Qubiva
Self-hosted K8s platform for cloud governance and AI ops
What it does
Qubiva is an open-source, self-hosted Kubernetes-native platform for platform and DevOps teams. Deploy via Helm in minutes. Get: • OpenTofu/Terraform execution with real-time log streaming • Live AWS, Azure, GCP resource discovery via SQL • CIS, SOC 2, HIPAA, PCI DSS compliance benchmarks and more • Natural language queries over your infra (bring your own LLM) • Tasks, RBAC, SSO, audit trails Your data never leaves your infrastructure.
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- RGRun globally distributed full-stack apps on high-performance MicroVMs2023 · koyeb.com · ▲98
Hi HN! We’re Yann, Edouard, and Bastien from Koyeb (https://www.koyeb.com/). We’re building a platform to let you deploy full-stack apps on high-performance hardware around the world, with zero configuration. We provide a “global serverless feeling”, without the hassle of re-writing all your apps or managing k8s complexity [1]. We built Scaleway, a cloud service provider where we designed ARM servers and provided them as cloud servers. During our time there, we saw customers struggle with the same issues while trying to deploy full-stack applications and APIs resiliently. As…
- KSKlaw.sh – Kubernetes for AI agentsFeb 2026 · github.com · ▲60
Hi everyone, I run a generative AI infra company, unified API for 600+ models. Our team started deploying AI agents for our marketing and lead gen ops: content, engagement, analytics across multiple X accounts. OpenClaw worked fine for single agents. But at ~14 agents across 6 accounts, the problem shifted from "how do I build agents" to "how do I manage them." Deployment, monitoring, team isolation, figuring out which agent broke what at 3am. Classic orchestration problem. So I built klaw, modeled on Kubernetes: Clusters — isolated environments per org/project Namespaces — team-level…
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Dev tools · May 2026 · kilo.ai


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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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Dev tools · May 2026 · github.com