Note: This course expects student to have pre-requisite knowledge of few technologies including GDAL/OGR, Cloud Computing (AWS) &Docker. It is not expected for the student to be an expert in these technologies and some material will be covered however do note this course does not provide detailed coverage of topics such as Docker containers, Cloud Computing or even GDAL. If the student finds these topics to be new, it is recommended to first learn about these technologies before attempting to go through this course.
In this course, we will learn, how we can utilize cloud technologies (AWS Serverless)to deliver optimized Raster datasets to end client applications. This approach is becoming very popular and does not require a full 24/7 running Geospatial Server such as MapServer, GeoServer or ArcGIS Server. We will make use of the popular Geospatial library called GDAL within our Serverless architecture, which will enable the core Geospatial capability within our service. GDAL is a very popular geospatial library that has been utilized in many open source and commercial applications and architectures. In this course we will see how GDAL can be utilized within a Lambda function to convert it into GeoLambda function which essentially enabled Geospatial capabilities within the Lambda function. Once GDAL functionality is available, various operations and functions can be performed on data within a Lambda function.
We will look at approaches on how to work with sample geospatial raster dataset, how to optimize it for efficient serving through out Serverless service (pre-processing), how to build and develop our Geospatial Restful API (AWS) and finally how to request the raster dataset from front end Geospatial Libraries.
This course is ideal for GIS Professionals who have been using Geospatial Technologies including ESRI or Open source and want to explore the new way of utilizing and server Geospatial Raster Dataset.
Do note, this approach has been adopted in various architectures and is found to be more efficient (in some use cases) as compared to Geospatial Servers however this does not mean that Serverless approach taught in this course is a complete replacement for Geospatial Servers like GeoServer, MapServer or ArcGIS Server. Use of Server based or Serverless approach for Geospatial greatly depends on the project requirements and several other factors.
It is hoped that this advance course will provide you with a glimpse into the world of serverless and how to utilize it for developing a Raster based Geospatial System/Service.
