Automotive – Noise

Breaking down data silos: Volkswagen’s approach with Amazon DataZone

Bandana Das — Tue, 07 Oct 2025 17:28:21 +0000

In this post, we introduce Amazon DataZone and explore how Volkswagen used Amazon DataZone to build their data mesh, tackle the challenges encountered, and break the data silos.

How Stellantis streamlines floating license management with serverless orchestration on AWS

Göksel SARIKAYA — Thu, 12 Jun 2025 12:16:54 +0000

In this post, we explore a unique scenario where an ISV, unable to provide a floating license option for cloud usage, worked with Stellantis to develop an alternative solution. This approach, implemented with the ISV’s permission, treats named user licenses as if they were floating, automatically assigning and removing them based on the state of user workbench instances.

How Volkswagen Autoeuropa built a data solution with a robust governance framework, simplifying access to quality data using Amazon DataZone

Dhrubajyoti Mukherjee — Wed, 13 Nov 2024 15:46:47 +0000

This second post of a two-part series that details how Volkswagen Autoeuropa, a Volkswagen Group plant, together with AWS, built a data solution with a robust governance framework using Amazon DataZone to become a data-driven factory. Part 1 of this series focused on the customer challenges, overall solution architecture and solution features, and how they helped Volkswagen Autoeuropa overcome their challenges. This post dives into the technical details, highlighting the robust data governance framework that enables ease of access to quality data using Amazon DataZone.

How Volkswagen Autoeuropa built a data mesh to accelerate digital transformation using Amazon DataZone

Dhrubajyoti Mukherjee — Thu, 31 Oct 2024 16:00:01 +0000

In this post, we discuss how Volkswagen Autoeuropa used Amazon DataZone to build a data marketplace based on data mesh architecture to accelerate their digital transformation. The data mesh, built on Amazon DataZone, simplified data access, improved data quality, and established governance at scale to power analytics, reporting, AI, and machine learning (ML) use cases. As a result, the data solution offers benefits such as faster access to data, expeditious decision making, accelerated time to value for use cases, and enhanced data governance.

How Volkswagen streamlined access to data across multiple data lakes using Amazon DataZone – Part 1

Bandana Das — Thu, 18 Jul 2024 18:15:23 +0000

This blog post introduces Amazon DataZone and explores how VW used it to build their data mesh to enable streamlined data access across multiple data lakes. It focuses on the key aspect of the solution, which was enabling data providers to automatically publish data assets to Amazon DataZone, which served as the central data mesh for enhanced data discoverability. Additionally, the post provides code to guide you through the implementation.

Software-defined edge architecture for connected vehicles

James Simon — Mon, 03 Apr 2023 13:47:23 +0000

To remain competitive in a marketplace that increasingly views transportation as a service emphasizing customer experience, vehicle capabilities and mobility applications need to improve and increase value over time, much like the internet of things and smart phones have done. Vehicle manufacturers and fleet operators are responding to this change by using data to inform […]

How to secure an enterprise scale ACM Private CA hierarchy for automotive and manufacturing

Anthony Pasquariello — Mon, 13 Jun 2022 15:38:46 +0000

In this post, we show how you can use the AWS Certificate Manager Private Certificate Authority (ACM Private CA) to help follow security best practices when you build a CA hierarchy. This blog post walks through certificate authority (CA) lifecycle management topics, including an architecture overview, centralized security, separation of duties, certificate issuance auditing, and […]

How to Run Massively Scalable ADAS Simulation Workloads on CAEdge

Hendrik Schoeneberg — Thu, 10 Feb 2022 05:27:16 +0000

This post was co-written by Hendrik Schoeneberg, Sr. Global Big Data Architect, The An Binh Nguyen, Product Owner for Cloud Simulation at Continental, Autonomous Mobility – Engineering Platform, Rumeshkrishnan Mohan, Global Big Data Architect, and Junjie Tang, Principal Consultant at AWS Professional Services. AV/ADAS simulations processing large-scale field sensor data such as radar, lidar, and […]

ZABBIX – Open-Source Monitoring Software for Automotive Monitoring

Dmitry Lambert — Mon, 17 Jan 2022 11:02:06 +0000

In this article, I will try to cover the theoretical models on monitoring your vehicle fleet with minimal to…

The post ZABBIX – Open-Source Monitoring Software for Automotive Monitoring appeared first on Zabbix Blog.

