Category: Amazon Simple Storage Service (S3)

With AWS Ground Station, you can now deliver data directly into Amazon S3 buckets. This simplifies downlinking because you no longer need to run an Amazon EC2 receiver instance. It also saves you cost and simplifies the creation of automated processing pipelines like the one we are going to show in this blog. By using an automated Earth observation (EO) pipeline, you can reduce the operating burden of your staff, as after scheduling a contact, everything is handled automatically and you’ll get a notification when the processed data is available. Read on to learn how to create an automated EO pipeline that receives and processes data from the NOAA-20 (JPSS-1) satellite, using this new AWS Ground Station feature.

Even though Amazon S3 provides regional data resiliency, customers often have compliance and business requirements to replicate their data to a second Region that is hundreds (or even thousands) of miles away from their primary location. Amazon S3 replication provides an automatic mechanism to make identical copies of your objects in a destination Region of your choice. Replication enables automatic, asynchronous copying of objects across S3 buckets. Learn how to configure S3 Cross Region Replication with S3 RTC feature, and do a walk-through of how to configure event notification for S3 replication events and configuring Amazon CloudWatch alarms for the replication metrics.

If you are hosting an ArcGIS web app today, then you are probably hosting it on a Windows or Linux server using traditional web server software like IIS or Apache. With the web hosting capability of Amazon S3 you can remove the need to run these servers and the maintenance, management, and monitoring overhead that comes with it. Serverless services like Amazon S3 can scale automatically and can be as simple as copying over your website assets to get up and running in minutes. This blog focuses on web app implementations using ArcGIS API for JavaScript (as other ArcGIS web apps have additional considerations).

The Intelligence Advanced Research Projects Activity (IARPA) Machine Intelligence from Cortical Networks (MICrONS) program seeks to revolutionize machine learning by better understanding the representations, transformations, and learning rules employed by the brain. We spoke with Dean Kleissas, Research Engineer working on the IARPA MICrONS Project at the Johns Hopkins University Applied Physics Laboratory (JHU/APL), and […]