AWS successfully runs AWS compute and machine learning services on an orbiting satellite in a first-of-its kind space experiment
At re:Invent 2022, AWS announced that it successfully ran a suite of AWS compute and machine learning (ML) software on an orbiting satellite, in a first-of-its-kind space experiment. The experiment, conducted over the past 10 months in low Earth orbit (LEO), was designed to test a faster, more efficient method for customers to collect and analyze valuable space data directly on their orbiting satellites using the cloud.
At AWS, our customers and partners serving government, nonprofit, healthcare, and education are focusing on advancing the way they deliver critical services, improve the customer experience, build resilience into how they operate, and respond to disruptive events. With much progress made to date and with customers expecting the same digital experience and service as in other industries, expectations are only getting higher. So how can public sector organizations approach this new dynamic, and how can AWS support their missions?
Edge computing moves data processing and analysis close to endpoints where data is generated to deliver real-time responsiveness, and reduces cost associated with transferring large amounts of data. Edge environments include Internet of Things (IoT) or mobile devices, sensors, video cameras, and other connected resources. With edge, the usual security principles still apply such as protecting data at rest and in motion, but new considerations emerge. Learn more in the new IDC whitepaper.
In a data-dependent world, success belongs to the side with decision advantage: the ability to acquire data and make sense of a complex and adaptive environment, and act smarter and faster than the competition. Understanding global environments requires more than just more data – it requires live two- and three-dimensional maps, new support tools, improved processes, seamless connectivity, and better collaboration that can scale to the needs of the environment. This blog post explores how to address challenges of big data and accelerate time to data insights with machine learning with AWS Snowball Edge device deployment at the edge.
In a recent disaster response field testing exercise (FTX), the AWS Global Social Impact Solutions (GSI) team developed a prototype cloud architecture and tested it in a search and rescue (SAR) scenario simulating a missing responder crisis. This blog post walks through the SAR simulation and result, and provides an overview of the AWS services and technical architecture components the GSI team used to provide a hybrid edge/cloud COP solution that helped locate the missing team member in the simulated scenario within 20 minutes.
In the immediate aftermath of a natural disaster, cell towers, power lines, and telephone and internet cable are often damaged or destroyed, limiting the ability for responders to share data and access the internet. The AWS Disaster Response team conducted a field testing operation designed to replicate a common disaster response scenario, to show how to establish an ad-hoc network at field sites with limited connectivity and create a link to an office headquarters to provide access to cloud-based resources and data to responders in the field.
AWS is announcing the opening of an office in Athens, furthering our commitment to investing in Greece and responding to the expanding customer base in the country. The office will support organisations of all sizes—startups, enterprises, and public sector agencies—as they make the transition to the cloud. The opening of the office is our latest investment in Greece.