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Keep Cloud Costs Low with Storage Tiering in AWS

Gil Peleg

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Mar 11, 2021

One of the great revelations for those considering new or expanded cloud adoption is the cost factor – especially with regard to storage. The received wisdom has long been that nothing beats the low cost of tape for long-term and mass storage.

In fact, though tape is still cheap, cloud options are getting very close such as with Amazon S3 Glacier Deep Archive, and offer tremendous advantages that tape can’t match. A case in point is Amazon S3 Intelligent-Tiering. 

Tiering (also called hierarchical storage management or HSM) is not new. It’s been part of the mainframe world for a long time, but with limits imposed by the nature of the storage devices involved and the software. According to Amazon, Intelligent Tiering helps to reduce storage costs by up to 95 percent and now supports automatic data archiving. It’s a great way to modernize your mainframe environment by simply moving data to the cloud, even if you are not planning to migrate your mainframe to AWS entirely.

How does Intelligent-Tiering work? The idea is pretty simple. When objects are found to have been rarely accessed over long periods of time, they are automatically targeted for movement to less expensive storage tiers.

Migrate Mainframe to AWS

In the past (both in mainframes and in the cloud) you had to define a specific policy stating what needed to be moved to which tier and when, for example after 30 days or 60 days. The point with the new AWS tiering is that it automatically identifies what needs to be moved, when, and then moves it at the proper time. To migrate mainframe to Amazon S3 is no problem because modern data movement technology now allows you to move both historical and active data directly from tape or virtual tape to Amazon S3. Once there, auto-tiering can transparently move cold and long-term data to less expensive tiers.

This saves the trouble of needing to specifically define the rules. By abstracting the cost issue, AWS simplifies tiering and optimizes the cost without impacting the applications that read and write the data. Those applications can continue to operate under their usual protocols while AWS takes care of selecting the optimal storage tier. According to AWS, this is the first and, at the moment, the only cloud storage that delivers this capability automatically.

When reading from tape, the traditional lower tier for mainframe environments, recall times are the concern as the system has to deal with tape mount and search protocols. In contrast, Amazon S3 Intelligent-Tiering can provide a low millisecond latency as well as high throughput whether you are calling for data in the Frequent or Infrequent access tiers. In fact, Intelligent-Tiering can also automatically migrate the most infrequently used data to Glacier, the durable and extremely low-cost S3 storage class for data archiving and long-term backup. And with new technology allowing efficient and secure data movement over TCP/IP, getting mainframe data to S3 is even easier.

The potential impact on mainframe data practices

For mainframe-based organizations this high-fidelity tiering option could be an appealing choice compared with tape from both a cost and benefits perspective. However, the tape comparison is rarely that simple. For example, depending on the amount of data involved and the specific backup and/or archiving practices, any given petabyte of data needing to be protected may have to be copied and retained two or more times, which immediately makes tape seem a bit less competitive. Add overhead costs, personnel, etc., and the “traditional” economics may begin to seem even less appealing.

Tiering, in a mainframe context, is often as much about speed of access as anything else. So, in the tape world, big decisions have to be made constantly about what can be relegated to lower tiers and whether the often much-longer access times will become a problem after that decision has been made. But getting mainframe data to S3, where such concerns are no longer an issue, is now easy. Modern data movement technology means you can move your mainframe data in mainframe format directly to object storage in the cloud so it is available for restore directly from AWS.

Many mainframe organizations have years, even decades of data on tape. The management of this tape data is retained only in the tape management system. Or perhaps it was just copied forward from a prior tape system upgrade.  How much of this data is really needed? Is it even usable anymore? To migrate mainframe to AWS, specifically this older data, allows management of the data in a modern way and can reduce the amount of tape data on-premises.

And what about those tapes that today are shipped off-site for storage and recovery purposes? Why not put that data on cloud storage for recovery anywhere? 

For mainframe organizations interested in removing on-premise tape technology, reducing tape storage sizes, or creating remote backup copies, cloud options like Amazon S3 Intelligent Tiering can offer cost optimization that is better “tuned” to an organization’s real needs than anything devised manually or implemented on-premises. Furthermore, with this cloud-based approach, there is no longer any need to know your data patterns or think about tiering, it just gets done.

Best of all, you can now perform a stand-alone restore directly from cloud. This is especially valuable with ransomware attacks on the rise because there is no dependency on a potentially compromised system.

You can even take advantage of AWS immutable copies and versioning capabilities to further protect your mainframe data.

Getting there

Of course, in order to take advantage of cloud storage like Amazon S3 Intelligent Tiering, you need to find a way to get your mainframe data out of its on-premises environment. Traditionally, that has presented a big challenge. But, as with multiplying storage options, the choices in data movement technology are also improving. For a review of new movement options, take a look at a discussion of techniques and technologies for Mainframe to Cloud Migration.

About the author

Gil Peleg | CEO
Gil has over two decades of hands-on experience in mainframe system programming and data management, as well as a deep understanding of methods of operation, components, and diagnostic tools. Gil previously worked at IBM in the US and in Israel in mainframe storage development and data management practices as well as at Infinidat and XIV. He is the co-author of eight IBM Redbooks on z/OS implementation.
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