Real-time Analytics Platform architecture template
Ingest events, process streams, and serve live dashboards. Generate a complete cloud architecture with cost estimates, Terraform, diagrams, and deployment workflows — on AWS, Azure, or GCP.
$250 – $700 / month on AWS
Typical production setup. Your actual cost is generated based on your specific configuration.
Architecture overview
Buffers incoming events via a message queue, processes streams in a managed pipeline, stores results in a columnar warehouse, and serves live dashboard queries through a read-optimized API with per-tenant isolation.
~8 services
Sample architecture diagram
graph TD
A[Event Sources] --> B[Kinesis
Data Streams]
B --> C[Lambda
Processor]
C --> D[Redshift
Warehouse]
C --> E[S3
Raw Archive]
D --> F[ElastiCache
Query Cache]
F --> G[Dashboard API]Terraform preview
Each generated workspace includes provider-aware Terraform starter modules, deployment variables, and environment notes for the selected cloud provider. This preview is intentionally short so the public page stays readable while still showing search engines the implementation artifact.
module "app_platform" {
source = "./modules/app-platform"
environment = "production"
region = var.primary_region
}
module "observability" {
source = "./modules/observability"
service_ids = module.app_platform.service_ids
}Production risks for this architecture
Redshift query latency under concurrent dashboard load: without workload management groups, a single heavy OLAP query can block all tenant dashboards — configure WLM queues with query timeouts
Kinesis shard hot partition on spiky traffic: if all events share the same partition key, a single shard becomes a bottleneck — use randomized suffix or user-id-based sharding from day one
Dashboard API timeout on full-table scans: pre-aggregate common dashboard metrics into summary tables during stream processing to avoid per-request warehouse scans