Developing a Platform for Software-defined Vehicles with Continental Automotive Edge (CAEdge)

Martin Stamm — Thu, 06 Jan 2022 14:58:46 +0000

This post was co-written by Martin Stamm, Principal Expert SW Architecture at Continental Automotive, Andreas Falkenberg, Senior Consultant at AWS Professional Services, Daniel Krumpholz, Engagement Manager at AWS Professional Services, David Crescence, Sr. Engagement Manager at AWS, and Junjie Tang, Principal Consultant at AWS Professional Services. Automakers are embarking on a digital transformation journey to […]

Ingesting Automotive Sensor Data using DXC RoboticDrive Ingestor on AWS

Bryan Berezdivin — Fri, 17 Dec 2021 17:05:12 +0000

This post was co-written by Pawel Kowalski, a Technical Product Manager for DXC RoboticDrive and Dr. Max Böhm, a software and systems architect and DXC Distinguished Engineer. To build the first fully autonomous vehicle, L5 standard per SAE, auto-manufacturers collected sensor data from test vehicle fleets across the globe in their testing facilities and driving […]

Field Notes: Building a Data Service for Autonomous Driving Systems Development using Amazon EKS

Ajay Vohra — Tue, 30 Nov 2021 20:57:43 +0000

Many aspects of autonomous driving (AD) system development are based on data that capture real-life driving scenarios. Therefore, research and development professionals working on AD systems need to handle an ever-changing array of interesting datasets composed from the real-life driving data. In this blog post, we address a key problem in AD system development, which […]

Field Notes: Deploy and Visualize ROS Bag Data on AWS using rviz and Webviz for Autonomous Driving

Aubrey Oosthuizen — Thu, 26 Aug 2021 13:54:26 +0000

In the automotive industry, ROS bag files are frequently used to capture drive data from test vehicles configured with cameras, LIDAR, GPS, and other input devices. The data for each device is stored as a topic in the ROS bag file. Developers and engineers need to visualize and inspect the contents of ROS bag files to identify […]

Field Notes: Building an automated scene detection pipeline for Autonomous Driving – ADAS Workflow

Kevin Soucy — Fri, 06 Aug 2021 18:40:59 +0000

This Field Notes blog post in 2020 explains how to build an Autonomous Driving Data Lake using this Reference Architecture. Many organizations face the challenge of ingesting, transforming, labeling, and cataloging massive amounts of data to develop automated driving systems. In this re:Invent session, we explored an architecture to solve this problem using Amazon EMR, Amazon […]

Field Notes: Deploying Autonomous Driving and ADAS Workloads at Scale with Amazon Managed Workflows for Apache Airflow

Hendrik Schoeneberg — Wed, 04 Aug 2021 23:05:15 +0000

Cloud Architects developing autonomous driving and ADAS workflows are challenged by loosely distributed process steps along the tool chain in hybrid environments. This is accelerated by the need to create a holistic view of all running pipelines and jobs. Common challenges include: finding and getting access to the data sources specific to your use case, […]

Field Notes: Automating Data Ingestion and Labeling for Autonomous Vehicle Development

Amr Ragab — Mon, 28 Jun 2021 18:35:49 +0000

This post was co-written by Amr Ragab, AWS Sr. Solutions Architect, EC2 Engineering and Anant Nawalgaria, former AWS Professional Services EMEA. One of the most common needs we have heard from customers in Autonomous Vehicle (AV) development, is to launch a hybrid deployment environment at scale. As vehicle fleets are deployed across the globe, they […]

AWS extends its TISAX scope to cover the London and Paris Regions

Clara Lim — Thu, 17 Dec 2020 17:22:15 +0000

We’re excited to announce the completion of Trusted Information Security Assessment Exchange (TISAX) certification on December 08, 2020 for the London and Paris regions. These regions were assessed at the HIGH protection level (AL 2) for the control domains Information Handling and Data Protection, according to article 28 (“Processor”) of the European General Data Protection […]

Amazon Lookout for Vision – New ML Service Simplifies Defect Detection for Manufacturing

Marcia Villalba — Tue, 01 Dec 2020 18:37:55 +0000

Today, I’m excited to announce Amazon Lookout for Vision, a new machine learning (ML) service that helps customers in industrial environments to detect visual defects on production units and equipment in an easy and cost-effective way. Can you spot the circuit board with the defect in these images? Maybe you can if you are familiar […]

Field Notes: Building an Autonomous Driving and ADAS Data Lake on AWS

Junjie Tang — Wed, 14 Oct 2020 15:49:45 +0000

Customers developing self-driving car technology are continuously challenged by the amount of data captured and created during the development lifecycle. This is accelerated by the need to design and launch incremental feature improvements on advanced driver-assistance systems (ADAS). Efforts to advance ADAS functionality have led to new approaches for storing, cataloging, and analyzing driving data […]

Field Notes: Implementing Hardware-in-the-Loop for Autonomous Driving Development on AWS

Bryan Berezdivin — Tue, 13 Oct 2020 14:32:11 +0000

Automotive customers use AWS as their platform for advanced driving assistance systems (ADAS) and autonomous driving (AD) development to accelerate their development cycles and experience faster time-to-market. In the blog post, Autonomous Vehicle and ADAS development on AWS Part 1: Achieving Scale, we illustrated how software in the loop (SiL) and hardware in the loop […]