Rule book based retention management engine
Systems and methods for determining retention periods or policies for backups are disclosed. A rule book stores relationships between rules and recommended retention periods. Data related to a backup is collected and organized. A query is generated from the organized data and used to identify a rule from the rule book. The retention period corresponding to the identified rule in the rule book is then applied to the corresponding backup.
1. A method for determining a retention period for a backup, the method comprising:
receiving raw data at a polling engine from at least a host, wherein the host includes source data to be backed up during a backup operation and the target device includes storage for storing a backup of the source data and wherein the raw data includes data relevant to determining the retention period for retaining the backup of the source data;
interpreting the raw data into categories of factors to generate grouped data;
forming a query from the grouped data by a rule-maker;
searching a rule book based on the query for a rule that matches the query, wherein the rule that matches the query identifies a recommended retention period for the backup, wherein the rule book associates rules with retention periods and each rule associates a retention period with a specific combination of the raw data that has been grouped into the categories of factors;
generating a backup of the source data;
storing the backup at the target device;
applying the recommended retention period associated with the rule in the rule book that matched the query to the backup; and
optimizing the rule book and formation of the query based on historical data including pervious queries and queries that are overridden such that an accuracy of the rule book is improved and such that a frequency of unacceptable recommended retention periods is reduced.
2. The method of claim 1 , wherein receiving raw data from a host includes polling the host and polling the target device and polling the application.
3. The method of claim 1 , wherein the target device includes one or more of a primary storage site, a disaster recovery site, and an archive site.
4. The method of claim 1 , wherein the raw data is mapped to the categories of factors, the factors including one or more of a data type, a data change, a schedule, a storage type, and a storage quota available.
5. The method of claim 1 , further comprising receiving a user-defined retention policy that is added to the query before searching the rule book.
6. The method of claim 1 , further comprising adding a rule to the rule book.
7. The method of claim 1 , further comprising revising the categories of factors based on historical data associated with the retention periods.
8. The method of claim 1 , wherein the rule book stores predetermined rules and recommended retention periods.
9. The method of claim 1 , further comprising publishing the retention period to a final buffer, wherein a policy engine enforces the retention period for the backup.
10. A non-transitory computer readable medium comprising instructions for implementing a method for determining a retention period for a backup, the method comprising:
receiving raw data at a polling engine from at least a host, wherein the host includes source data to be backed up during a backup operation and the target device includes storage for storing a backup of the source data and wherein the raw data includes data relevant to determining the retention period for retaining the backup of the source data;
interpreting the raw data into categories of factors to generate grouped data;
forming a query from the grouped data by a rule-maker;
searching a rule book based on the query for a rule that matches the query, wherein the rule that matches the query identifies a recommended retention period for the backup, wherein the rule book associates rules with retention periods and each rule associates a retention period with a specific combination of the raw data that has been grouped into the categories of factors;
generating a backup of the source data;
storing the backup at the target device;
applying the recommended retention period associated with the rule in the rule book that matched the query to the backup; and
optimizing the rule book and formation of the query based on historical data including pervious queries and queries that are overridden such that an accuracy of the rule book is improved and such that a frequency of unacceptable recommended retention periods is reduced.
11. The non-transitory computer readable medium of claim 10 , wherein receiving raw data from a host includes polling the host and polling the target device and polling the application.
12. The non-transitory computer readable medium of claim 10 , wherein the target device includes one or more of a primary storage site, a disaster recovery site, and an archive site.
13. The non-transitory computer readable medium of claim 10 , wherein the raw data is mapped to the categories of factors, the factors including one or more of a data type, a data change, a schedule, a storage type, and a storage quota available.
14. The non-transitory computer readable medium of claim 10 , further comprising receiving a user-defined retention policy that is added to the query before searching the rule book.
15. The non-transitory computer readable medium of claim 10 , further comprising adding a rule to the rule book.
16. The non-transitory computer readable medium of claim 10 , further comprising revising the categories of factors based on historical data associated with the retention periods.
17. The non-transitory computer readable medium of claim 10 , wherein the rule book stores predetermined rules and recommended retention periods.
18. The non-transitory computer readable medium of claim 10 , further comprising publishing the retention period to a final buffer, wherein a policy engine enforces the retention period for the backup.