Azure
Data & Analytics
intermediate
Real-Time Streaming Ingestion — Azure Architecture Template
Event Hubs ingests high-volume telemetry into Stream Analytics, splitting hot-path Cosmos DB writes from cold-path lake archive.
Why this architecture works
- Event Hubs partitioning gives ordered, replayable ingestion at millions of events per second
- Hot/cold path split: Cosmos DB for dashboards now, the lake for cheap replay and batch analytics later
- Stream Analytics SQL jobs mean windowed aggregation without managing any cluster
- An alert function reacts to anomalies inline instead of waiting for batch cycles
- Job diagnostics stream to Log Analytics so watermark delay and SU pressure are alertable
What's inside (8 resources)
Event Ingest
event-hub-namespace
Alert Handler
function-app
Stream Processing
stream-analytics
Raw Archive
data-lake-gen2
Hot Store
cosmos-db
Lake Storage
storage-account
Secrets
key-vault
Logs
log-analytics-workspace
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, ARM, or Bicep in one click.
- Review the plan diff and security scan, then deploy with human approval.