AWS for Industries

AWS for Industrial – Making it easy for customers to scale their industrial workloads on AWS

Increasingly, industrial customers across asset intensive industries such as manufacturing, energy, mining, transportation, and agriculture are leveraging new digital technologies to drive faster and more informed decisions in their industrial operations. ‘AWS for Industrial’ is a new initiative that features new and existing services and solutions from AWS and our Partners, which are built specifically for developers, engineers and operators at industrial companies. This initiative simplifies the process for customers to build or deploy innovative Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), analytics and edge solutions to achieve step change improvements in operational efficiency, quality, and agility.

Using data to drive digital transformation

To kickstart their digital transformation journey, industrial customers are looking to extract insights from their data and deliver business outcomes across the following workloads: engineering and design, production and asset optimization, quality management, worker safety and productivity, supply chain management, and smart products and machines. Industrial customers adjust the primary levers available to optimize their business operations – they can grow revenue, and they can lower costs. Growing revenue is often achieved with a faster time to market, optimized marketing strategies, or creating new revenue streams through smart product capabilities. Lowering costs can take the form of cost reduction in infrastructure, reducing operating expenses, and reducing production costs by improving productivity, machine availability or product quality.

Achieving these business outcomes is now possible with cloud tools and technologies such as data lakes, IoT, AI and ML. However, industrial customers have different preferences for how they want to solve for their use cases. Some customers have the in-house skills to build their own solutions using building block services and are looking for accelerators to simplify their deployment, others want to work with industry experienced professional services teams or consulting partners to help them build a custom solution, and others simply want to buy, deploy and configure a ready-made solution. ‘AWS for Industrial’ makes it easy for industrial customers to implement solutions faster using AWS no matter their preference.

Leading industrial companies, such as Volkswagen, Georgia Pacific, Invista, Carrier, and Vector, use AWS to fuel their digital transformation. Data is the connective tissue for industrial processes, and industrial customers have massive datasets that they want to leverage to drive more informed decisions to optimize their operations. While nearly any industrial process can be digitized and improved with AI/ML, the journey is often difficult for customers to navigate. These challenges include 1/ integrating data from new and legacy equipment that use different protocols and formats, 2/ organizing large amounts structured, unstructured, and disparate machine data, 3/ managing assets, device fleets and data across multiple sites, 4/ operating at the edge with minimal tolerance for latency, and 5/ the struggle to find highly skilled data scientists and AI/ML-trained developers that can build intelligent applications. This makes it tough for many companies who are early in their digital transformation journey or lack the skills to do this well. Many processes are built and documented so that the systems and workflows cannot change without a heavy investment of time and resources. This means that change in industrial processes can be slow to implement, and the impact of improvement can often take a long time to evaluate. For these reasons, industrial customers are increasingly looking for faster, simpler ways to capture and manage data from their processes, and apply ML without lengthy development times or needing specialized ML expertise.

New purpose-built AI and ML services make it easier to improve industrial operations with speed and accuracy using data

To address industrial use cases that require near real time decision making, AWS provides five new purpose-built services bringing AI and ML to industrial environments, born out of complex automation and factory operations of Amazon. These new services enable customers to use machine data to predict when equipment will require maintenance and to use computer vision (like images from existing camera feeds) to improve processes, identify bottle necks and detect anomalies, real-time – with no machine learning expertise required.

Using machine data to predict when equipment will require maintenance:

  • Amazon Lookout for Equipment. AWS Lookout for Equipment is an anomaly detection service for industrial machinery. It uses data from equipment tags and sensors, and historical maintenance events to detect abnormal equipment behavior.
  • Amazon Monitron. Amazon Monitron is an end-to-end system that detects abnormal behavior in industrial machinery, such as motors, gearboxes, fans, and pumps, enabling customers to implement predictive maintenance and reduce unplanned downtime. It includes sensors to measure vibration and temperature, a gateway device, and a mobile app to set up devices and track and review potential failures in equipment.

Using computer vision to improve processes, identify bottle necks and detect anomalies:

  • Amazon Lookout for Vision. Amazon Lookout for Vision enables customers to spot industrial product defects and anomalies using computer vision, accurately and at scale. Customers can automate real-time visual inspection for processes like quality control and defect assessment by analyzing images from cameras that monitor the process line. Amazon Lookout for Vision identifies missing components, damage to products, irregularities in production lines, and even minuscule defects in silicon wafers such as a missing capacitor on a printed circuit board.
  • AWS Panorama. AWS Panorama is a machine learning appliance and SDK, which enable customers to add computer vision (CV) to existing on-premises cameras or to new Panorama enabled cameras. It gives customers the ability to make real-time decisions to improve operations, automate monitoring of visual inspection tasks, find bottlenecks in industrial processes, and assess worker safety within facilities.
    • The AWS Panorama Appliance turns existing onsite cameras into powerful edge devices with the processing power to analyze video feeds from multiple cameras in parallel, and generate highly accurate predictions within milliseconds. With a dust resistant and waterproof appliance, customers can install devices in different environments without compromising functionality.
    • The AWS Panorama SDK enables hardware partners to build new Panorama enabled devices that run more meaningful CV models at the edge, and offer a selection of edge devices to satisfy different use cases. New Panorama enabled devices, coming soon from partners including ADLINK Technology, Axis Communications, Basler AG, Lenovo, STANLEY Security, and Vivotek.

