Abstract: A method includes receiving an object from a client as part of a data ingestion process, directing the object to an object access microservice, providing a copy of the object to a masker worker microservice, masking the copy of the object to create a masked object, and the masking of the copy of the object is performed inline prior to storage of the object, deduplicating the object, and storing the masked object and the object in storage.

Abstract: A method includes retrieving an object from storage and copying the object, generating a list that identifies one or more byte ranges, of the copy of the object, to be masked, providing the list to a masker controller microservice that examines a recipe corresponding to the copy of the object, where the recipe references a slice of the copy of the object, and the slice includes one or more data segments, masking, by the masker controller microservice, a segment of the slice that is in one of the byte ranges, to create a masked segment, and replacing, in the slice, the segment with the masked segment, to create a masked slice and creating a masked object recipe that contains a reference to the masked slice, creating a masked object that includes the masked slice, and that references any unmasked segments of the slice, and deduplicating the masked object.

Abstract: Systems and methods enabling garbage collection operations and normal system operations concurrently. Concurrent operations are performed by configuring a similarity group to permit garbage collection and normal operations. This may include creating a new subgroup in a similarity group for write and deduplication purposes such that an impacted subgroup can be cleaned.

Abstract: A method includes receiving an object from a client as part of a data ingestion process, directing the object to an object access microservice, providing a copy of the object to a masker worker microservice, masking the copy of the object to create a masked object, and the masking of the copy of the object is performed inline prior to storage of the object, deduplicating the object, and storing the masked object and the object in storage.

Abstract: A method includes retrieving an object from storage and copying the object, generating a list that identifies one or more byte ranges, of the copy of the object, to be masked, providing the list to a masker controller microservice that examines a recipe corresponding to the copy of the object, where the recipe references a slice of the copy of the object, and the slice includes one or more data segments, masking, by the masker controller microservice, a segment of the slice that is in one of the byte ranges, to create a masked segment, and replacing, in the slice, the segment with the masked segment, to create a masked slice and creating a masked object recipe that contains a reference to the masked slice, creating a masked object that includes the masked slice, and that references any unmasked segments of the slice, and deduplicating the masked object.

Abstract: A method includes receiving an object from a client as part of a data ingestion process, directing the object to an object access microservice, providing a copy of the object to a masker worker microservice, masking the copy of the object to create a masked object, and the masking of the copy of the object is performed inline prior to storage of the object, deduplicating the object, and storing the masked object and the object in storage.

Abstract: A method includes retrieving an object from storage and copying the object, generating a list that identifies one or more byte ranges, of the copy of the object, to be masked, providing the list to a masker controller microservice that examines a recipe corresponding to the copy of the object, where the recipe references a slice of the copy of the object, and the slice includes one or more data segments, masking, by the masker controller microservice, a segment of the slice that is in one of the byte ranges, to create a masked segment, and replacing, in the slice, the segment with the masked segment, to create a masked slice and creating a masked object recipe that contains a reference to the masked slice, creating a masked object that includes the masked slice, and that references any unmasked segments of the slice, and deduplicating the masked object.

Abstract: Systems and methods for estimating the number of workers needed to perform a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The number of workers can be determined based on the impacted similarity groups. More specifically, the number of impacted similarity groups and/or workers can be evaluated in terms of memory requirements, input/output constraints and/or time requirements to estimate the number or workers needed to clean similarity groups impacted by a garbage collection operation.

Abstract: A method includes retrieving, with a masker controller job, an object and an associated object ID from a masking bucket that is defined in storage, making a copy of the object, with a masker worker microservice, masking the copy of the object to create a masked object, transmitting the masked object to an object access microservice, with the object access microservice, transmitting the masked object to a deduplication microservice, with the deduplication microservice, deduplicating the masked object, and storing the masked object in the storage.

Abstract: Systems and methods for marking similarity groups impacted by a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The live segments associated with the impacted similarity groups are also identified. This allows segments that are associated with the deleted objects and that are not associated with any live objects to be removed.

