94건 · 관련도순
Assess Google Cloud workloads for environmental sustainability using the Well-Architected Framework. Get recommendations on lower-carbon regions, efficient computing and storage, AI energy use, and ongoing emissions measurement with Carbon Footprint.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Design a Google Cloud system that combines multiple services, starting with a discussion of business and technical requirements. The skill produces service recommendations, architecture diagrams, deployment guidance, and validation plans, with user approval at each stage.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud. Use when designing end-to-end cloud solutions, selecting and integrating Google Cloud services, generating architecture diagrams, or conducting requirements discovery for new cloud workloads or migrations. Don't use for single-product tasks (use product-specific skills), initial onboarding or authentication (use google-cloud-recipe-*), Well-Architected Framework reviews or audits (use google-cloud-waf-*), or workloads covered by specialized solution skills.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Helps address Google Cloud Security Command Center findings by planning targeted fixes for permissions, misconfigurations, vulnerabilities, and combined attack paths. It includes impact checks, verification, rollback steps, and execution after user approval.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Design a shared data platform across Google Cloud, AWS, and Azure for analytics and AI. The skill turns requirements into architecture diagrams, infrastructure code, deployment instructions, and validation checks using Apache Iceberg and BigQuery data agents.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Plan and build AI agents on Google Cloud, from gathering requirements to choosing a single-agent or multi-agent design. Produce architecture diagrams, deployment code and instructions, and validation plans tailored to the workload.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Design AI agent analytics workflows across distributed tables and documents. Combine Knowledge Catalog for metadata, meaning information about data and its usage rules, with managed Spark processing to produce architecture diagrams, deployment guidance, and validation plans.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Design and create new Cloud Storage buckets for uses such as backups, media, and AI data. Check project security and name availability, choose storage and protection settings, and produce creation commands or code in the preferred format.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Helps choose and tune Cloud Storage FUSE mounts, which expose bucket objects through file paths. It covers cache sizing, training performance, checkpoint write safety, and cost diagnosis on GKE, Compute Engine, and Cloud Run.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Generate Python code to clean, transform, analyze, visualize, and model BigQuery data with BigQuery DataFrames. The skill keeps processing in the cloud and uses familiar table operations, with guidance for previews, schema checks, and machine learning.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Discovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Creates Cloud Storage (Google Cloud Storage, or GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Designs, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Deploys a baseline landing zone foundation for a Google Cloud Organization, establishing security guardrails using Organization Policies, resource hierarchy folders and projects, billing association, and centralized logging and monitoring. Deploys Google Cloud's recommended security controls and architecture. Use when setting up a new Google Cloud Organization or establishing a secure, enterprise-grade landing zone foundation. Don't use for individual project onboarding (use google-cloud-recipe-onboarding or product-specific skills instead).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Mounts Cloud Storage buckets as a POSIX file system with Cloud Storage FUSE (gcsfuse). Use when interacting with gcsfuse: decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size file, stat, and list caches, tune mount flags or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and config files, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or fully POSIX-compliant shared file systems (Filestore, Managed Lustre).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Guides migration of existing AI inference workloads to self-hosted GKE, Google’s managed Kubernetes service. Covers requirements, GPU sizing, deployment configuration, model storage, validation, and traffic cutover using gcloud and kubectl.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Retrieve security findings from Google Cloud Security Command Center for initial assessment. Filter active vulnerabilities, threats, and external exposures, inspect one finding’s full details, or group counts by category to understand the reported risks.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Helps individual developers get started on Google Cloud by checking local tools and authentication, selecting or creating a project, and linking billing. It verifies the setup and directs users to specialized guides for their first deployment.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.