Device and IoT data
Thousands of devices sending readings that end up in reports.
My stack for this
- 01AWS IoT Core
Cheapest AWS front door if devices speak MQTT.
- 02Amazon SQS
Buffer, then batch into Lambda.
- 03Neon (serverless Postgres)
Postgres wins for ingest-and-report.
Don't
- API Gateway
A per-request HTTP front door for a stream of tiny messages. At 216M messages a month, the REST API alone costs about $756. The whole IoT Core pipeline, processing included, costs about $215–230.
Instead: AWS IoT Core
- Amazon SNS
SNS invokes Lambda once per message: at device volumes that's millions of tiny invocations. SQS lets Lambda take them in batches.
Instead: Amazon SQS
- Cloudflare Durable Objects
Each object only sees its own data, so there's no SQL across devices for reports. Use them only for sending commands back to devices; the readings belong in Postgres.
Instead: Neon (serverless Postgres)
The picks, in brief
What each one is, my verdict, and what it costs. Every name opens the full entry: when to use it and when not, the gotchas with their fixes, provisioning and alternatives.
The cheapest AWS front door for device data, when the devices speak MQTT.
Pricing: Sydney: $0.096 per million connection-minutes, $1.20 per million messages (metered in 5 KB steps), $0.18 per million rules triggered plus $0.18 per million actions. Basic Ingest messages carry no messaging charge. In my IoT example (5,000 devices, one message a minute), IoT Core → SQS → batched Lambda → Postgres ≈ $215–230 a month vs about $1,014–1,109 for API Gateway REST → SNS → Lambda.
The queue in front of Lambda. Natural back-pressure, nearly free when batched.
Pricing: Sydney: $0.40 per million requests (Standard), $0.50 (FIFO). A request carries up to 10 messages, so batching cuts the bill tenfold: 50M messages ≈ $6 batched, $60 unbatched.
My go-to Postgres. Scales to zero, branches like git, and talks HTTP so Lambda needs no VPC or proxy.
Pricing: Launch plan $0.106 per compute-unit hour, Scale $0.222; storage $0.35/GB-month; no minimum. Available in Sydney.
Where they sit
The layers of the stack this job touches, with every tool named on this page.
Edge
Between your users and your backend.
APIs, queues and events
How requests and events move.
Data
Databases, migrations and the data lake.
Want this stack in your AWS account?
Cloudless Labs is a Sydney consultancy. We migrate on-premises systems to AWS, build serverless apps on this stack, and coach teams to ship with Claude Code and Codex.