AWS for Industries

re:Invent wrap up for manufacturing – not only for developers anymore!

Another re:Invent is behind us, and attendees had a busy week of learning at technical sessions, exploring interactive demos, networking with peers, and having some fun at the re:Play celebration. We had great announcements on new services, features, and solutions that will help manufacturing and industrial companies accelerate their digital transformation journey and assist companies to move past pilot-purgatory to scalable, business changing initiatives in the cloud. The event also hosted manufacturing executives and line of business attendees, proving that this event is no longer ‘just’ a developer-focused week.

Key Sessions to Watch

If you didn’t catch the livestreams of keynote sessions, I encourage you to check out the keynote from our CEO Adam Selipsky who shared his perspective on cloud transformation. He highlighted innovations in data, infrastructure, and artificial intelligence and machine learning. These advancements are helping AWS customers achieve their goals faster, mine untapped potential, and create a better future.

Our Manufacturing and Automotive Vice-President, Wendy Bauer, also presented an Innovation Talk following Adam’s keynote. She discussed how industrial companies across verticals like automotive, aerospace, and consumer electronics, are using data and cloud technologies to optimize operations, accelerate time to market, and generate new revenue streams with fresh business approaches. She was joined by Tony Hemmelgarn, President and CEO at Siemens Digital Industries Software, who spoke about how they are using their Xcelerator industrial software portfolio powered by AWS to innovate. Tadafumi Nogawa, GM of Connected Solution Development at Honda Japan and Jay Joseph, VP of Sustainability and Business Development American Honda, joined Wendy to talk about their work on software-defined mobility and electrification at Honda with AWS.

In his breakout session, Accelerating industrial transformation with IoT on AWS Michael MacKenzie, GM of Industrial IoT & Edge for AWS, and Brad Davis, Maintenance Manager at Toyota Motors North America shared real-world examples how customers are using the new capabilities in AWS IoT SiteWise to modernize their infrastructure, build a strong industrial data foundation, and transform their operations.

In this breakout session, Nicolas Pouyez, Head of AWS IoT Industrial Edge, and Torben Poertner, Vice President of Edge Ecosystem at Siemens Factory Automation discuss the new collaboration between AWS and Siemens.

In the Emerging Tech Innovation Talk, Bill Vass, VP of Engineering at AWS, and Rainer Brehm, CEO of Siemens Factory Automation, addressed the challenges in OT, particularly in data accessibility and integration with IT. He also announced that AWS IoT SiteWise Edge is available on Siemens Industrial Edge Marketplace to facilitate seamless OT data flow from the shop floor to the cloud. In this related breakout session, Nicolas Pouyez, Head of AWS IoT Industrial Edge, and Torben Poertner, Vice President of Edge Ecosystem at Siemens Factory Automation, discussed the new collaboration between AWS and Siemens. Check out the session recording for Accelerate shop floor digitization with edge-to-cloud data integration (IOT215) or this blog announcement for more details on the collaboration between AWS and Siemens to help simplify, accelerate, and reduce the cost of sending industrial equipment data to the AWS cloud.

On Monday, Peter DeSantis dove deep into the engineering that powers AWS services. He provided a closer look at how AWS’ unique approach and culture of innovation help create leading-edge solutions across the entire spectrum, from silicon to services—without compromising on performance or cost.

On Wednesday, Dr. Swami Sivasubramanian, Vice President of Data and AI at AWS, explored the powerful relationship between humans, data, and AI, unfolding right before us. Generative AI is augmenting our productivity and creativity in new ways, while also being fueled by massive amounts of enterprise data and human intelligence. Swami discussed how companies can use data to build differentiated generative AI applications and accelerate productivity for employees across organizations. Customer speakers detailed real-world examples of how they’ve used their data to support their generative AI use cases and create new experiences for their customers.

On Thursday, CTO Dr. Werner Vogels highlighted best practices for designing resilient and cost-aware architectures, and he also discussed why artificial intelligence is something every builder must consider when developing systems and the impact this will have in our world.

Check out all the keynotes and innovation session recordings here.

Although manufacturing customers appear in many sessions, the list below captures some of the most popular topics for manufacturers today:

Service, Feature, and Solution Launches

Just before re:invent, and throughout the event week, AWS innovation was a consistent drumbeat. We launched a number of services and enhancements that are applicable to manufacturers and industrial companies. Let’s breakdown why they matter.

In a previous blog, I talked about how Generative AI has the potential to help create new product designs, drive unprecedented levels of manufacturing productivity, and optimize supply chain applications. We launched several generative AI related services and features, but the most notable is Amazon Q (preview). Amazon Q helps you get fast, relevant answers to pressing questions, solve problems, generate content, and take actions using the data and expertise found in your company’s information repositories, code, and enterprise systems. When you chat with Amazon Q, it provides immediate, relevant information and advice to help streamline tasks, speed decision-making, and help spark creativity and innovation at work. For developers and IT professionals Amazon Q transforms the way applications and workloads are built, deployed, and operated on AWS. Amazon Q is an expert on patterns in the AWS Well-Architected Framework, best practices, documentation, and solution implementations, making it easier for manufacturers to explore new services and capabilities, get started faster, learn unfamiliar technologies, architect solutions, troubleshoot, upgrade applications, and more. We also launched AWS Graviton4 and AWS Trainium2 to reduce training time, at lower cost, and with less energy. We also launched Amazon SageMaker HyperPod, purpose-built to accelerate foundation model (FM) training, removing the undifferentiated heavy-lifting involved in managing and optimizing a large training compute cluster. With SageMaker HyperPod, you can train FMs for weeks and months without disruption.

