AWS Architecture Blog

Category: Amazon Managed Workflows for Apache Airflow (Amazon MWAA)

Reusable ETL framework architecture

Use a reusable ETL framework in your AWS lake house architecture

Data lakes and lake house architectures have become an integral part of a data platform for any organization. However, you may face multiple challenges while developing a lake house platform and integrating with various source systems. In this blog, we will address these challenges and show how our framework can help mitigate these issues. Lake […]

Figure 1. Architecture diagram for autonomous driving simulation

How to Run Massively Scalable ADAS Simulation Workloads on CAEdge

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 […]

Figure 1 - Architecture showing the DXC RoboticDrive Ingestor (RDI) solution

Ingesting Automotive Sensor Data using DXC RoboticDrive Ingestor on AWS

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 […]

Figure 1. Architecture for batch inference at scale with Amazon SageMaker

Batch Inference at Scale with Amazon SageMaker

Running machine learning (ML) inference on large datasets is a challenge faced by many companies. There are several approaches and architecture patterns to help you tackle this problem. But no single solution may deliver the desired results for efficiency and cost effectiveness. In this blog post, we will outline a few factors that can help […]

Deploying Autonomous Driving & ADAS workloads at scale

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

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, […]