DevOps & Cloud

Deployment, cloud, containers, CI/CD, monitoring, and infrastructure

skills in category: 19,589
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Showing 15,121–15,144 of 19,589 skills

Tinyworld Tinyverse CollectiblesATinyverse collectibles lane — pack reveal, frozen islands, play-mode visits. Universe carousel is archived but code stays in repo.devopsrustgoVotes: 0GitHub stars: 1,587
Tinyworld Runtime StateAUse when adding or changing persisted user state — settings defaults, audio, camera/orbit, panel positions, feature flags, and the in-app "Save Defaults" pipeline that snapshots localStorage into tinyworld-defaults.json. Also covers the inline-script regex gotcha that has burned us twice.devopsgonodeVotes: 0GitHub stars: 1,587
Tinyworld Onboarding DriverAUse this skill when changing the TinyWorld onboarding tour, Guide button, or Driver.js integration.devopsnodeVotes: 0GitHub stars: 1,587
Tinyworld Flight SimAFlyable plane flight, ported from the standalone `ships/flight-sim3.html` arcade model. **The plane is NOT a bespoke tool or object kind** — it is the existing crop-duster / stunt-plane that the codebase already ships as a **model-stamp** (`models/stunt_plane.glb`, stamp id `stunt-plane`, label "Stunt Plane"), placed through the **Stamps** system. The placed cell is therefore `kind: 'model-stamp'` with `appearance.modelStampId === 'stunt-plane'`. Do not reintroduce a separate `plane` tool/kin...devopsgorailsVotes: 0GitHub stars: 1,587
Run ExperimentARuns existing Isaac Lab-Arena Experiment Definitions locally with experiment_runner.py in a ready native or Docker runtime, coordinates required local OpenPI or GR00T servers, applies local CLI overrides, and verifies generated result and report artifacts. Use for local named-Run or batch policy evaluations, variation listing, visualization or video, and result inspection. Do not use for installation or runtime preparation (setup-arena), pytest or regression checks (run-tests), interactive no...devopspythonshellVotes: 0GitHub stars: 592
C4 Codebase ArchitectureAHelps an agent inspect a repository and produce C4 architecture documentation. Use this when reverse engineering a codebase, documenting system context, containers, components, or clarifying architecture from code and infrastructure.devopsrustgoVotes: 0GitHub stars: 3
Setup Service MeshCDeploy and configure a service mesh (Istio or Linkerd) to enable secure service-to-service communication, traffic management, observability, and policy enforcement in Kubernetes clusters. Covers installation, mTLS configuration, traffic routing, circuit breaking, and integration with monitoring tools. Use when microservices need encrypted service-to-service communication, fine-grained traffic control for canary or A/B deployments, observability across all service interactions without applicat...devopsgobashVotes: 0GitHub stars: 31
Setup Local KubernetesDSet up a local Kubernetes development environment using kind, k3d, or minikube for fast inner-loop development. Covers cluster creation, ingress configuration, local registry setup, and integration with development tools like Skaffold and Tilt for automatic rebuild and redeploy workflows. Use when needing a local Kubernetes environment for development, testing manifests or Helm charts before production deployment, wanting fast automatic rebuild-and-redeploy cycles, or learning Kubernetes with...devopspythongoVotes: 0GitHub stars: 31
Setup Container RegistryAConfigure container image registries including GitHub Container Registry (ghcr.io), Docker Hub, and Harbor with automated image scanning, tagging strategies, retention policies, and CI/CD integration for secure image distribution. Use when setting up a private container registry, migrating from Docker Hub to self-hosted registries, implementing vulnerability scanning in CI/CD pipelines, managing multi-architecture images, enforcing image signing, or configuring automatic cleanup and retention...devopsrustgoVotes: 0GitHub stars: 31
Orchestrate Ml PipelineAOrchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.devopspythongoVotes: 0GitHub stars: 31
Optimize Cloud CostsAImplement cloud cost optimization strategies for Kubernetes workloads using tools like Kubecost for visibility, right-sizing recommendations, horizontal and vertical pod autoscaling, spot/preemptible instances, and resource quotas. Covers cost allocation, showback reporting, and continuous optimization practices. Use when cloud costs are growing without proportional business value, when resource requests are misaligned with actual usage, when manual scaling leads to over-provisioning, or when...devopsrustgoVotes: 0GitHub stars: 31
Manage Kubernetes SecretsBImplement secure secrets management in Kubernetes using SealedSecrets for GitOps, External Secrets Operator for cloud secret managers, and rotation strategies. Handle TLS certificates, API keys, and credentials with encryption at rest and RBAC controls. Use when storing sensitive configuration for Kubernetes applications, implementing GitOps where secrets must be version-controlled, integrating with AWS Secrets Manager or Azure Key Vault, rotating credentials without downtime, or migrating fr...devopsrustgoVotes: 0GitHub stars: 31
