149 skills · sorted by relevance
Diagnose unresponsive GKE GPU or TPU nodes and pods stuck terminating through read-only checks of node status, logs, serial output, and repair history. Receive documented recovery guidance to apply yourself.
Set up an organization-wide Google Cloud foundation with 17 baseline security policies, environment folders and projects, billing links, and centralized audit logging and monitoring. Check the resulting setup against a defined validation checklist.
Design and implement Google Cloud serverless web apps with separate presentation, application, and data layers. Produces architecture diagrams, Terraform infrastructure code, deployment instructions, and validation scripts for private networking and controlled access between layers.
Inspect Google Cloud Filestore usage and free space, then propose capacity increases or decreases based on configured thresholds and storage tier limits. Apply resizing after confirmation to address low space or reduce excess capacity.
Browse and search files on Google Cloud Filestore, read selected log lines, and inspect permissions and timestamps. Uses a Cloud Run bridge or an existing virtual machine without requiring local NFS client packages or root access.
Check Google Cloud IAM allow policy changes against the last 90 days of access logs. The skill identifies access that could be lost and applies changes only after a successful simulation and user approval.
Define reliability goals for Google Cloud services and generate Terraform files for Cloud Monitoring SLO alerts. A guided conversation gathers service scope, measurement metrics, targets, and alert conditions, then explains the PromQL queries used to evaluate them.
Helps create and extend Apache Airflow DAGs, workflows that define task order and dependencies, for Managed Service for Apache Airflow. Covers environment checks, version compatibility, coding practices, and local or deployed validation.
Diagnoses applications that fail to start or repeatedly crash on GKE, Google's managed Kubernetes service. It examines logs, events, memory use, image pulls, and connectivity, then proposes configuration patches or commands without applying live changes.
Guides authentication and access permissions for Google Cloud users and applications. It helps choose credentials for local development, production services, or external clouds, with guidance on short-lived credentials and avoiding downloaded service account keys.
Evaluate Google Cloud workloads against built-in best practices or custom organizational rules using Workload Manager. Use public client libraries or the REST API to run checks, review violations and scanned resources, and export results to BigQuery.
Manage temporary access in Google Cloud with Privileged Access Manager. Configure who can request which roles and for how long, maintain access configurations, and handle access requests and approval decisions through guided workflows.
Investigate Google Cloud network problems using traffic logs, performance metrics, and connection path tests. Identify blocked traffic, packet loss, and latency, summarize traffic volumes, or estimate VPC Flow Logs costs.
Diagnose Google Cloud Filestore mount failures by checking client access rules, network firewalls, and audit logs. Distinguish permission errors from connection timeouts, then provide a structured report and remediation commands that require confirmation before execution.
Plan and manage Cloud Spanner databases on Google Cloud, design tables and primary keys, write SQL and client code, and investigate slow queries using database statistics to identify resource-intensive operations.
Adapt Airflow workflow definitions for newer versions in Google Cloud's managed service. The skill guides checks for incompatible code and dependencies, explains required changes, and supports requested deployment and verification for Airflow 2.11.1 or Airflow 3.
Deploy AI models on GKE with suitable GPUs or TPUs and model servers. Generate deployment configuration, adjust automatic scaling, and tune inference—the process of producing model responses—for memory use, throughput, and response time.
Plan and configure GKE cluster networks, including private nodes, IP address ranges, DNS, and outbound connectivity. Use the guidance to set up VPC-native networking and Dataplane V2, which provides built-in network policy enforcement.
Configure GKE logging, metrics collection, dashboards, and alerts with Cloud Logging, Cloud Monitoring, and managed Prometheus. Diagnose missing measurements, collection failures, permission errors, and alert rule problems to identify appropriate configuration changes.
Audit and strengthen security for applications running on GKE. Configure pod traffic restrictions, sandbox isolation, namespace security standards, and Secret Manager volume mounts to protect workloads at the application and namespace level.
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.
Investigate crashes, out-of-memory errors, and device initialization failures on GKE TPU v6e nodes. The skill checks logs and custom metrics collection for conflicting operations, then guides temporary mitigation by disabling an identified collector.
Diagnoses storage failures in GKE, Google's managed Kubernetes service, including stuck Pods, disk attachment errors, storage pressure, and missing volume expansion. It provides diagnostic commands and reviewable configuration patches for deployment through GitOps.
Configure and troubleshoot automatic node scaling in GKE. Examine logs and workload constraints to explain why nodes fail to grow or shrink, and guide tuning for capacity shortages, zone placement, and sudden traffic increases.