Many enterprises have data that doesn't need to be accessed frequently. Higher-volume, lower-cost and lower-performance...
resources are good options in these AWS data management situations.
Data has a lifecycle, and it moves between storage resources over the course of that lifecycle. Storage lifecycle management is increasingly important as organizations seek to limit storage investments, especially when it comes to operating expenses like cloud storage.
Public cloud providers, like AWS, implement storage lifecycle management, allowing data to migrate to or from other storage services. In most cases, lifecycle management options allow a user's predetermined rules to automatically migrate data objects to other storage options or to schedule unnecessary or expired data to be deleted. Simple Storage Service (S3) allows up to 1,000 rules per bucket.
Admins use the Amazon S3 console, AWS SDK or API to create lifecycle configurations. The configurations are XML files, which are attached to S3 buckets. Lifecycle rules move objects to other S3 storage classes, such as S3 Infrequent Access (IA) or Glacier archives. The rules also impose expiration actions, like deleting expired objects. However, S3 objects can only migrate to Glacier archives -- not from them. Once an object is in Glacier, admins can access it by creating a temporary copy from Glacier to S3. This means the original Glacier instance of the object remains untouched. Admins can delete Glacier data through lifecycle rules only after 90 days.
S3 IA also plays a valuable role in data object lifecycle planning. Data is normally stored to the S3 "standard" storage class, but the IA class provides a lower-cost, lower-performance option for data that is accessed less frequently but still must be readily accessible. This is unlike Glacier, which may take up to five hours to restore to S3. While IA may be less expensive than standard S3, there is a retrieval fee for IA objects, so admins must consider access frequency and corresponding storage lifecycle management costs before they migrate objects to IA. In many cases, data moves from standard S3 to IA for a time before finally being relegated from IA to Glacier for long-term offline retention.
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