blog_posts: fd6b48971c
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id | createdDate | title | link | postExcerpt | featuredImageUrl | hash | contributors | modifiedDate | displayDate |
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blog-posts#18-13302 | 2021-11-10 19:20:04 | Analyze terabyte-scale geospatial datasets with Dask and Jupyter on AWS | https://aws.amazon.com/blogs/publicsector/analyze-terabyte-scale-geospatial-datasets-with-dask-and-jupyter-on-aws/ | Terabytes of Earth Observation (EO) data are collected each day, quickly leading to petabyte-scale datasets. By bringing these datasets to the cloud, users can use the compute and analytics resources of the cloud to reliably scale with growing needs. In this post, we show you how to set up a Pangeo solution with Kubernetes, Dask, and Jupyter notebooks step-by-step on Amazon Web Services (AWS), to automatically scale cloud compute resources and parallelize workloads across multiple Dask worker nodes. | https://d2908q01vomqb2.cloudfront.net/9e6a55b6b4563e652a23be9d623ca5055c356940/2021/11/10/Analyze-terabyte-scale-geospatial-datasets-dask-jupyter-AWS-featured-image-1200x600-1-300x150.png | fd6b48971c | Ethan Fahy, Zac Flamig | 2021-11-16 03:07:16 | 10 Nov 2021 |
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