#kubernetes

🔊 Pronounce developer jargon out loud. 1,650+ entries (kubectl, GIF, JSON, JWT, …), sourced with confidence levels. Bash CLI + VS Code extension + interactive quiz + voice search + MCP server + Claude Code skill.

The self-improving SRE agent

A Kubernetes-native operator for platform teams to inspect, debug, and explore files on idle or active Persistent Volume Claims (PVCs).

Turn an architecture spec into editable diagrams with official vendor service icons (Azure/AWS/GCP/K8s) - .pdf/.drawio/.vsdx. Usable by AI agents via skill or MCP server.

Multi-cluster Kubernetes dashboard — the whole UI baked into one Go binary. Resource lists stream binary MessagePack deltas over WebSocket; no polling, no pagination, virtualised end-to-end. Inline scale, restart, rollback, exec, logs, port-forward, YAML edit. Prometheus + metrics-server. Docker, Helm or raw manifests.

2026 AI Dev Sandbox: Real Env Injection, Live Traffic Replay & Network Mirroring

Claude Code scaffold for building AI platforms securely — agent/LLM security, Kubernetes, SRE, observability, identity, and supply chain, grounded in published framework canon (OWASP, NIST, CIS, SLSA). Data-science lanes included.

Local-first Kubernetes platform for private LLM and coding-agent workloads.

Autonomous Claude Code CI agent in a rootless Podman sandbox — GitLab CI & GitHub Actions, two personalities (read-write Agent, read-only Advisor), OpenTelemetry audit to Elastic, Helm chart for AKS/OpenShift.

How far does this command reach? Guards AI coding agents against shell commands that leave your machine. Zero dependencies.

AI governance and edge infrastructure platform with HTTP/3, OpenTelemetry tracing, adaptive load shedding, circuit breakers and Kubernetes deployment support.

Private AI platform on k3s — Ollama/Qwen3 + Milvus RAG + MCP agentic tooling + Fleet multi-cluster management

A modern banking application with an integrated AI chatbot, deployed on AWS EKS using Terraform, ArgoCD, Gateway API, and Prometheus monitoring.

Production-oriented Kimi K3 inference control plane with checkpoint release gates, MoE capacity planning, OpenAI gateway, NVL72 deployment, benchmarks, and observability.

Kubernetes observability suite: a pod/container metadata service plus a per-node agent that tails container logs, scrapes Prometheus targets, cadvisor, node metrics and journald, enriches everything with pod metadata, and exports OTLP

AI-powered FastAPI chatbot with Docker and Kubernetes support, integrating NVIDIA/Ollama LLMs

A self-hosted agent fleet deployed to AWS EKS the way an FDE hands a system to a platform team: Terraform, Helm, GitHub OIDC CI/CD with an approval gate, SOC 2 control mapping, and a Go notify bridge. VALIDATION.md marks what is proven locally vs. what needs a live account.

End-to-end document processing — Spring Boot microservices, Python OCR (AWS Textract), OpenAI GPT-4o extraction, Kafka async pipeline, React dashboard.

Kubernetes deployment of my personal always-on agent system, migrated from systemd on a DigitalOcean droplet to k3s. Artifacts built and statically verified; nothing has run on a cluster yet, and VALIDATION.md says exactly which is which.

OpenTelemetry observability and privacy-aware failure replay for production AI agents.

Production-grade agentic AI on Kubernetes — LangGraph-native agent orchestration (Synapse) on EKS + Istio Ambient Mesh + AgentGateway. Zero-credential LLM access, pluggable MongoDB Atlas Vector Search memory, A2A protocol runtime, multi-tenant by design.

Diagrams as D2 source rendered to PNG, so the picture lives in git next to the code. A skill for Claude Code, Opencode and Codex.

Ryan Prasad's AI Engineering portfolio and recruiter-agent GitHub profile README

Real-time multiplayer workload on Kubernetes with GitOps, WebSockets, TLS ingress, readiness probes, and a Redis/HPA scaling roadmap.

Kubernetes resource analytics — real usage vs requests/limits, waste & multi-tenant chargeback, on ClickHouse. Rust agent reads cgroup v2 directly.

A Kubernetes lab that reproduces real production incidents on a live, instrumented microservice stack — for testing root-cause-analysis tools and agents.