Abstract: A distributed storage system includes a primary storage system and a secondary storage system. The secondary storage system stores the actual data and the primary storage system stores metadata for the actual data. The metadata references at the primary storage system may be deleted without deleting the corresponding data at the secondary storage system. Snapshots of the metadata at the primary storage system are sent to the secondary storage system. The secondary storage system can compare two metadata snapshots received from the primary storage in order to determine whether data stored at the secondary storage system has been deleted at the primary storage system for longer than a retention period. Such data may be deleted to free up storage space at the secondary storage server.

Abstract: A distributed storage system includes a primary storage system and a secondary storage system. The secondary storage system stores the actual data and the primary storage system stores metadata for the actual data. The metadata references at the primary storage system may be deleted without deleting the corresponding data at the secondary storage system. Snapshots of the metadata at the primary storage system are sent to the secondary storage system. The secondary storage system can compare two metadata snapshots received from the primary storage in order to determine whether data stored at the secondary storage system has been deleted at the primary storage system for longer than a retention period. Such data may be deleted to free up storage space at the secondary storage server.

Abstract: Test suite recommendations for testing a software application are automatically generated and applied. The system extracts and learns all available, relevant data concerning the intended operation of a software release; this information can be automatically obtained, for example, from engineering tools and systems, previous releases, and/or from other sources. Based on the extracted information, the system automatically recommends any number of test suites. In at least one embodiment, machine learning techniques are applied, so that the system is able to learn which tests and test suites are most effective for certain characteristics of software applications, and to learn what parameters for such tests should be applied. Once the system has automatically selected test suite(s), tests from the test suite(s) can be automatically run on the software product being developed. Results from such tests can be used to inform developers as to issues and/or problems with the software application.