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Run OpenShell’s Release Canary checks to verify that published development packages and Helm charts install and support basic sandbox operations. Use workflow logs and local Kubernetes reproduction steps to investigate failures before a public release.
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Create GitHub Actions workflows to automate testing, builds, and deployments. Includes patterns for Docker image publishing, Kubernetes deployment, security scans, and testing across multiple environments, plus reusable workflows and approval steps for production releases.
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Plan and configure security across Google Kubernetes Engine clusters. Review access permissions, enable Secret Manager integration, and configure protections such as Shielded Nodes and Binary Authorization to strengthen the platform supporting your applications.
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Helps deploy, manage, and troubleshoot applications on Kubernetes using kubectl and Helm. Covers container logs, resource settings, network access, and deployment strategies to investigate failures and review how applications run.
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Create reusable Helm charts, packages of Kubernetes deployment templates and settings. The skill guides environment configuration, dependency management, shared templates, and release procedures so applications can be deployed across environments with fewer template changes.
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Set up WizTelemetry Events to collect and store Kubernetes events in KubeSphere. Configure index retention policies and use the query API to filter warnings, inspect resource events, generate statistics, or export matching records.
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Create Kubernetes deployment files and Helm charts, reusable application packages. Configure permissions, network isolation, and persistent storage, then investigate pod failures and resource usage to adjust workloads and verify deployment health.
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Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
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Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
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ベストプラクティスとセキュリティ標準に従った、Deployment、Service、ConfigMap、Secret用の本番環境対応Kubernetesマニフェストの作成。KubernetesYAMLマニフェストの生成、K8sリソースの作成、本番グレードのKubernetes構成の実装に使用します。
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Investigate Kubernetes permissions and cluster behavior in CTF sandboxes. Trace role-based access control, service accounts, and automated controllers to explain workload changes, secret exposure, and differences between configuration files and live objects.
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Design and review infrastructure and release workflows with checks tailored to the environment. Covers automated build and deployment pipelines, containers, health checks, rollback plans, feature flags, and mobile releases to help assess readiness before deployment.
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Create CI/CD configurations, which automate build, test, and deployment steps, alongside Terraform infrastructure templates and Kubernetes deployment files. Generate health-check and rollback instructions to review before applying changes to cloud infrastructure or application environments.
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Set up a managed Kubernetes environment on Google Cloud, from choosing Autopilot or Standard to creating a GKE cluster, obtaining kubectl connection credentials, and deploying workloads. Includes guidance on private clusters and resource requests.
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Guides an application’s first deployment to GKE, Google’s managed Kubernetes service. Covers application assessment, container creation, image storage, deployment configuration, security settings, health checks, and verification that the application is running.
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Plan and create Google Kubernetes Engine clusters using templates for production, development, or AI workloads. Compare Google-managed and self-managed node options, review configurations before creation, and check settings for production readiness.
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Create or update Kubernetes YAML configuration files for GKE Autopilot and Standard. Translates application requirements into manifests covering container permissions, CPU and memory allocation, health checks, storage, external routing, and GPU resources for AI model serving.
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Inspect KubeSphere clusters with read-only commands. List clusters, view detailed configuration, identify host and member roles, and review connection types, readiness indicators, and KubeSphere and Kubernetes versions without changing cluster resources.
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Manage credentials for Git access and deployments in KubeSphere DevOps. Covers SSH keys, passwords, API tokens, and Kubernetes connection settings, including their use in Jenkins pipelines and troubleshooting synchronization failures.
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Set up and manage a local Kubernetes development environment for OpenShell using k3d, Skaffold, and Helm. Build and deploy changes, inspect traces, configure optional authentication components, and test behavior across multiple gateway replicas.
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Set up NVIDIA infrastructure for synthetic data generation on MicroK8s or Azure AKS. Coordinate Kubernetes, inference services, and OSMO workflow execution, with prerequisite checks, deployment validation, capacity planning, and failure investigation before workloads are retried.
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Build GitLab workflows that automate building, testing, and deployment. The skill covers pipeline stages, dependency caching, runners that execute jobs, and manual approval before production deployment, with examples for Docker, Kubernetes, and Terraform.
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Develop and troubleshoot distributed applications with Aspire. Coordinate services written in different languages through AppHost, configure connections and startup dependencies, inspect logs and metrics, and prepare deployment settings.
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Use Stratus Red Team to simulate attack techniques across AWS, Azure, GCP, and Kubernetes. Prepare test resources, run and repeat simulations, check logs and alerts, and remove resources to assess whether security detections work.
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