Docker, Kubernetes, and orchestration.
Design, organize, and manage Helm charts for templating and packaging Kubernetes applications with reusable configurations. Use when creating Helm charts, packaging Kubernetes applications, or implementing templated deployments.
Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.
Implement GitOps workflows with ArgoCD and Flux for automated, declarative Kubernetes deployments with continuous reconciliation. Use when implementing GitOps practices, automating Kubernetes deployments, or setting up declarative infrastructure management.
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Comprehensive guidance for creating, organizing, and managing Helm charts for packaging and deploying Kubernetes applications.
Check for .claude/apple-design-context.md before asking questions. Use existing context and only ask for information not already covered.
Step-by-step guidance for creating production-ready Kubernetes manifests including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims.
Comprehensive guide for implementing NetworkPolicy, PodSecurityPolicy, RBAC, and Pod Security Standards in Kubernetes.
Kubernetes deployment workflow for container orchestration, Helm charts, service mesh, and production-ready K8s configurations.
Encrypted Saved Objects (ESO) in Kibana — registration, AAD attribute choices, partial update safety, model version migrations with createModelVersion, canEncrypt checks, and Serverless constraints. Use when creating, modifying, or working with ESO types.
Local text-to-speech via sherpa-onnx (offline, no cloud). Converts text to speech audio using the sherpa-onnx runtime and Piper VITS voices with no cloud dependency. Use when the user asks to generate speech, read text aloud, produce a voice audio file, perform TTS, speech synthesis, or convert text to WAV output locally.
Kubernetes operations expert for kubectl, pods, deployments, and debugging
Compile TensorRT-LLM on a compute node inside a Docker container. Use this when already on a compute node with GPUs visible.
Use when launching cloud VMs, Kubernetes pods, or Slurm jobs for GPU/TPU/CPU workloads, training or fine-tuning models on cloud GPUs, deploying inference servers (vllm, TGI, etc.) with autoscaling, writing or debugging SkyPilot task YAML files, using spot/preemptible instances for cost savings, comparing GPU prices across clouds, managing compute across 25+ clouds, Kubernetes, Slurm, and on-prem clusters with failover between them, troubleshooting resource availability or SkyPilot errors, or optimizing cost and GPU availability.
