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Configure how GKE applications receive traffic from the internet or internal networks. The skill provides configuration templates for routing, load balancing, certificates, and access protection, and guides diagnosis of failed health checks, dropped requests, and TLS connection problems.

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• Expose a GKE application through Gateway API or Ingress
• Split traffic between application versions during a rollout
• Configure Cloud Armor protection and HTTPS certificates

Plan and configure a shared GKE cluster for multiple teams or environments. Set up namespaces, team permissions, resource limits, and network separation, then use labels and GKE cost allocation to track spending by team.

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• Design a GKE cluster shared by multiple teams
• Separate development, staging, and production workloads
• Set team permissions and resource quotas

Review GKE reliability settings for applications running in Kubernetes. Configure availability safeguards during maintenance, health checks, replica counts, graceful shutdown, and distribution across zones and nodes to help workloads handle disruptions.

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• Reviewing GKE high availability
• Maintaining Pod availability during upgrades
• Configuring application health checks

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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• Review cluster access permissions
• Enable Secret Manager integration
• Configure Shielded Nodes and GKE Sandbox

Find relevant Google Cloud monitoring metrics for a service or resource. Retrieves current metric definitions through the API, filters them by the requested concepts, and presents selected metrics with their names, data types, units, and monitored resources.

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• Find CPU metrics for Compute Engine
• Identify Cloud Storage write throughput and request metrics
• Check metric data types and units

Evaluate a machine learning GPU cluster during a cloud trial or acceptance test. Measure GPU computing performance, communication within and between machines, and local and shared storage, then compile the results into a dated Markdown report.

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• Evaluating trial GPU machines from a cloud provider
• Running acceptance tests for a GPU cluster
• Measuring GPU performance under load from neighboring GPUs

Plan and troubleshoot large language and vision model training and inference. This guide uses hardware measurements to identify bottlenecks, address memory shortages and unstable training, and improve checkpointing, recovery, and performance across multiple GPUs and machines.

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• Diagnosing slow training and GPU memory shortages
• Investigating loss spikes and invalid numerical values
• Debugging communication hangs across GPUs and machines

Deploy and configure LangBot with Docker Compose or Kubernetes. Set up application settings, plugin execution, the Box sandbox for isolated commands, and API authentication, with guidance on hosting choices and common deployment problems.

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• Deploy LangBot on a self-hosted server
• Configure Box and the plugin runtime
• Enable API authentication for agent access

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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• Creating reusable Helm charts
• Separating development and production settings
• Managing dependencies and migration order

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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• Investigating repeatedly crashing containers
• Reviewing deployment and resource settings
• Troubleshooting service connectivity and DNS

Manage GPU compute jobs on Qizhi through a command-line tool. Find available nodes, submit distributed training runs, launch batches with different parameter combinations, and inspect, monitor, or stop jobs across workspaces.

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• Finding available GPU nodes across workspaces
• Submitting distributed training jobs
• Launching evaluation batches with different parameter combinations

Create and run KubeSphere DevOps pipelines connected to Jenkins to automate builds and tests. Covers branch-specific workflows, required input parameters, private repository credentials, execution monitoring, logs, and downloading build output files.

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• Create a pipeline that builds and tests a Go application
• Run builds for individual repository branches
• Configure credentials for a private repository

Set up KubeSphere’s WizTelemetry Data Pipeline to collect, transform, and route logs, audit data, events, and notifications. Configure delivery to OpenSearch, deploy agents across selected clusters, and check their operating status.

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• Setting up a shared collection pipeline for observability data
• Configuring delivery to OpenSearch
• Deploying agents across multiple clusters

Install and configure WizTelemetry Platform Service, the shared API backend for KubeSphere observability extensions. Generate configuration based on installed extensions, update installation settings, and inspect service health, pods, and logs.

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• Install the shared backend for observability extensions
• Regenerate configuration after changing extensions
• Check API server and console health

Install and configure OpenSearch for storing, searching, and analyzing KubeSphere logs, events, audit records, and notification history. Adjust storage and memory, enable a visualization interface, and manage scheduled cleanup of old search indexes.

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• Preparing storage for logs and event history
• Enabling OpenSearch Dashboards
• Adjusting storage capacity and memory

Set up and troubleshoot the WizTelemetry Notification extension for KubeSphere. Configure delivery channels such as email and Slack, route alerts by labels, silence notifications for scheduled periods, and search notification history to investigate delivery problems.

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• Configuring email or Slack alert delivery
• Routing alerts by severity or namespace
• Silencing notifications during maintenance

Manage OpenKruise in KubeSphere, from extension installation to troubleshooting. Generate SidecarSet configuration for adding helper containers and CloneSet configuration for application updates, including in-place changes and staged rollouts, with commands to apply and verify each configuration.

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• Install OpenKruise and check its status
• Add and update helper containers with SidecarSet
• Stage application image updates with CloneSet

Create and manage Volcano jobs and scheduling queues in KubeSphere. Use YAML templates for PyTorch, TensorFlow, MPI, and batch workloads, configure resource requests and execution policies, and investigate jobs that remain pending or fail to create pods.

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• Prepare distributed training jobs for PyTorch or TensorFlow
• Create MPI and batch processing jobs
• Configure queue capacity and scheduling weight

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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• Setting up Kubernetes event collection and storage
• Finding warnings for a specific resource or time range
• Generating event statistics and time-based counts

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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• Register credentials for private Git repositories
• Use deployment credentials in Jenkins pipelines
• Investigate credentials missing from Jenkins

Set up and troubleshoot automated build, test, and deployment workflows in KubeSphere DevOps. Covers Jenkins integration, project management, multi-cluster installation, and ArgoCD integration for deployments managed through Git.

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• Set up build, test, and deployment pipelines
• Configure Jenkins integration
• Install DevOps across multiple clusters

Manage KubeSphere extensions from discovery through installation, configuration, upgrades, and removal. Check dependencies and exact versions, prepare an InstallPlan deployment resource, and inspect status and logs to investigate installation or upgrade failures.

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• Find extensions and available versions
• Install a specific extension version
• Change settings or upgrade an extension

Operate FrontendIntegration resources from existing YAML definitions using kubectl, the Kubernetes command-line tool. Manage updates and enabled state, inspect build output, troubleshoot failures, and install or manage the frontend-forge extension.

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• Create a FrontendIntegration from existing YAML
• Update, enable, or disable a FrontendIntegration
• Inspect build output and troubleshoot failures

Manage users, team workspaces, and projects in KubeSphere through its API. Create accounts and resources, invite members, inspect existing access, and assign or change built-in permission roles with minimum access as the default.

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• Create user accounts with limited default access
• Create team workspaces and projects on selected clusters
• Invite members and assign built-in permission roles