Google Cloud
Data & Analytics
intermediate
Dataflow Streaming Ingest — Google Cloud Architecture Template
Real-time ingestion from Pub/Sub through Dataflow into BigQuery for analytics, Bigtable for low-latency serving, and GCS for archive.
Why this architecture works
- One Dataflow pipeline fans out to analytics, serving, and archive sinks in a single pass.
- Bigtable serves single-digit-millisecond point reads that BigQuery is not built for.
- Exactly-once Dataflow semantics prevent duplicate rows in BigQuery during retries.
- The GCS archive is the cheap system of record for replays and backfills.
What's inside (7 resources)
Event Stream
gcp-pub-sub
Streaming Pipeline
gcp-dataflow
Analytics Warehouse
gcp-bigquery
Low-Latency Serving
gcp-bigtable
Cold Archive
gcp-cloud-storage
Cloud Monitoring
gcp-monitoring
Cloud Logging
gcp-logging
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.