New Google Cloud Feature Simplifies Data Science Deployments
Google Cloud this week announced a new feature that can make it significantly easier for system administrators and data scientists to set up and maintain their specialized data infrastructure environments in the cloud.
Called “machine images”, the new feature essentially stores all the information needed to restore a virtual machine. While this can already be done by an older feature known as “custom images”, machine images can span multiple disks and contains instance properties of individual machines, instance metadata, and the relevant permissions.
Without the need to manually adjust each cloud instance, spinning up new cloud systems for data science tasks much faster – and less error prone.
The new machine images make it easy to create new instances at the heart of your scalability, backup and disaster recovery strategy, says Ari Liberman, a product manager for Google Compute Engine. It also uses the same differential disk backup technology that powers incremental snapshots for reliable and cost-effective instance backups.
Liberman explained the new feature by using a web application as an example: “Imagine that you’ve created and configured an instance as part of your web application, and you want to use it as the basis of other instances. With machine images, you can capture your web application exactly as you want it and save it as a golden machine image.”
“You can then use that machine image to launch as many instances as you need, configured in the exact same way as your source instance. You can also share the machine image with other projects.”
Moreover, the properties of new virtual machines can also be individually tweaked if desired, by using machine images’ override functionality.
Machine images are currently in beta and can be accessed from the console for Google Cloud, gcloud or via API.