AWS’ re:Invent  - Takeaways for Industry Users

An industry event with 50,000 participants is truly impressive. AWS’ re:Invent, the annual get-together of users of the company’s platforms and tools, is overwhelming by the sheer amount of knowledge and content shared among members of this huge global community. In the fast-moving IT sector, the event was used to launch literally dozens of new products and services, ranging from analytics to databases, data tools to global infrastructure, machine learning to security, and many, many more.

What can AWS do for Industry Users?

What AWS offers to industry users is nothing less than the future of computing in industrial environments. The influence of information technology (IT) on operation technology (OT) is forever changing manufacturing companies as they adopt modern architectures on the enterprise side, and then tie these to both legacy and newly installed manufacturing systems. Most companies have already moved their enterprise solutions to a cloud-hosted model, but the industrial plant has its own special priorities that can’t always be met in this way.

In addition to the many commercial sectors that AWS targets, the company also focuses on manufacturing industries that are of interest to ARC clients. These include automotive, CPG, manufacturing, energy, semiconductor, and power & utilities. AWS employs executives with industrial backgrounds to help it develop solutions that address the particular needs of industry users. While most of AWS’ solutions for manufacturers are focused on the external IT infrastructure, the company has also invested into building out “purpose-built AI/ML and IoT services for asset-intensive industry use cases” over the last few years.

Based on use cases frequently asked for by industrial clients or tapping into Amazon innovation relevant to industrial clients, AWS released in 2020: AWS IoT SiteWise (collect, manage, visualize process data) and Amazon Monitron (equipment monitoring with predictive maintenance and machine learning). Amazon Lookout for Vision (use computer vision to automate quality inspection), Amazon Lookout for Equipment (detect abnormal equipment behavior), and AWS Panorama Appliance (add computer vision at the edge) were added in 2021, and this year AWS IoT RoboRunner (build applications that help robot fleets work together) was added to the list of purpose-built services for industrial settings.

On top of this, AWS offers references (quick-start architectures) that combine several services to create solutions focused on specific manufacturing use cases. The manufacturing and industrial section in the AWS solutions library includes blueprint architectures and links to specialist manufacturing ISVs that have made their products available on AWS infrastructure, for example Siemens Teamcenter. In fact, at re:Invent, Cedrik Neike, CEO Siemens Digital Industries, talked about Siemens’ role in industrial automation and how AWS has helped the company to move industrial software to the cloud to make it accessible for companies of all sizes and unlock industrial data. In his keynote speech, AWS CEO Adam Selipsky, recalled working with Siemens to support Swedish battery-maker Northvolt in support of its “factory in the cloud” strategy, detailed in this ARC View.

The Phenomenal Evolution of AWS

AWS first offered IT infrastructure as a service in the form of web services in 2006, just as the shift to cloud-hosting was gaining traction. Tools for compute, storage and database originally had been developed for internal use to help Amazon.com scale up its fast-growing e-commerce business. AWS recognized the potential to sell these services on the open market to help other companies develop and deploy their web-based businesses using standard tools. By In 2022, the company’s revenue will likely exceed $70 billion.

According to AWS, much of its knowledge and experience in industry arises from internal developments. As a major logistics user, parent company Amazon has developed many solutions internally – not only the IT infrastructure, but also innovations in packaging and shipping. For example, customers can easily set up a unified supply chain data lake using AWS Supply Chain’s built-in connectors, which use pre-trained machine learning models based on Amazon.com's 30 years of supply chain experience, to understand, extract, and aggregate data from ERP and supply chain management systems. AWS Supply Chain then contextualizes that information in a real-time visual map highlighting current inventory selection and quantity at each location.