Extending an expiration time of an object associated with an archive
An amount of expiration time extension for one or more objects associated with a first archive of a first snapshot of a source storage is determined based at least in part on a second data management policy associated with a second archive and one or more dynamically determined metrics. The first archive that includes the one or more objects is caused to be stored to a remote storage. At least a portion of content of the first archive is referenced by data chunks stored in a first chunk object of the remote storage and the first archive is associated with a first data management policy. Based on the determined amount of expiration time extension, an expiration time for the one or more objects associated with the first archive is stored in an archive metadata of the one or more objects associated with the first archive.
1 . A method comprising:
determining, by a computing system, based at least in part on a second data management policy associated with a second archive, an expiration time for one or more objects included in a first archive associated with a first data management policy;
storing, by the computing system, the first archive to a remote storage, wherein at least a portion of the first archive references data chunks stored in a chunk object of the remote storage;
determining, by the computing system, whether the first archive is subject to a data lock period;
before extending the expiration time for the one or more objects included in the first archive, determining, by the computing system, whether to extend the expiration time for the one or more objects included in the first archive based at least in part on a rate of change between the first and second archives;
extending, by the computing system, the expiration time for the one or more objects included in the first archive in response to a determination that the first archive is subject to the data lock period;
determining, by the computing system, the first archive has expired; and
performing, by the computing system, according to the expiration time for the one or more objects included in the first archive, based on determining the first archive has expired and none of one or more objects included in the second archive reference the data chunks stored in the chunk object, garbage collection of the chunk object of the remote storage.
2 . The method of claim 1 , wherein determining the expiration time for the one or more objects included in the first archive comprises applying, by the computing system, a machine learning model to determine the expiration time for the one or more objects included in the first archive.
3 . The method of claim 1 , wherein the second archive comprises an incremental archive of the first archive.
4 . The method of claim 1 , wherein determining whether to extend the expiration time for the one or more objects included in the first archive comprises determining, by the computing system, whether to extend the expiration time for the one or more objects included in the first archive using a machine learning model.
5 . The method of claim 1 , further comprising storing, by the computing system, the expiration time in an archive metadata object associated with the first archive, wherein determining the first archive has expired is based on the expiration time stored in the archive metadata object associated with the first archive.
6 . A computing system comprising:
non-transitory computer-readable storage media storing instructions; and
processing circuitry that executes the instructions to:
determine, based at least in part on a second data management policy associated with a second archive, an expiration time for one or more objects included in a first archive associated with a first data management policy;
store the first archive to a remote storage, wherein at least a portion of the first archive references data chunks stored in a chunk object of the remote storage;
determine whether the first archive is subject to a data lock period;
before extending the expiration time for the one or more objects included in the first archive, determine whether to extend the expiration time for the one or more objects included in the first archive based at least in part on a rate of change between the first and second archives;
extend the expiration time for the one or more objects included in the first archive in response to a determination that the first archive is subject to the data lock period;
determine the first archive has expired; and
perform, according to the expiration time for the one or more objects included in the first archive, based on determining the first archive has expired and none of one or more objects included in the second archive reference the data chunks stored in the chunk object, garbage collection of the chunk object of the remote storage.
7 . The computing system of claim 6 , wherein to determine the expiration time for the one or more objects included in the first archive the processing circuitry that executes the instructions to apply a machine learning model to determine the expiration time for the one or more objects included in the first archive.
8 . The computing system of claim 6 , wherein the second archive comprises an incremental archive of the first archive.
9 . The computing system of claim 6 , wherein the processing circuitry executes the instructions to, before extending the expiration time for the one or more objects included in the first archive, determine, whether to extend the expiration time for the one or more objects included in the first archive using a machine learning model.
10 . The computing system of claim 6 , wherein the processing circuitry executes the instructions to store the expiration time in an archive metadata object associated with the first archive, wherein determining the first archive has expired is based on the expiration time stored in the archive metadata object associated with the first archive.
11 . Non-transitory computer-readable storage media comprising instructions that, when executed, cause processing circuitry of a computing system to:
determine, based at least in part on a second data management policy associated with a second archive, an expiration time for one or more objects included in a first archive associated with a first data management policy;
store the first archive to a remote storage, wherein at least a portion of the first archive references data chunks stored in a chunk object of the remote storage;
determine whether the first archive is subject to a data lock period;
before extending the expiration time for the one or more objects included in the first archive, determine whether to extend the expiration time for the one or more objects included in the first archive based at least in part on a rate of change between the first and second archives;
extend the expiration time for the one or more objects included in the first archive in response to a determination that the first archive is subject to the data lock period;
determine the first archive has expired; and
perform, according to the expiration time for the one or more objects included in the first archive, based on determining the first archive has expired and none of one or more objects included in the second archive reference the data chunks stored in the chunk object, garbage collection of the chunk object of the remote storage.
12 . The non-transitory computer-readable storage media of claim 11 , wherein to determine the expiration time for the one or more objects included in the first archive the instructions, when executed, cause processing circuitry to apply a machine learning model to determine the expiration time for the one or more objects included in the first archive.