸Setting up #JWT Authentication 🔸Profiles 🔸Articles 🔸Comments 🔸Following 🔸Favoriting 🔸Tagging 🔸Pagination 🔸Filtering 🔸Conclusion Configuring Django Settings for Production Building #Web#Applications with Django and #AngularJS 🔸Learning Django and AngularJS 🔸Setting up your environment 🔸Extending Django's built-in User model 🔸Serializing the Account Model 🔸Registering new users 🔸Logging users in 🔸Logging users out 🔸Making a Post model 🔸Rendering Post objects 🔸Making new posts 🔸Displaying user profiles 🔸Updating user profiles 🔸Congratulations, you did it!

GitHub Trends

@githubtrending · Post #15066 · 08/16/2025, 12:30 PM

#python#agents#ai#api_gateway#asyncio#authentication_middleware#devops#docker#fastapi#federation#gateway#generative_ai#jwt#kubernetes#llm_agents#mcp#model_context_protocol#observability#prompt_engineering#python#tools The MCP Gateway is a powerful tool that unifies different AI service protocols like REST and MCP into one easy-to-use endpoint. It helps you manage multiple AI tools and services securely with features like authentication, retries, rate-limiting, and real-time monitoring through an admin UI. You can run it locally or in scalable cloud environments using Docker or Kubernetes. It supports various communication methods (HTTP, WebSocket, SSE, stdio) and offers observability with OpenTelemetry for tracking AI tool usage and performance. This gateway simplifies connecting AI clients to diverse services, making development and management more efficient and secure. https://github.com/IBM/mcp-context-forge