AWS for Industries
Category: Automotive
Rivian accelerates production with second-generation AWS Outposts: Improving resiliency and reducing costs
In this blog post, we show how Rivian, a leading innovator in the electric vehicle market, is using this feature to support modern containerized workloads and highly available database architectures for their critical manufacturing workloads at the edge.
How Toyota securely deployed HiveMQ with mTLS on AWS to power Smart Manufacturing
This blog post covers how Toyota deployed HiveMQ on Amazon ECS with mutual TLS (mTLS) for a secure, scalable IIoT architecture, now scaling beyond a successful single-plant pilot across all North American facilities.
Accelerating Android Builds on AWS: From 3 Hours to Under 5 Minutes with SourceFS
In this post, we explore how SourceFS from Source.dev, running on AWS, transforms the AOSP build experience – reducing end-to-end checkout-and-build time from 3 hours to under 5 minutes. We highlight how leading automotive OEMs are achieving material gains in build velocity, cost efficiency and developer productivity by using SourceFS.
Building a Serverless Supply Chain Management Solution for Automotive Customers with AWS AppSync and Amazon Aurora Serverless
In this blog post, we demonstrate how to build a serverless supply chain management solution tailored for automotive customers using AWS AppSync (a managed GraphQL service) and Amazon Aurora Serverless (an on-demand, auto-scaling relational database). This solution addresses common challenges in managing parts inventory, orders, and shipments by using a fully serverless, GraphQL-based approach.
Driving Intelligent Quality in the Software-Defined Vehicle Era
This blog will cover how PQD enables the transformation of after-sales vehicle quality from a reactive to a proactive, data-driven approach enabled by connected vehicle data, software-defined architectures, and AI/ML services from AWS.
The Evolution of BMW Group’s 3D Streaming Experience
In this blog post, we’ll explain why BMW Group chose Amazon Web Services, Inc. (“AWS”) as its cloud provider to deliver this user experience and dive deep into how the team solved the technical challenges along the way.
Building an End-to-End Physical AI Data Pipeline for Autonomous Vehicle 3.0 on AWS with NVIDIA
Autonomous Vehicles (AV) development has been maturing and is advancing through clear architectural changes: AV 1.0: classical modular stacks (perception → prediction → planning → control) with hand-engineered interfaces AV 2.0: multi-modal LLM end-to-end (E2E) learned stacks that reduce modularity and improve scaling with data AV 3.0: end-to-end reasoning VLA (Vision–Language–Action) systems that perceive, reason, […]
Multi-Agent AI Solution for Vehicle Fleet Data Discovery and Edge Case Classification
Every day, autonomous vehicle (AV) fleets generate terabytes of sensor data—but the rarest, most safety-critical moments often go undetected. Autonomous vehicle manufacturers and Tier 1 suppliers face a specific challenge: identifying which driving scenarios their vehicles encounter and deciding which edge cases require safety validation. As fleets grow, organizations cannot scale manual review to find these rare […]
DR Strategies for Connected Mobility Workloads, Part 1: Backup and Restore
Introduction Connected Mobility (CM) integrates vehicles, infrastructure, and data analytics to enhance user experience, safety, and reduce emissions. System resilience is critical as disruptions can cause: 1/direct customer impact on vehicle remote functions 2/brand reputation damage through negative publicity 3/manufacturing disruptions 4/revenue loss and legal consequences. Disaster Recovery (DR) is essential to prepare for natural […]
Accelerating mainframe modernization: How Toyota Motor Europe (TME) uses Amazon Bedrock to automate legacy code documentation
Toyota Motor Europe NV/SA (TME) oversees the wholesale sales and marketing of Toyota, GR (GAZOO Racing), Lexus vehicles, parts and accessories, as well as Toyota’s European manufacturing and engineering operations. As part of their strategic Legacy Modernization program, TME is exploring the use of generative artificial intelligence (generative AI) to accelerate their mainframe migration efforts. […]









