With a network of 12 antenna ground stations in AWS Regions around the world customers can download, process, store, analyze, and act upon satellite data quicker with substantial cost savings

Initial customers DigitalGlobe, BlackSky, Spire, Capella Space, Open Cosmos, and HawkEye 360 to access antennas on demand; preview starting today

SEATTLE — (BUSINESS WIRE) — November 27, 2018 — Today at AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), announced AWS Ground Station, a new service that makes it easy and cost-effective for customers to download data from satellites into AWS Global Infrastructure Regions using a fully managed network of 12 ground station antennas located around the world. Once customers receive satellite data at a ground station, they can immediately process it in an Amazon Elastic Compute Cloud (Amazon EC2) instance, store it in Amazon Simple Storage Service (S3), apply AWS analytics and machine learning services to gain insights, and use Amazon’s network to move the data to other regions and processing facilities. Getting started with AWS Ground Station takes just a few clicks in the AWS Management Console to schedule antenna access time and launch an Amazon EC2 instance to communicate with the satellite. There are no up-front payments or long-term commitments, no ground infrastructure to build or manage, and customers pay-by-the-minute for antenna access time used. To get started with AWS Ground Station, visit https://aws.amazon.com/ground-station.

Satellites are being used by more and more businesses, universities, and governments for a variety of applications, including weather forecasting, surface imaging, and communications. To do this today, customers must build or lease ground antennas to communicate with the satellites. This is a significant undertaking and cost because customers often require antennas in multiple countries to download data when and where they need it without waiting for the satellite to pass over a desired location. And the antennas are just the beginning of the infrastructure requirements because customers need servers, storage, and networking in close proximity to the antenna to process, store, and transport the data from the satellite. And then customers must build business rules and workflows to organize, structure, and route the data to employees or customers before it can be used to deliver insight. All of this requires significant capital investments and operational costs to build, manage, and maintain antennas, compute infrastructure, and business logic at each antenna location.

AWS Ground Station allows customers to more easily and cost-effectively control satellite operations, ingest satellite data, and integrate the data with applications and other cloud services running in AWS. Using AWS Ground Station, customers can save up to 80 percent of their ground station costs by paying for antenna access time on demand, and they can rely on AWS Ground Station’s global footprint of ground stations to downlink data when and where they need it. The recency of data is particularly critical when it comes to tracking and acting upon fast-moving conditions on the ground. This timeliness depends on frequent communications between ground stations and satellites, which can only be achieved with a large, global footprint of antennas maintaining frequent contact with orbiting satellites. For example, as fast-moving environmental, geopolitical, or news events unfold on the ground, AWS Ground Station customers can downlink current data to any of the 12 AWS ground stations around the world and quickly combine the data with other AWS services to process, store, analyze, and transport the data to keep up with rapidly evolving conditions. With AWS and AWS Ground Station, customers can get timely data sooner, rapidly experiment with new applications, and deliver products to market faster without buying, leasing, or maintaining complex and expensive infrastructure.

“Satellite data is incredibly useful for building a wide range of important applications, but it is super complex and expensive to build and operate the infrastructure needed to do so. A few years back our customers asked us if we could remove that cost and complexity, and the more we thought about it, the more we realized that AWS with its global footprint was uniquely positioned to solve this challenge,” said Charlie Bell, Senior Vice President of AWS. “Today, we are giving satellite customers the ability to dynamically scale their ground station antenna use based on actual need. And, they will be able to ingest data straight into AWS, where they can securely store, analyze, and transmit products to their customers without needing to worry about building all of the infrastructure themselves.”

AWS Ground Station’s self-service graphical interface makes it easy to identify antenna locations and communications windows, and schedule antenna time. This enables customers to review confirmed times in the console and cancel or reschedule prior to the scheduled contact time. Because many AWS Ground Station antennas are co-located with AWS Regions, customers have low-latency, local access to other AWS services to process and store this data. For example, they can use Amazon EC2 to control satellites and downlink data, store and share the data in Amazon Elastic Block Store (Amazon EBS), Amazon Elastic File System (Amazon EFS), or Amazon S3, use Amazon Virtual Private Cloud (Amazon VPC) for secure communications between Amazon EC2 instances and the AWS Ground Station antenna gateway, hunt for real-time business insights with Amazon Kinesis Data Streams and Amazon Elastic Map Reduce, apply machine learning algorithms and models with Amazon SageMaker, add image analysis with Amazon Rekognition, and improve data sets by combining satellite data with IoT sensor data from AWS IoT Greengrass. AWS customers can combine these capabilities to build exciting applications that might use image recognition to identify and protect endangered animals, machine learning to predict faulty construction or industrial systems, or analytics to estimate oil production or assess agriculture yields in real time.