Aero Platform

Introducing Aero, a platform designed to help you deploy, manage and scale workflows for #DataScience, #MachineLearning and beyond.

[Aero Platform @AeroPlatform]

At Aero, we know that building software is hard! We also know that building software that is scalable, maintainable, and reliable is even harder. That's why, with #AeroPlatform, we've set out to change that.

[Aero Platform @AeroPlatform]

It's often difficult to process large amounts of #data, requiring lots of setup and optimisations. This isn't the case with the #aeroplatform. Follow along as we show you how to process large datasets by harnessing the power of the #cloud

https://t.co/Baci2QlhN0

[Aero Platform @AeroPlatform]

Part 2 in our series showcasing the features of #AeroPlatform outlines how easy it is to seamlessly flip our workflows to the #Cloud, provisioning the resources you need to execute workflows at lightning speed. Continue reading here:

https://t.co/Baci2QlhN0

[Aero Platform @AeroPlatform]

#AeroPlatform uses the open-source standards of #Metaflow to define workflows. These workflows can then be scaled from single machines to hundreds of nodes - all without managing any infrastructure. Find out how with our first introduction to Aero here:

https://t.co/DclHzkDrxn

[Aero Platform @AeroPlatform]

#AeroPlatform is released! And to celebrate, we've launched a new series of blogs outlining many of the use cases of the platform, starting with building an #ETL system for news data from #GDELT. Follow along for free now or find out more here:

https://t.co/DclHzkDrxn

[Aero Platform @AeroPlatform]

#MachineLearning engineers are increasingly being asked to fulfil multiple responsibilities, building infrastructure and managing systems. This increases time to value for businesses and leaves #Developers frustrated. #AeroPlatform offers an alternative https://t.co/4EnvFzSEiB

[Aero Platform @AeroPlatform]

One of the biggest issues facing #MLOps is the difficulty in pushing to production. This means that many #MachineLearning workflows never deliver their full value. #AeroPlatform eliminates the prototype/production divide to streamline deployment https://t.co/4EnvFzSEiB

[Mark Saroufim @marksaroufim]

This is what happens when not wanting to learn Kubernetes becomes your identity

But seriously I think we may have built one of the easiest to use 100% open source cloud launchers for distributed ML training

[Aero Platform @AeroPlatform]

Modern-day #DataScience problems focus on large and complex datasets. This means #Developers spend time scaling workflows. #AeroPlatform removes this burden, allowing anyone to use resources at will, reducing overhead and increasing productivity https://t.co/4EnvFzSEiB

[Aero Platform @AeroPlatform]

The ultimate goal of #AeroPlatform is to solve some of the biggest problems facing Developers working in #DataScience, #MachineLearning and beyond. https://t.co/4EnvFzSEiB

[Aero Platform @AeroPlatform]

We think #AeroPlatform is the solution to these problems. It's built to take responsibility for infrastructure, security, and orchestration away from Developers, allowing them to seamlessly switch between development and production as they focus on adding tangible value

[Aero Platform @AeroPlatform]

At Aero, we know that building software is hard! We also know that building software that is scalable, maintainable, and reliable is even harder. That's why, with #AeroPlatform, we've set out to change that.

[Aero Platform @AeroPlatform]

Also, if a workflow takes a long time to deploy each time you want to test it, catching those small bugs is going to take a lot longer. It's essential that Developers have an environment that can be quickly spun up locally to test, then mimicked in production down the line.