Autonomous Driving Data Framework (ADDF) security and operations guide - AWS Prescriptive Guidance

Autonomous Driving Data Framework (ADDF) security and operations guide

Andreas Falkenberg, Junjie Tang, Torsten Reitemeyer, and Srinivas Reddy Cheruku, Amazon Web Services (AWS)

November 2022 (document history)

Autonomous Driving Data Framework (ADDF) is an open-source project designed to provide reusable, modular code artifacts for automotive teams who want to implement common tasks for advanced driver-assistance systems (ADAS), such as configuring centralized data storage, data processing pipelines, visualization mechanisms, search interfaces, simulation workloads, analytics interfaces, and prebuilt dashboards. Using ADDF, you can share, modify, or create fully customizable modules that reduce the amount of effort required to create and deploy these solutions.

This guide is intended to help you understand best practices for securely deploying and operating ADDF in the AWS Cloud. It discusses the following topics:

Intended audience

This guide is intended for Development Operations (DevOps) teams, infrastructure engineers, administrators, IT security staff, and incident response teams who are tasked with assessing, deploying, customizing, and operating ADDF. You can apply the recommendations in this guide for proof-of-concept or production environments.

This guide assumes you have no prior knowledge of ADDF. However, we recommend that you read the ADDF readme (GitHub) before proceeding.

Targeted business outcomes

This guide is designed to help you more confidently and securely set up and operate ADDF in development and production environments.