[Webinar] Protect Your Most Trusted Mainframe Data Across the World in an Age of Heightened Cyber-security
Model9 and Amazon Web Services (AWS)
Create a unified data repository for your mainframe and open systems data on Amazon S3. Protect your mainframe data from cyber threats.
Protect your mainframe data from cyber attacks such as ransomware, by using immutable AWS storage to create multiple copies of the data and ensure all copies are protected. In addition, the data is compressed and encrypted end-to-end. When sent to Amazon S3, the data can also be air-gapped — which means an additional copy is isolated from the network and is not exposed to malicious attacks. Model9 will also enable you to recover your mainframe data directly from the AWS immutable copy into a clean room.
Model9 runs a simple, lightweight software agent on your mainframe environment that can send encrypted, compressed disk and tape data to Amazon S3. Once in Amazon S3, the data can be transformed, on the cloud, into open formats for use with any downstream application including Amazon Reshift, Amazon Athena, Amazon QuickSight and other AWS services.
Managing your mainframe data on Amazon S3 unifies it with your open systems data and gives you one, unified data repository.
Model9 lets you manage your data on Amazon S3, Amazon S3 Glacier Flexible Retrieval, and Amazon Glacier Deep Archive. It provides tools for automatic discovery of all your mainframe data assets, support for efficient delivery of data sets to the AWS Cloud, and makes data assets accessible from your cloud applications.
Model9 eliminates legacy VTL, delivering reduced cost and improved performance by replacing it with affordable Amazon S3 for cloud backups and disaster recovery. You can also migrate all historical tape data to Amazon S3 and replace your legacy system entirely.
Model9 Cloud Data Manager for Mainframe on AWS includes automated discovery to map and list all SGs, volumes, and datasets available for migration, automatically connects to the mainframe, delivers the defined data to the target, and can then transform it to open formats. This is substantially faster and less risky than getting mainframe workloads and applications to the cloud, making it an accelerated path to AWS Cloud adoption.