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Workshop 5 & 5A Description Updated!
AWS is working with a group of Wisconsin counties to help them store imagery and LiDAR on Amazon Simple Storage Service (S3). S3 is our object store used by many public and private sector customers around the world. By moving GIS to the Cloud, counties can reduce GIS IT costs but more importantly allow GIS experts to focus on supporting smart communities, rather than the details of technical infrastructure. In addition, storing data on S3, which has a REST interface, with many available open and vendor supplied clients in the market, is simple way to support open data mission.
This workshop is an introduction to what you need to know to both store data on Amazon S3 and use that data in-situ for systems such as OGC WMS or WMTS.
Simple architectures are core to scalable systems. Every day on our mobile devices we interact with mapping systems that rely on a simple concept popularized by Google Maps back in 2005, cached map tiles, or “slippy-maps”. On ESRI’s website there is an article titled “Tiles on a Cloud” dated 2009. In 2008, James Fee, on his Spatially Adjusted site, had a post called “ArcGIS Map Server Cache in Amazon S3”. The idea of using Simple Storage Service (S3), rather than a server to deliver map tiles, is a popular and simple way to increase performance and uptime while reducing costs.
However, most of the available documentation speaks to the batch creation of tiles or methods that rely on extensions to cache map tiles at the server level. This workshop will step through the process of creating a real-time map tiling application that relies on S3 and CloudFront for caching, while demonstrating best practice for open data in the Cloud. I will spend some time demonstrating a few of the lesser known features of S3, including the requester pays feature and S3 event notification that relate to open data strategy. Having covered the basics on S3, I will use a simple map tiling architecture that uses CloudFront (CDN), S3, Elastic Beanstalk (Compute service), and Mapserver/GDAL (open source) running on an auto-scaling group of EC2 instances(VMs), to show how to build a system that leverages the Cloud, but uses familiar items such as shapefiles and geotiff imagery data.
Participants will need notebooks/wifi and have an AWS account to build out their own version of system. This will be 200 level AWS content. I will supply data. You are also welcome to come and just watch to see what is possible. Either way I am looking forward to answering your many questions.