IoT & Edge Computing

Connect, secure, and analyze billions of devices.

1 session at the summit4 external resources

Overview

AWS IoT spans device software (FreeRTOS, AWS IoT Greengrass), connectivity (AWS IoT Core supports MQTT, MQTT-over-WebSockets, HTTPS), data services (IoT SiteWise for industrial, IoT TwinMaker for digital twins, IoT FleetWise for vehicles), and analytics. For edge compute, AWS Outposts brings AWS to your data center, AWS Wavelength brings it to 5G networks, and Local Zones bring it to metro areas.

Key concepts

  1. MQTT and pub/sub messaging
  2. Device shadows and desired vs. reported state
  3. Greengrass — Lambda and ML at the edge
  4. Digital twins and industrial data models
  5. OTA firmware updates and fleet management

Key AWS services

  • AWS IoT Core
  • AWS IoT Greengrass
  • AWS IoT SiteWise
  • AWS IoT TwinMaker
  • AWS Outposts

Learn more — curated resources

Hand-picked official docs, foundational papers, and the best community guides for going deeper on this topic.

Sessions on this topic

1 session from the Summit covered this topic. Each is a self-contained mini-lesson.

  1. DEV207Intermediate

    Data Observability Without the Pain - Lessons from a Production System

    Modern IoT platforms are inherently data platforms. Events flow through APIs, queues, AWS Lambda Serverless functions, storage systems, and device networks before becoming meaningful data. When something goes wrong, tracing a single event across these distributed components quickly becomes painfuland the question shifts from _what happened_ to _where do I even start looking Ill walk through three practical observability patterns drawn from building and operating a production, event-driven IoT healthcare platform on AWS that processes tens of thousands of device events daily. Using OpenTelemetry, AWS X-Ray and Honeycomb, well explore techniques for gaining visibility into asynchronous event pipelines, correlating activity across services, and tracing events as they move through distributed systems. Youll leave with three concrete patterns you can apply immediately to your own event-driven data systems.

Non-obvious insights

From the Playbook

One sharp, contrarian insight per session — the things teams don't think of unprompted.

The biggest observability win is not tools — it's a *correlation ID standard* the team enforces. Pick one (the X-Ray trace ID is fine), enforce it everywhere, and stop debating. Tooling matters far less than you think once the IDs are consistent. ---DEV207 — Data Observability Without the Pain - Lessons from a…