Implement Gitops WorkflowBImplement GitOps continuous delivery using Argo CD or Flux with app-of-apps pattern, automated sync policies, drift detection, and multi-environment promotion. Manage Kubernetes deployments declaratively from Git with automated reconciliation. Use when implementing declarative infrastructure management, migrating from imperative kubectl commands to Git-driven deployments, setting up multi-environment promotion workflows, enforcing code review gates for production, or meeting audit and complia...devopsgobashVotes: 0GitHub stars: 31
Enforce Policy As CodeAImplement policy-as-code enforcement using OPA Gatekeeper or Kyverno to validate and mutate Kubernetes resources according to organizational policies. Covers constraint templates, admission control, audit mode, reporting violations, and integrating with CI/CD pipelines for shift-left policy validation. Use when enforcing resource configuration standards, preventing security misconfigurations such as privileged containers, ensuring compliance before deployment, standardizing naming conventions...devopsgobashVotes: 0GitHub stars: 31
Deploy Ml Model ServingBDeploy machine learning models to production serving infrastructure using MLflow, BentoML, or Seldon Core with REST/gRPC endpoints, implement autoscaling, monitoring, and A/B testing capabilities for high-performance model inference at scale. Use when deploying trained models for real-time inference, setting up REST or gRPC prediction APIs, implementing autoscaling for variable load, running A/B tests between model versions, or migrating from batch to real-time inference.devopspythongoVotes: 0GitHub stars: 31
Configure Log AggregationASet up centralized log aggregation with Loki and Promtail (or ELK stack), including log parsing, label extraction, retention policies, and integration with metrics for correlation. Use when consolidating logs from multiple services into a searchable system, replacing local log files with centralized queryable storage, correlating logs with metrics and traces, implementing structured logging with label extraction, or troubleshooting production incidents requiring cross-service log analysis.devopspythongoVotes: 0GitHub stars: 31
Configure Ingress NetworkingAConfigure Kubernetes Ingress networking with NGINX Ingress Controller, cert-manager for automated TLS certificate management, path-based routing, rate limiting, and multi-domain hosting with SSL termination and load balancing. Use when exposing multiple Kubernetes services via a single load balancer, implementing path-based or host-based routing, automating TLS certificate issuance with Let's Encrypt, or setting up blue-green and canary deployments with traffic splitting.devopsrustgoVotes: 0GitHub stars: 31
Build Ci Cd PipelineADesign and implement multi-stage CI/CD pipelines using GitHub Actions with matrix builds, dependency caching, artifact management, and secret handling. Create workflows that span linting, testing, building, and deployment stages with parallel execution and conditional logic. Use when setting up automated testing and deployment for a new project, migrating from Jenkins or CircleCI to GitHub Actions, implementing matrix builds across platforms, adding build caching, or creating multi-stage pipe...devopsrustgoVotes: 0GitHub stars: 31
Setup Local KubernetesD使用 kind、k3d 或 minikube 搭建本地 Kubernetes 开发环境，实现快速内循环开发。涵盖集群创建、Ingress 配置、本地注册表设置，以及与 Skaffold 和 Tilt 等开发工具的集成，实现自动重建和重新部署工作流。适用于需要本地 Kubernetes 环境进行开发、在生产部署前测试清单或 Helm chart、希望快速自动重建部署循环，或在无云成本的情况下学习 Kubernetes 的场景。devopspythongoVotes: 0GitHub stars: 31
Orchestrate Ml PipelineAOrchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.devopspythongoVotes: 0GitHub stars: 31
Optimize Cloud CostsA使用 Kubecost 等工具为 Kubernetes 工作负载实施云成本优化策略，包括可见性分析、资源规格调整建议、水平和垂直 Pod 自动扩缩容、 Spot/可抢占实例和资源配额。涵盖成本分配、分摊报告和持续优化实践。适用于云成本增长与业务价值不匹配、资源请求与实际使用不一致、手动扩缩容导致过度配置，或需要为内部成本问责实施分摊计费的场景。devopsbashnodeVotes: 0GitHub stars: 31
Deploy Ml Model ServingBDeploy machine learning models to production serving infrastructure using MLflow, BentoML, or Seldon Core with REST/gRPC endpoints, implement autoscaling, monitoring, and A/B testing capabilities for high-performance model inference at scale. Use when deploying trained models for real-time inference, setting up REST or gRPC prediction APIs, implementing autoscaling for variable load, running A/B tests between model versions, or migrating from batch to real-time inference.devopspythongoVotes: 0GitHub stars: 31
Configure Log AggregationA使用 Loki 和 Promtail（或 ELK 栈）设置集中式日志聚合，包括日志解析、标签提取、保留策略及与指标的集成关联。适用于将多服务日志整合到可搜索系统、用集中式可查询存储替代本地日志文件、将日志与指标和追踪关联、实现带标签提取的结构化日志记录，或排查需要跨服务日志分析的生产事故。devopspythongoVotes: 0GitHub stars: 31
Configure Ingress NetworkingA使用 NGINX Ingress Controller 配置 Kubernetes Ingress 网络，支持通过 cert-manager 自动管理 TLS 证书、基于路径的路由、速率限制，以及带 SSL 终止和负载均衡的多域名托管。适用于通过单个负载均衡器暴露多个 Kubernetes 服务、实现基于路径或主机的路由、使用 Let's Encrypt 自动化 TLS 证书签发，或设置带流量拆分的蓝绿和金丝雀部署。devopsgobashVotes: 0GitHub stars: 31