IoT and storage advancements make it easy to securely collect, integrate, organize, and store massive industrial data sets even with limited connectivity

Industrial companies today have more operational data than ever before, however, securely accessing, collecting, and organizing these massive industrial data sets is difficult, and often requires new tools to improve systems and processes in industrial low-latency environments. Customers use AWS compute, storage, and database services to build their single source of data truth, and use AWS IoT services to securely collect, organize, and monitor industrial data at scale.

  • AWS IoT SiteWise. 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 customers make better, data-driven decisions in optimizing their operations.
  • AWS Snowcone. AWS Snowcone is the smallest member of the AWS Snow Family of edge computing, edge storage, and data transfer devices. It is ruggedized, secure, and purpose-built for use outside of a traditional data center, and Its small form factor makes it a perfect fit for tight spaces or where portability is a necessity. Customers can execute compute applications at the edge, and can ship the device with data to AWS for offline data transfer, or can transfer data online with AWS DataSync from edge locations.
  • AWS Snowball Edge. AWS Snowball Edge, a part of the AWS Snow Family, is an edge computing, data migration, and edge storage device that customers use for data collection, machine learning and processing, and storage in environments with intermittent connectivity or in extremely remote locations before shipping them back to AWS.
  • AWS Outposts. AWS Outposts is a fully managed service that offers the same AWS infrastructure, AWS services, APIs, and tools to virtually any datacenter, co-location space, or on-premises facility for a truly consistent hybrid experience. AWS Outposts is ideal for workloads that require low latency access to on-premises systems, local data processing, data residency, and migration of applications with local system interdependencies.
  • Amazon Lake Formation. Setting up and managing data lakes involves manual and time-consuming tasks such as loading, transforming, securing, and auditing access to data. AWS Lake Formation automates many of those manual steps and reduces the time required to build a successful data lake using Amazon S3, from months to days.

AWS solutions for the broadest set of industrial workloads

To accelerate time to value from these services, ‘AWS for Industrial’ provides customers with solutions that package IoT, AI, ML, analytics, compute, storage, and edge services, designed to achieve business outcomes across the common industrial workloads that include engineering and design, production and asset optimization, quality management, worker safety and productivity, supply chain management, and smart products and machines.

AWS solutions help customers build and deploy faster by packaging recommended AWS services into vetted reference architectures designed to be operationally effective, reliable, secure, and cost efficient. These solutions can include source code, deployment guides, and easy one-click deployments with AWS CloudFormation templates, and offerings from hardware, ISV, and systems integrator partners.

  • Connected Factory. Connected Factory with AWS IoT is a purpose-built offering from AWS and Partners to unlock data from manufacturing equipment, PLCs and Historians to optimize operations, increase productivity, and improve availability.
  • Amazon Virtual Andon. Amazon Virtual Andon provides a framework to automatically notify managerial, maintenance, and other workers of a quality or factory line processing problem so personnel can quickly take action.
  • Machine to Cloud Connectivity. The Machine to Cloud Connectivity Framework provides secure factory equipment connectivity to the AWS Cloud. The solution features fast and robust data ingestion; highly reliable and durable storage of equipment data; and serverless event-driven applications that help manage the factory configuration.
  • Smart Product. The Smart Product solution provides secure product connectivity to the AWS Cloud, and includes capabilities for local computing within products, sophisticated event rules, and data processing and storage.

AWS Partner solutions from industry leading partners to accelerate time to results

For customers looking to buy and deploy solutions for even faster results, ‘AWS for Industrial’ also comprises a diverse slate of partner solutions from the deepest bench of industrial partners, including Siemens and Hitachi Vantara. AWS Partner solutions are SaaS products or Systems Integrator solutions built on AWS, that let customers address specific industry use cases with ready-made solutions such as the following snapshot of available partner solutions.

  • Siemens MindSphere. MindSphere on AWS is an industrial IoT-as-a-service solution, based on more than 40 AWS services and makes leveraging services in connected systems easier and more economical. Siemens MindSphere helps customers realize complete IoT solutions, such as a fully connected ‘closed loop’ digital twin. To learn more, visit:
  • Hitachi Vantara Lumada Industrial Solutions. Lumada is Hitachi’s advanced digital solutions, services, and technologies for turning data into insights to drive digital innovation. To learn more, visit:
  • Deloitte Smart Factory Fabric. A pre-configured suite of cloud-based IoT applications for the smart factory delivers operational insights to improve performance and reduce costs by increasing visibility, improving production, improving quality, and reducing unplanned downtime. To learn more, visit:
  • Autodesk Forge. A cloud developer platform for building custom software applications, workflows, and integrations across industries such as manufacturing, architecture, engineering, and construction. To learn more, visit:

To see many more industrial partner solutions, visit


With ‘AWS for Industrial’, industrial customers now have one place they can go to for their industrial edge and cloud needs, whether it is to start building their own custom industrial applications using purpose-built AWS services or whether they want to jumpstart their time to value with AWS solutions and partner solutions. To get started, visit


Douglas Bellin

Douglas Bellin

Douglas is the Global Lead of Business Development for Smart Factories and Industrie 4.0 at Amazon Web. He leads the strategy and execution of manufacturing and supply chain solution areas across Industrial customers at the intersection between Operational Technologies and Information Technologies. Prior to AWS, he ran the Marketing, Go-to-Market and Business Development teams for the Industrial Markets within Cisco Systems. He has a background in both the RFID and Analytics markets and was instrumental in running a Business Intelligence software company by bringing it to the Asia market. Douglas started his career in the steel and food manufacturing industry. After 12 years in Asia Pacific he is now based in Seattle, WA