Real-time Analytics Platform Architecture Template
Ingest events, process streams, and serve live dashboards. Generate a complete cloud architecture with cost estimates, Terraform, sequence diagrams, CLI deployment workflows, and a GitHub Actions pipeline — on AWS, Azure, or GCP.
Production estimates. Your workspace generates actuals.
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
cloud services
AWS Architecture Diagram
Full topology with all services and request flows — switch providers above to compare.
Real-time Analytics Platform - AWS - Production implementation lanes - CloudDesign AI
Architecture Breakdown
Every major component, what it does, and the AWS service powering it.
Event Ingestion
Amazon API Gateway
Handles business logic and integrates with surrounding services.
Stream Processor
Amazon Kinesis Data Streams
Handles business logic and integrates with surrounding services.
Data Warehouse
Amazon Redshift
Handles business logic and integrates with surrounding services.
Query Cache
Amazon ECS Fargate
Serves high-frequency reads at sub-millisecond latency.
Dashboard API
Amazon CloudFront
Routes, authenticates, and rate-limits incoming requests.
Raw Archive
Amazon S3 (Parquet)
Handles business logic and integrates with surrounding services.
Alerting
AWS Lambda
Handles business logic and integrates with surrounding services.
Metadata Store
Amazon Redshift
Stores and retrieves data with durability and access controls.
Cost Estimate — AWS
Representative production estimate. Your workspace generates a breakdown based on your actual configuration.
AWS — $575 / month estimated
Kinesis
Event ingestion
Lambda
Stream processor
Redshift
Data warehouse
ElastiCache
Query cache
API Gateway
Dashboard API
S3
Raw archive
CloudWatch
Alerting
RDS
Metadata store
Total estimate
$575 / month
What CloudDesign AI Generates
Every generation produces a complete set of production-ready artifacts.
Architecture Diagram
Full topology showing every service and how traffic flows between them.
Sequence Diagrams
Request lifecycle flows for upload, query, and overall system paths.
Cost Analysis
Per-service cost breakdown with total estimate for the selected provider.
Terraform Code
Complete infrastructure-as-code export you can deploy immediately.
CLI Deployment Workflow
Ordered provisioning commands for every service in the architecture.
GitHub Actions Pipeline
Ready-to-commit `.github/workflows/terraform.yml` for CI/CD.
Tradeoff Analysis
Cost, scalability, reliability, and operational complexity breakdown.
Production Checklist
Architecture-specific risks and mitigations before you go live.
Terraform Preview — AWS
Provider-specific infrastructure code. The full export is available after generating.
resource "aws_kinesis_stream" "events" {
name = "${var.prefix}-events"
shard_count = 4
}
resource "aws_redshift_cluster" "warehouse" {
cluster_identifier = "${var.prefix}-warehouse"
node_type = "ra3.xlplus"
number_of_nodes = 2
}
resource "aws_elasticache_replication_group" "cache" {
replication_group_id = "${var.prefix}-cache"
node_type = "cache.r7g.large"
}
# + 310 more lines — generate the full export →Full Terraform export includes: variables, outputs, IAM roles, environment configs, and module structure.
Generate Full TerraformCLI Preview — AWS
Ordered provisioning commands for every service. The full workflow is generated in your workspace.
aws kinesis create-stream --stream-name $PREFIX-events --shard-count 4
aws redshift create-cluster --cluster-identifier $PREFIX-warehouse \
--node-type ra3.xlplus --number-of-nodes 2
aws elasticache create-replication-group \
--replication-group-id $PREFIX-cache --cache-node-type cache.r7g.large
# + 22 more commands — generate the full workflow →Full CLI workflow includes: bucket creation, networking, IAM setup, application deployment, and health checks — in order.
Generate Full CLI WorkflowCloud Provider Mapping
Every architectural function mapped to its native service on AWS, Azure, and GCP.
Architecture Tradeoffs
How AWS, Azure, and GCP compare across the dimensions that matter most for this architecture.
Query Performance
BigQuery's serverless architecture and columnar storage consistently outperforms Redshift and Synapse for ad-hoc OLAP queries.
Cost at Scale
BigQuery charges per-query (no idle cluster cost); Redshift and Synapse incur reserved node costs regardless of usage.
Streaming Throughput
All three providers handle millions of events per second at the ingestion layer.
Operational Simplicity
BigQuery and Pub/Sub require almost no capacity planning; Kinesis and Redshift require shard/node sizing.
Ecosystem Integration
AWS has the widest range of analytics tool integrations (QuickSight, Glue, EMR, Athena).
Production Risks for This Architecture
Known failure modes with concrete mitigations — included in every generated checklist.
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
Key Capabilities Covered
Frequently Asked Questions
Common questions about this architecture and what CloudDesign AI generates.
Generate the Real-time Analytics Platform Architecture
Get the full architecture diagram, cost breakdown, Terraform, CLI workflow, and GitHub Actions pipeline — specific to your chosen cloud provider.
Free account · No credit card required · 5 architecture runs per month