Individual skill
google-cloud-solution-agentic-ai-borderless-data-lakehouse
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).
skills/cloud/google-cloud-solution-agentic-ai-borderless-data-lakehouse/SKILL.md
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- Last checked
- Nov 4, 2026
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- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
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- google Repository topic
- googlecloud Repository topic
- skills Repository topic
- data Derived category
- devops Derived category
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SKILL.mdcore · 10,365 bytesassets/output-template.mddoc · 6,606 bytesreferences/attribution.mddoc · 2,022 bytesreferences/design_recommendations.mddoc · 5,045 bytesreferences/product_mapping.mddoc · 3,833 bytesreferences/product_renaming.mddoc · 1,523 bytes
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# Borderless open data lakehouse agentic AI system
Follow this workflow to help users design and implement a custom multi-product
solution in the cloud for a given workload, use case, or requirement.
## Attribution
**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you
MUST read and follow the instructions in
[Usage Attribution](references/attribution.md).
## Product Renaming & Terminology
When generating solution designs, architecture diagrams, and documentation, use