Storage Tiering

Storage tiering matches the cost of storing data to how it is used. Cloud providers offer several classes of object storage, from high-performance tiers designed for frequently accessed data to archive tiers that cost a fraction as much but take longer and cost more to retrieve. Most organizations have large amounts of data that is rarely or never read after its first few weeks, such as logs, backups, old project files and historical records. Keeping all of it in the most expensive tier wastes money.

Tiering moves data to cheaper classes as it ages or as its access pattern changes, either through rules or automatically. Done well, it can reduce storage costs significantly without affecting applications. For IT financial management, storage tiering is an important optimization lever because storage costs grow steadily as data accumulates, and they persist long after the data has stopped being useful.

Definition of Storage Tiering

Storage tiering is the placement and movement of data across storage classes that differ in cost, performance, availability and retrieval charges, according to how frequently the data is accessed and how quickly it must be available.

It is part of cloud cost optimization and is closely linked to data lifecycle management, which also covers retention and deletion.

Typical Storage Classes

Standard or hot tiers are designed for data that is accessed frequently, with low latency and no retrieval fees, but the highest storage price per gigabyte.

Infrequent access or cool tiers cost less to store but charge for each retrieval and may have minimum storage periods. They suit data accessed occasionally, such as monthly reports or recent backups.

Archive or cold tiers offer the lowest storage prices, but retrieval can take minutes to hours and carries higher charges. They suit data kept for compliance or long-term records that is rarely read.

Lifecycle Rules and Automatic Tiering

Lifecycle rules move data between tiers or delete it based on age, for example moving logs to an infrequent access tier after 30 days, to an archive tier after 90 days and deleting them after seven years.

Some providers offer automatic tiering classes that monitor each object's access and move it between tiers without manual rules, for a small monitoring fee. These suit data with unpredictable access patterns.

Choosing between lifecycle rules and automatic tiering depends on how predictable the access pattern is and how many objects are involved.

Importance of Storage Tiering in IT Financial Management

Storage is one of the few cloud costs that grows almost automatically, since data keeps accumulating unless it is deleted. Over years, storage can become a large share of the cloud bill.

Tiering slows that growth. It does not stop data from accumulating, but it ensures that older data costs far less to keep than new data that is in active use.

It also encourages organizations to think about how long data should be kept, which supports both cost control and data governance.

Cost Reduction

The price difference between hot and archive tiers is large, often an order of magnitude or more per gigabyte. Moving rarely accessed data to lower tiers can therefore reduce storage costs substantially.

Because lifecycle rules apply automatically to new data, savings continue to grow as data ages, without ongoing manual effort.

Tiering complements deleting data that is no longer needed, which removes the cost entirely and reduces cloud waste. Reviewing what data is kept, and why, often reveals datasets that can be removed altogether, which is a form of cloud cost optimization that requires no new tools.

Trade-Offs

Lower tiers charge for retrieval and may have minimum storage durations, so moving data that is accessed more often than expected can increase costs. Understanding access patterns before tiering is essential.

Retrieval times in archive tiers can be long, so data that may be needed quickly in an emergency, such as recent backups, should not be archived too early.

Compliance and legal requirements may dictate how long data must be kept and how quickly it must be retrievable, which should be reflected in tiering and retention rules.