Kubernetes
Orquestració amb Kubernetes
aws-troubleshoot
incidentfox
AWS service troubleshooting patterns. Use for EC2, ECS, Lambda, CloudWatch, RDS issues.
log-analysis
incidentfox
Partition-first log analysis methodology. Use for log searches, error analysis, pattern finding across Datadog, CloudWatch, or Kubernetes logs.
sre-principles
incidentfox
Core SRE behavioral principles for incident response. Guides intellectual honesty, evidence-based reasoning, and communication standards.
k8s-debug
incidentfox
Kubernetes debugging patterns. Use for pod crashes, CrashLoopBackOff, OOMKilled, ImagePullBackOff, scheduling failures, deployment issues.
backend-service-implement
parhumm
Generate service implementations with business logic from specs and scaffold stubs. Use when implementing backend services.
azure-swa
markpitt
Comprehensive expertise for Azure Static Web Apps including architecture, configuration, API integration with Azure Functions, authentication, routing, deployment, and CI/CD. Use when building, configuring, deploying, or troubleshooting Azure Static Web Apps projects with frameworks like React, Angular, Vue, Blazor, or vanilla JavaScript.
twelve-factor-app
markpitt
Applies the Twelve-Factor App methodology when designing, building, reviewing, or auditing cloud-native and SaaS applications. Use when asked about 12-factor compliance, app architecture for cloud platforms, environment configuration, stateless processes, deployment pipelines, service design, or scaling strategies. Covers all 12 factors: codebase, dependencies, config, backing services, build/release/run, processes, port binding, concurrency, disposability, dev/prod parity, logs, and admin processes.
root-cause-analysis
markpitt
Conducts systematic root cause analysis using proven methodologies including Toyota's 5 Whys, Ishikawa fishbone diagrams, Pareto analysis, and fault tree analysis. Use when investigating bugs, debugging code, troubleshooting systems, diagnosing equipment failures, analyzing life problems, or identifying underlying causes of any issue across software engineering, hardware maintenance, process failures, or personal challenges.
avalonia
markpitt
Expert guidance for developing cross-platform desktop applications with Avalonia UI framework. Use when building, debugging, or optimizing Avalonia apps including MVVM architecture, XAML design, data binding, styling, theming, custom controls, and cross-platform deployment for Windows, macOS, Linux, iOS, Android, and WebAssembly.
dotnet-aspire
markpitt
Adds .NET Aspire cloud-native orchestration to existing .NET solutions. Analyzes solution structure to identify services (APIs, web apps, workers), creates AppHost and ServiceDefaults projects, configures service discovery, adds NuGet packages, and sets up distributed application orchestration. Use when adding Aspire to .NET solutions or creating new cloud-ready distributed applications.
load-balancing-patterns
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-on-gcp
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
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
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
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
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.
deploying-on-azure
ancoleman
Design and implement Azure cloud architectures using best practices for compute, storage, databases, AI services, networking, and governance. Use when building applications on Microsoft Azure or migrating workloads to Azure cloud platform.
deploying-applications
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.
implementing-gitops
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.
architecting-networks
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.
configuring-firewalls
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.
implementing-service-mesh
ancoleman
Implement production-ready service mesh deployments with Istio, Linkerd, or Cilium. Configure mTLS, authorization policies, traffic routing, and progressive delivery patterns for secure, observable microservices. Use when setting up service-to-service communication, implementing zero-trust security, or enabling canary deployments.
implementing-mlops
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.
operating-kubernetes
ancoleman
Operating production Kubernetes clusters effectively with resource management, advanced scheduling, networking, storage, security hardening, and autoscaling. Use when deploying workloads to Kubernetes, configuring cluster resources, implementing security policies, or troubleshooting operational issues.