Industrial IoT and Machine Learning Launches

AWS IoT SiteWise is a managed service that makes it easy to collect, store, organize and monitor data from industrial equipment at scale to help you make better, data-driven decisions. We announced the general availability of extended industrial protocol support through a new integration with AWS Partner Domatica. Using Domatica’s EasyEdge software, customers can now ingest data from 10 additional industrial protocols including Modbus (TCP & RTU), Ethernet/IP, Siemens S7, KNX, LoRaWAN, MQTT, Profinet, Profibus BACnet, and Rest interfaces, in addition to native OPC UA support. We also launched additional enhancements aiming to reduce the cost of equipment data ingestion and storage including asset model components, bulk asset import, integration with Lookout for Equipment, buffered ingestion, user-defined unique identifiers, Query API/SQL, and new warm storage tier. We also announced that AWS IoT SiteWise Edge, on-premises software for the factory edge, can now be deployed directly from the Siemens Industrial Edge Marketplace to help simplify, accelerate, and reduce the cost of sending industrial equipment data to the AWS cloud. This blog provides a recap of all features launched in AWS IoT SiteWise to help shorten time to value.

We also launched AWS IoT TwinMaker enhancements which enable customers to model, deploy, and scale their digital twins faster and more efficiently. This includes metadata bulk operations, like import, export, and update, and an increase in AWS IoT TwinMaker service quotas to support digital twins with higher entity and component counts, and finally a new composite component type that provides flexibility and efficiency in building complex component types. Amazon Monitron continues to evolve with new Amazon Monitron Ex-rated sensors, an intrinsically safe offering for hazardous environments.

Supply Chain Launches

Last year at re:Invent, we launched AWS Supply Chain to support this critical area for manufacturers. This year, AWS Supply Chain announced four new capabilities: Supply Planning, N-Tier Visibility, Sustainability, and Amazon Q in AWS Supply Chain (Preview). These new capabilities optimize the upstream part of the supply chain, which includes sourcing and movement of raw materials and components from suppliers and trading partners. Additionally, we launched AWS B2B Data Interchange, which automates the exchange of EDI-based business-critical transactions at scale, with elasticity and pay-as-you-go pricing. B2B Data Interchange reduces the time, complexity, and costs incurred to build and manage EDI with trading partners, letting you focus on using the transacted data to gain insights.

Another service announcement with implications for machine builders is AWS Clean Rooms ML (Preview). It can help machine builders and their end manufacturing customers apply privacy-enhancing ML to generate predictive insights without having to share raw data with each other. The capability’s first model is specialized to help companies create lookalike segments. With AWS Clean Rooms ML lookalike modeling, you can train your own custom model using your data, and invite your partners to bring a small sample of their records to a collaboration to generate an expanded set of similar records while protecting you and your partner’s underlying data.

Storage and High Performance Compute Launches

New for latent sensitive applications, we launched the Amazon S3 Express One Zone storage class, which is purpose-built to deliver the fastest cloud object storage for performance-critical applications that demand consistent single-digit millisecond request latency. S3 Express One Zone can improve data access speeds by 10x and reduce request costs by 50% compared to S3 Standard and scales to process millions of requests per minute for your most frequently accessed datasets.

For remote engineers and remote developers, we also announced that Amazon WorkSpaces Thin Client is now generally available. It improves end-user and IT staff productivity—supporting a wide range of end users with cost-effective, secure, easy-to-manage access to virtual desktops. End users can set up their endpoint device and connect to their virtual desktop in a few minutes using an on-device guided deployment experience, without requiring additional assistance from IT. Just before re:Invent, we also launched Research and Engineering Studio on AWS (RES) which is an open source, easy-to-use web-based portal for administrators to create and manage secure cloud-based research and engineering environments. Using RES, scientists and engineers can visualize data and run interactive applications without the need for cloud expertise.

Lastly, AWS introduced three additional Amazon EC2 instances: P5e instances, powered by NVIDIA H200 Tensor Core GPUs, for large-scale and cutting-edge generative AI and HPC workloads; and G6 and G6e instances, powered by NVIDIA L4 GPUs and NVIDIA L40S GPUs respectively, for a wide set of applications such as AI fine tuning, inference, graphics, and video workloads.


The year’s re:Invent demonstrated how AWS innovation can help accelerate digital transformation and optimize manufacturing businesses. It also marked a shift from a developer-centric conference to an event with offerings for the entire manufacturing value chain. If you didn’t make the event this year, I hope you can make it next year, scheduled for December 2-6, in Las Vegas, NV!

Scot Wlodarczak

Scot Wlodarczak

Scot joined AWS in July 2018, where he now manages the manufacturing industry marketing efforts. Scot worked previously at Cisco, and Rockwell Automation where he held roles as Industrial Marketing Manager and Regional Marketing Leader. Scot has focused on marketing to industrial customers on their digital transformation journey, and bridging the gap between IT and operations. He has experience in automation across a wide range of industries. Scot holds a Mechanical Engineering degree from SUNY - Buffalo, and an MBA from Colorado University. He lives in Colorado.