Abstract: A method includes retrieving, with a masker controller job, an object and an associated object ID from a masking bucket that is defined in storage, making a copy of the object, with a masker worker microservice, masking the copy of the object to create a masked object, transmitting the masked object to an object access microservice, with the object access microservice, transmitting the masked object to a deduplication microservice, with the deduplication microservice, deduplicating the masked object, and storing the masked object in the storage.

Abstract: A method includes retrieving, with a masker controller job, an object and an associated object ID from a masking bucket that is defined in storage, making a copy of the object, with a masker worker microservice, masking the copy of the object to create a masked object, transmitting the masked object to an object access microservice, with the object access microservice, transmitting the masked object to a deduplication microservice, with the deduplication microservice, deduplicating the masked object, and storing the masked object in the storage.

Abstract: A method includes retrieving an object from storage and copying the object, generating a list that identifies one or more byte ranges, of the copy of the object, to be masked, providing the list to a masker controller microservice that examines a recipe corresponding to the copy of the object, where the recipe references a slice of the copy of the object, and the slice includes one or more data segments, masking, by the masker controller microservice, a segment of the slice that is in one of the byte ranges, to create a masked segment, and replacing, in the slice, the segment with the masked segment, to create a masked slice and creating a masked object recipe that contains a reference to the masked slice, creating a masked object that includes the masked slice, and that references any unmasked segments of the slice, and deduplicating the masked object.

Abstract: A method includes receiving an object from a client as part of a data ingestion process, directing the object to an object access microservice, providing a copy of the object to a masker worker microservice, masking the copy of the object to create a masked object, and the masking of the copy of the object is performed inline prior to storage of the object, deduplicating the object, and storing the masked object and the object in storage.

Abstract: A method includes receiving an object from a client as part of a data ingestion process, by a masker worker, generating a list that identifies one or more byte ranges, of the object, to be masked, providing the list to an object access microservice, by the object access microservice, creating an object recipe of the object, and the object recipe includes one or more slices, and each of the slices includes one or more segments of data, masking only those segments of a slice that are in a byte range identified in the list, creating a masked slice that comprises the masked segments, and creating a masked object recipe that contains a reference to the masked slice, and the masking is performed before the object is stored in storage, creating a masked object that includes the masked slice, and deduplicating the masked object.

Abstract: Systems and methods for estimating the number of workers needed to perform a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The number of workers can be determined based on the impacted similarity groups. More specifically, the number of impacted similarity groups and/or workers can be evaluated in terms of memory requirements, input/output constraints and/or time requirements to estimate the number or workers needed to clean similarity groups impacted by a garbage collection operation.

Abstract: Systems and methods for estimating the number of workers needed to perform a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The number of workers can be determined based on the impacted similarity groups. More specifically, the number of impacted similarity groups and/or workers can be evaluated in terms of memory requirements, input/output constraints and/or time requirements to estimate the number or workers needed to clean similarity groups impacted by a garbage collection operation.

Abstract: Systems and methods for estimating the number of workers needed to perform a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The number of workers can be determined based on the impacted similarity groups. More specifically, the number of impacted similarity groups and/or workers can be evaluated in terms of memory requirements, input/output constraints and/or time requirements to estimate the number or workers needed to clean similarity groups impacted by a garbage collection operation.

Abstract: Systems and methods for marking similarity groups impacted by a garbage collection operation are disclosed. Similarity groups are used to identify segments associated with objects in a computing system. Using deletion records that identify objects to be deleted, the similarity groups impacted by the deletion records can be identified. The live segments associated with the impacted similarity groups are also identified.

Abstract: Systems and methods enabling garbage collection operations and normal system operations concurrently. Concurrent operations are performed by configuring a similarity group to permit garbage collection and normal operations. This may include creating a new subgroup in a similarity group for write and deduplication purposes such that an impacted subgroup can be cleaned.