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Found 68 Skills
Comprehensive GitOps methodology and principles skill for cloud-native operations. Use when (1) Designing GitOps architecture for Kubernetes deployments, (2) Implementing declarative infrastructure with Git as single source of truth, (3) Setting up continuous deployment pipelines with ArgoCD/Flux/Kargo, (4) Establishing branching strategies and repository structures, (5) Troubleshooting drift, sync failures, or reconciliation issues, (6) Evaluating GitOps tooling decisions, (7) Teaching or explaining GitOps concepts and best practices, (8) Deploying ArgoCD on Azure Arc-enabled Kubernetes or AKS with workload identity. Covers the 4 pillars of GitOps (OpenGitOps), patterns, anti-patterns, tooling ecosystem, Azure Arc integration, and operational guidance.
AWS, GCP, Azure data platforms, infrastructure as code, and cloud-native data solutions
High-performance Quarkus framework expertise covering reactive patterns, CDI, build-time augmentation, and cloud-native development. Use for general Quarkus questions.
Orchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or workload before going live to production. Don't use for deep-dive single-domain implementation (use specific domain skills like gke-scaling, gke-platform-security, gke-workload-security, gke-service-networking, gke-reliability instead).
Expert knowledge for Modern Java (21+) development, including Virtual Threads, performance tuning, and idiomatic clean code. Use for deep Java language/logic questions.
Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inference, GKE upgrade, GKE observability, GKE multi-tenancy, GKE batch, GKE HPC, GKE compute class.
Use when deploying or managing Kubernetes workloads requiring cluster configuration, security hardening, or troubleshooting. Invoke for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization.
Use for high-stakes technical decisions, system design (Microservices/Monolith), cloud infrastructure, or generating ADRs/RFCs.
Expert-level Microsoft Azure cloud platform, services, and architecture
Expert guidance for GraalVM native image development with Java frameworks, build optimization, and high-performance application deployment
Go (Golang) with goroutines, channels, interfaces, and idiomatic patterns. Use for .go files.
Architecture pattern for Lambda handlers. Env vars validated at module level, AWS clients at module scope, pure business logic with injected dependencies. Apply when creating or modifying any Lambda function.