# BLUEPRINT-AWS-SERVERLESS
Billions-per-day audience distribution
Fully automated, serverless data pipeline for audience-segment delivery at scale — Step Functions orchestrates every step end-to-end, on-demand EMR and Glue handle compute with zero idle cost, codified end-to-end as IaC.
# THE-PROBLEM
why this pattern exists.
Distributing audience segments at scale means moving billions of records per day to many downstream destinations — each with its own API shape, rate limits, quota semantics, and failure modes. Manual hand-offs don't scale; naive parallelism gets rate-limited into oblivion; every destination has a different notion of 'done'. What you actually want is a fully automated pipeline that handles ingestion, transformation, delivery, retry, and quota recovery without a human in the loop.
The hard part isn't pushing data — it's coordinating many concurrent deliveries on shared compute while respecting per-destination quotas, recovering gracefully when an upstream API defers work, and keeping the whole thing auditable. You want one platform where stack boundaries are permission boundaries, capacity scales with use, and the entire footprint is codified — not a scheduler service bolted onto a fleet of always-on workers.
# ARCHITECTURE
how it's built.
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Fully automated end-to-end pipeline
Once a destination is configured, segments flow end-to-end without human touchpoints. Step Functions models the entire delivery lifecycle — ingestion, optional Glue transformation, EMR-based processing, delivery via API or SFTP, retry accounting, and quota-deferral recovery — as a single replayable, audit-logged workflow.
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Serverless from edge to data plane
API Gateway + Lambda for the control plane, Step Functions for orchestration, on-demand EMR and Glue for compute, Aurora Serverless v2 for transactional reads. No always-on servers, no parked clusters, no idle queues. Every component scales with use and releases capacity on completion.
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Zero standby cost
Capacity is provisioned per job and released when work drains. You pay for processing minutes, not for over-provisioned headroom. The serverless-first posture is what makes the platform materially cost-efficient even at billions of records per day.
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Resilient by construction
Typed Catch handlers per workflow phase, SQS DLQs with redrive policies, per-destination state machines that isolate failures, and a DynamoDB-backed distributed lock with heartbeat-refreshed leases for jobs that share upstream quota. A single failed delivery never stalls the rest of the platform.
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Infrastructure as code, end-to-end
Every Lambda, queue, state machine, IAM role, KMS key, and API Gateway route is codified as Serverless Framework + CloudFormation. Per-stage configuration and CloudFormation cross-stack exports drive deterministic, zero-downtime deploys; the platform stands up in a fresh AWS account in hours, not weeks.
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Security & least privilege by default
A custom Serverless plugin attaches an account-level IAM permission boundary to every generated role. Per-function IAM statements, KMS-encrypted queues/tables, a VPC-bound Lambda tier, and an IP-allowlisted API Gateway resource policy complete the posture. Security is in the build, not bolted on.
# KEY-PRIMITIVE
the load-bearing idea.
End-to-end orchestration as code, no human in the loop
The architectural decision that makes this 'fully automated' is modeling each destination's complete delivery lifecycle as a Step Functions state machine — file ingestion, optional Glue transformation, EMR-based processing, API or SFTP delivery, retry accounting, and quota-deferral recovery — all expressed in code, all replayable, all audit-logged. Native service integrations (glue:startJobRun.sync) handle batch transforms; typed Catch handlers cover every failure mode; a DynamoDB-backed distributed lock with conditional-write acquisition and heartbeat-refreshed leases coordinates jobs that must respect upstream rate limits. The result is a pipeline you can leave running unattended for years.
# TECH-STACK
what runs it.
# PRODUCTION-EVIDENCE
what we've measured.
Fully automated, serverless data delivery at internet scale. Years in production.
This is a working platform — not a POC, not a demo. The serverless-first design means there's no idle compute cost: pipelines spin up per job and release capacity on completion. Once a destination is configured, segments flow end-to-end without human touchpoints — ingestion, transformation, delivery, retry, and quota recovery all happen in code. Every component is codified as IaC, so changes ship as zero-downtime deploys and the platform extends to new destinations by registering a state machine, not by redeploying the runtime.
- Records processed
- Billions/day
- Idle / standby cost
- Zero
- Pipeline automation
- End-to-end
- In production
- Years
want one of these in production?
30-min discovery call. we adapt the blueprint, we don't resell it.
book-call// or write: hello@saloid.com · gräfelfing · de