End-To-End Data Science in Python on the AWS Marketplace
Enables scalable Python for faster data science and machine learning workloads within your AWS environment
What is the AWS Marketplace?
AWS Marketplace is a curated digital catalog customers can use to find, buy, deploy, and manage third-party software, data, and services that customers need to build solutions and run their businesses. AWS Marketplace includes thousands of software listings from popular categories such as security, networking, storage, machine learning, business intelligence, database, and DevOps. AWS Marketplace also simplifies software licensing and procurement with flexible pricing options and multiple deployment methods. In addition, AWS Marketplace includes data products available from AWS Data Exchange. Customers can quickly launch pre configured software with just a few clicks, and choose software solutions in Amazon Machine Images (AMIs), software as a service (SaaS), and other formats. Source: Amazon
Integrate
Saturn connects to existing storage services, real time data sources, and management tools. While Saturn is compatible with the full AWS ecosystem, you maintain full control around user access to the various data sources within your environment.
Develop
Saturn automates the DevOps and ML infrastructure engineering required to scale the full Python ecosystem. Develop Data Science and Machine Learning models in custom Jupyter environments that can leverage both CPU and GPU hardware.
Scale
With Saturn you can run models on a cluster with Dask and Kubernetes to auto-scale resources, and schedule tasks that launch asynchronously and can run in parallel with Prefect. You can deploy models as REST APIs on Saturn or as part of a separate application.
Secure and Scalable Infrastructure
Saturn Cloud runs as an application inside Kubernetes, leveraging AWS services such as EC2, AWS Identity and Access Management (IAM), and Amazon Virtual Private Cloud (VPC) to provide secure and scalable infrastructure for running Data Science and Machine Learning workloads within your AWS environment.
Customize and Share Docker Images
Saturn users can customize and share docker images by providing environment.yml, requirements.txt, or a bash script without knowing docker. Once something is working, Saturn turns it into a Kubernetes production deployment. These can be dashboards, machine learning models, or scheduled workflows with Prefect. All of this runs with the same environment, eliminating the “well it works on my computer” problem.
Setting Up Your Data Science & Machine Learning Capability in Python
Python is the clear winning programming language in data science & machine learning (DSML). With its rich and dynamic open source software ecosystem, Python stands unmatched in how adoptable, reliable, and functional it is.
Read morePractical Issues Setting up Kubernetes for Data Science on AWS
Kubernetes provides a ton of useful primitives in setting up your own infrastructure. However, the standard way of provisioning Kubernetes isn’t set up very well for data science workflows. This article describes those problems, and how we think of them.
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