What ILM rule filtering is

When you create an ILM rule, you specify filtering criteria to identify which objects the rule applies to.

Filtering criteria can be simple or complex.

In the simplest case, a rule might not specify any filtering criteria. A rule without filtering criteria applies to all objects, which might be exactly what you need if all of your data has the same storage requirements.

An example of a rule without filtering criteria is the stock rule Make 2 Copies, which stores two replicated object copies forever on any two Storage Nodes. The Make 2 Copies rule can be used for all objects if you do not have more specific storage needs. You can also include the Make 2 Copies rule as the default rule in an ILM policy to provide storage instructions for objects that do not meet any of the filtering criteria in other rules.

Basic filtering criteria allow you to apply different rules to large, distinct groups of objects. The filters available on the Define Basics page of the Create ILM Rule wizard are for Tenant Accounts, and for S3 Buckets or Swift containers.

ILM wizard: step 1 of 3

These basic filters give you a simple way to apply different rules to large numbers of objects. For example, your company's financial records might need to be stored to meet regulatory requirements, while data from the marketing department might need to be stored to facilitate daily operations. After creating separate tenant accounts for each department or after segregating data from the different departments into separate S3 buckets, you can easily create one rule that applies to all financial records and a second rule that applies to all marketing data.

The Advanced Filtering page of the Create ILM Rule wizard gives you very granular control. You can create filtering criteria to select objects based on the following object properties:

You can use advanced filtering to create very specific filtering criteria. For example, objects stored by a hospital's imaging department might be used frequently when they are less than 30 days old and infrequently afterwards, while objects that contain patient visit information might need to be copied to the billing department at the health network's headquarters. You can create filters that identify each type of object based on object name, size, S3 object tags, or any other relevant criteria, and then create separate rules to store each set of objects appropriately.

You can also combine basic and advanced filtering criteria as needed in a single rule. For example, the marketing department might want to store large image files differently than their vendor records, while the Human Resources department might need to store personnel records in a specific geography and policy information centrally. In this case you can create rules that filter by tenant account to segregate the records from each department, while using advanced filters in each rule that identify the specific type of objects that the rule applies to.