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Source channel @githubtrending · Post #15415 · Jan 15

#go#bpf#cncf#cni#containers#ebpf#k8s#kernel#kubernetes#kubernetes_networking#loadbalancing#monitoring#networking#observability#security#troubleshooting#xdp Cilium is an eBPF-based tool for Kubernetes that delivers fast networking, deep visibility, and strong security. It creates simple Layer 3 networks across clusters, handles load balancing to replace kube-proxy, enforces identity-based policies from L3 to L7 (like HTTP or DNS rules), supports service mesh with encryption, and offers Hubble for real-time traffic monitoring. Stable versions like v1.18.6 run on AMD64/AArch64. You gain scalable performance, easier policy management without IP hassles, better troubleshooting, and higher efficiency for large cloud-native apps, cutting costs and boosting reliability. https://github.com/cilium/cilium

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@githubtrending · Post #14663 · 05/02/2025, 12:30 PM

#python#agents#ai#ai_agents#api#developer_tools#function_calling#integration#llm#mcp#oauth2#open_source#permissions#tools ACI.dev is an open-source platform that helps build AI agents by providing easy access to over 600 tools. It simplifies authentication and tool integration, allowing AI agents to work with many services like Google Calendar and Slack without needing separate setups. This platform offers multi-tenant authentication, flexible access methods, and natural language permissions, making it easier to manage and secure AI agent capabilities. It's open-source and works with any framework, which means you can build AI agents without worrying about vendor lock-in. https://github.com/aipotheosis-labs/aci

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@githubtrending · Post #15214 · 10/12/2025, 11:30 AM

#python#agents#ai#ai_agents#api#developer_tools#discord#function_calling#integration#llm#mcp#mcp_client#mcp_server#oauth2#open_source Klavis AI helps developers connect AI tools to other services like GitHub, Gmail, and Slack easily. It offers hosted servers that handle authentication and client code automatically, making it simpler to integrate AI with various platforms. This saves time and effort by eliminating the need for custom authentication management and client library maintenance. Users can quickly set up and scale their AI applications without worrying about complex integrations, making it easier to deploy AI-powered workflows securely and efficiently. https://github.com/Klavis-AI/klavis

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@githubtrending · Post #15556 · 03/12/2026, 12:30 PM

#typescript#ai#ai_agents#coding#deno#embeddings#insforge#nextjs#oauth2#pgvector#postgresql#realtime#vectors#websockets InsForge is an open-source backend platform for AI coding agents, offering easy auth, Postgres database, S3 storage, edge functions, and model gateway via a simple semantic layer. Agents fetch context, configure services, and inspect state to build full-stack apps quickly. Set up locally with Docker or use cloud deploys. It boosts agent accuracy 1.7x, speed 1.6x, and cuts tokens 30% vs. rivals, letting you prototype and ship AI-driven apps faster with less hassle and cost. https://github.com/InsForge/InsForge

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@githubtrending · Post #14691 · 05/10/2025, 12:00 AM

#csharp#architecture#aspnetcore#clean_architecture#cqrs#ddd#dotnet#dotnetcore#event_driven_architecture#event_sourcing#kubernetes#masstransit#messaging#microservice#microservices#oauth2#opentelemetry#software_architecture#software_design#software_engineering#vertical_slice_architecture Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5]. https://github.com/meysamhadeli/monolith-to-cloud-architecture