Kubernetes
Kubernetes orchestration
docker-containerization
by ailabs-393
This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.
Bankr Agent - Token Deployment
by BankrBot
This skill should be used when the user asks to "deploy token", "create token", "launch token", "Clanker", "claim fees", "token metadata", "update token", "mint new token", or any token deployment operation. Provides guidance on deploying ERC20 tokens via Clanker.
load-balancing-patterns
by ancoleman
When distributing traffic across multiple servers or regions, use this skill to select and configure the appropriate load balancing solution (L4/L7, cloud-managed, self-managed, or Kubernetes ingress) with proper health checks and session management.
deploying-applications
by ancoleman
Deployment patterns from Kubernetes to serverless and edge functions. Use when deploying applications, setting up CI/CD, or managing infrastructure. Covers Kubernetes (Helm, ArgoCD), serverless (Vercel, Lambda), edge (Cloudflare Workers, Deno), IaC (Pulumi, OpenTofu, SST), and GitOps patterns.
administering-linux
by ancoleman
Manage Linux systems covering systemd services, process management, filesystems, networking, performance tuning, and troubleshooting. Use when deploying applications, optimizing server performance, diagnosing production issues, or managing users and security on Linux servers.
deploying-on-gcp
by ancoleman
Implement applications using Google Cloud Platform (GCP) services. Use when building on GCP infrastructure, selecting compute/storage/database services, designing data analytics pipelines, implementing ML workflows, or architecting cloud-native applications with BigQuery, Cloud Run, GKE, Vertex AI, and other GCP services.
implementing-tls
by ancoleman
Configure TLS certificates and encryption for secure communications. Use when setting up HTTPS, securing service-to-service connections, implementing mutual TLS (mTLS), or debugging certificate issues.
deploying-on-aws
by ancoleman
Selecting and implementing AWS services and architectural patterns. Use when designing AWS cloud architectures, choosing compute/storage/database services, implementing serverless or container patterns, or applying AWS Well-Architected Framework principles.
optimizing-costs
by ancoleman
Optimize cloud infrastructure costs through FinOps practices, commitment discounts, right-sizing, and automated cost management. Use when reducing cloud spend, implementing budget controls, or establishing cost visibility across AWS, Azure, GCP, and Kubernetes environments.
model-serving
by ancoleman
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
implementing-gitops
by ancoleman
Implement GitOps continuous delivery for Kubernetes using ArgoCD or Flux. Use for automated deployments with Git as single source of truth, pull-based delivery, drift detection, multi-cluster management, and progressive rollouts.
configuring-firewalls
by ancoleman
Configure host-based firewalls (iptables, nftables, UFW) and cloud security groups (AWS, GCP, Azure) with practical rules for common scenarios like web servers, databases, and bastion hosts. Use when exposing services, hardening servers, or implementing network segmentation with defense-in-depth strategies.
architecting-networks
by ancoleman
Design cloud network architectures with VPC patterns, subnet strategies, zero trust principles, and hybrid connectivity. Use when planning VPC topology, implementing multi-cloud networking, or establishing secure network segmentation for cloud workloads.
runpod-deployment
by ScientiaCapital
"Deploy GPU workloads to RunPod serverless and pods - vLLM endpoints, A100/H100 setup, scale-to-zero, cost optimization. Use when: deploy to RunPod, GPU serverless, vLLM endpoint, scale to zero, A100 deployment, H100 setup, serverless handler, GPU cost optimization."
localstack-state
by localstack
Manage LocalStack state and snapshots. Use when users want to save, load, export, or import LocalStack state, work with Cloud Pods, create local snapshots, or enable persistence across restarts.
coolify-deploy
by v1truv1us
Deploy to Coolify with best practices
effect-ts
by joncrangle
This skill should be used when the user asks about Effect-TS patterns, services, layers, error handling, service composition, or writing/refactoring code that imports from 'effect'. Also covers Effect + Next.js integration with @prb/effect-next.
gitops
by proompteng
'GitOps workflows for this repo: edit Argo CD/Kubernetes/infra manifests in version control, validate changes, and rely on Argo CD to sync. Use when tasks touch argocd/, kubernetes/, tofu/, ansible/, or deployment/runbook changes, or when asked to roll out services via GitOps.'
implementing-mlops
by ancoleman
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
designing-distributed-systems
by ancoleman
When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures.
kubectl-basics
by chaterm
kubectl 基础操作与常用命令
backend-service-implement
by parhumm
Generate service implementations with business logic from specs and scaffold stubs. Use when implementing backend services.
deploying-app
by wasp-lang
deploy the Wasp app to Railway or Fly.io using Wasp CLI.
svelte-deployment
by spences10
Svelte deployment guidance. Use for adapters, Vite config, pnpm setup, library authoring, PWA, or production builds.