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BigQuery Lakehouse — Google Cloud Architecture Template
A zoned data lakehouse: raw and curated Cloud Storage zones feeding BigQuery through Data Fusion and Dataflow, with Dataproc for ad-hoc Spark.
Why this architecture works
- Raw and curated zones separate immutable landings from validated, consumable data.
- Data Fusion provides governed, low-code ELT with built-in lineage tracking.
- BigQuery external plus native tables let you query the lake without duplicating everything.
- CMEK via Cloud KMS keeps encryption keys under your control for compliance.
- Dataproc spins up ephemeral Spark clusters against the curated zone, avoiding idle cluster cost.
What's inside (9 resources)
Raw Zone
gcp-cloud-storage
Curated Zone
gcp-cloud-storage
Data Fusion ELT
gcp-data-fusion
Transformations
gcp-dataflow
Lakehouse Warehouse
gcp-bigquery
Ad-hoc Spark
gcp-dataproc
Dataset ACLs
gcp-iam
CMEK Keys
gcp-kms
Cloud Monitoring
gcp-monitoring
From template to running infrastructure
- Open this template in the CloudForge visual designer (free account, no credit card).
- Customize resources, names, and connections on the drag-and-drop canvas — or ask Vani, the AI architect, to adapt it.
- Generate production-ready Terraform or Pulumi in one click.
- Review the plan diff and security scan, then deploy with human approval.