A Primer on Kubernetes and Google Container Engine

Moving an established, well-understood file-sharing or home directory environment for your Windows or Linux users into the cloud can cause some sleepless nights. In this on-demand webinar, you'll hear about some ideas to get that sleep back, including how to help users recover from their own mistakes (user error) and how to quickly recover after suffering an attack.With NetApp® Cloud Volumes, users can benefit from Snapshot™ technology, which allows users to recover individual files as well as enables IT staff to recover entire environments, all in a matter of seconds.

Join our webinar on Wednesday, June 26, to see how Cloud Volumes ONTAP can help Google Cloud users cut down storage consumption and costs, protect their data, and recover from potential outages and failures without impacting their businesses.With Cloud Volumes ONTAP, Google Cloud users get:Instant, space-efficient snapshots.SnapMirror® replication for DR and backup.Data deduplication, compression, and thin provisioning storage efficiencies.Automatic tiering between Google Persistent Disk and Google Cloud Storage.Zero-capacity data clone creation.Programmatic control over storage via API calls

Planning for a successful move to Cloud can present many challenges without proper preparation and effective strategy in place. Knowing the best practices ahead of time help streamline the migration process with minimal disruption and valuable results. In this video, you will learn efficient preparing techniques and the importance of assessing capabilities, processes, and governance before migrating.

As the volume, variety, and velocity of data increases, the cloud is the most efficient and cost-effective option for machine learning and advanced analytics. Organizations looking to scale their big data projects can do so with greater ease with a cloud-native data platform. Qubole provides a single platform for data engineers, analysts, and scientists that supports multiple use cases -- from machine learning to predictive analytics. The platform saves organizations up to 50 percent in data processing costs by leveraging multiple engines like Apache Spark, Presto, and Hive, and automatically provisions, manages, and optimizes cloud resources.