摘要:
The embodiments of the invention provide methods, computer program products, etc. for autonomic retention classes when retaining data within storage devices. More specifically, a method of determining whether to retain data within at least one storage device begins by storing data items in at least one storage device. Furthermore, the method maintains access statistics for each of the data items, an age of each of the data items, and an administrator-defined importance value of each of the data items. Following this, a retention value is calculated for each of the data items based on the access statistics for each of the data items, the age of each of the data items, and the administrator-defined importance value of each of the data items.
摘要:
Disclosed is an autonomic abnormality detection device having a plurality of agents, a server with a one or more processors, a data storage device and a corrective actions engine. The device is adapted to detect and diagnose abnormalities in system components. Particularly, the device uses agents to track performance/workload measurements of system components and dynamically compiles a history of those performance/workload measurements for each component. In order to detect abnormalities a processor compares current performance/workload measurements for a component to the compiled histories for that component and for other components. The processor can further be adapted to determine possible causes of a detected abnormality and to report the abnormality, including the possible causes, to a corrective actions engine.
摘要:
The embodiments of the invention provide methods, computer program products, etc. for complaint-based service level objectives. More specifically, a method of deducing undefined service level objectives receives complaints regarding behavior of a system. The complaints could include a severity parameter, an entity parameter, a nature-of-complaint parameter, a timestamp parameter, and/or an identification parameter. Next, system details representing a current state of the system are recorded for each of the complaints. The method then automatically analyzes a history of the system details and the complaints to produce a historical compilation of the system details. The analyzing can include weighing each of the system details by a severity parameter value.
摘要:
Embodiments of the present invention provide a hybrid (e.g., local and remote) approach for data backup in a networked computing environment (e.g., a cloud computing environment). In a typical embodiment, a set of storage configuration parameters corresponding to a set of data to be backed up is received and stored in a computer data structure. The set of storage configuration parameters can comprise at least one of the following: a recovery time objective (RTO), a recovery point objective (RPO), and a desired type of protection for the set of data. Regardless, the set of data is compared to previously stored data to identify at least one of the following: portions of the set of data that have commonality with the previously stored data; and portions of the set of data that are unique to the set of data (i.e., not in common with any of the previously stored data). The above-described process is referred to herein as “de-duplication”. A storage solution is then determined based on the set of storage configuration parameters. In general, the storage solution identifies at least one local storage resource and at least one remote storage resource (e.g., a cloud storage resource) for backing up the portions of the set of data that are unique to the set of data. Once the storage solution has been determined, the unique portions of the set of data will be stored in accordance therewith.
摘要:
The embodiments of the invention provide methods, computer program products, etc. for complaint-based service level objectives. More specifically, a method of deducing undefined service level objectives receives complaints regarding behavior of a system. The complaints could include a severity parameter, an entity parameter, a nature-of-complaint parameter, a timestamp parameter, and/or an identification parameter. Next, system details representing a current state of the system are recorded for each of the complaints. The method then automatically analyzes a history of the system details and the complaints to produce a historical compilation of the system details. The analyzing can include weighing each of the system details by a severity parameter value.
摘要:
A method, system, and article are provided for monitoring performance of hardware devices. Each hardware device is configured with an agent, and the server is configured with a coordinator. The agent collects device data at a first modifiable frequency and communicates the collected data to the coordinator at a second dynamically modifiable frequency. The collected data is periodically monitored and the first and second frequencies are modified subject to evaluation of the collected and monitored data.
摘要:
The embodiments of the invention provide a method, computer program product, etc. for risk-modulated proactive data migration for maximizing utility. More specifically, a method of planning data migration for maximizing utility of a storage infrastructure that is running and actively serving at least one application includes selecting a plurality of potential data items for migration and selecting a plurality of potential migration destinations to which the potential data items can be moved. Moreover, the method selects a plurality of potential migration speeds at which the potential data items can be moved and selects a plurality of potential migration times at which the potential data items can be moved to the potential data migration destinations. The selecting of the plurality of potential migration speeds selects a migration speed below a threshold speed, wherein the threshold speed defines a maximum system utility loss permitted.
摘要:
A system and method of conducting resource flow control sessions in a computer network comprises sending a resource request from a client computer to a server computer; assigning to the client computer a flow control window, wherein a size of a flow control window is based on resources available to the server computer and a level of activity of a corresponding client computer, wherein the server computer is in any of a busy and idle state of activity; determining whether to change the size of the flow control window upon receiving the resource request based on the level of activity of the corresponding client computer and a current utilization of resources during a particular session of use; tracking a number of active sessions of use of the resources in a predetermined time window; and maintaining the flow control window with a maximum queue size per number of sessions value.
摘要:
The embodiments of the invention provide methods, computer program products, etc. for autonomic retention classes when retaining data within storage devices. More specifically, a method of determining whether to retain data within at least one storage device begins by storing data items in at least one storage device. Furthermore, the method maintains access statistics for each of the data items, an age of each of the data items, and an administrator-defined importance value of each of the data items. Following this, a retention value is calculated for each of the data items based on the access statistics for each of the data items, the age of each of the data items, and the administrator-defined importance value of each of the data items.
摘要:
The embodiments of the invention provide methods, computer program products, etc. for autonomic retention classes when retaining data within storage devices. More specifically, a method of determining whether to retain data within at least one storage device begins by storing data items in at least one storage device. Furthermore, the method maintains access statistics for each of the data items, an age of each of the data items, and an administrator-defined importance value of each of the data items. Following this, a retention value is calculated for each of the data items based on the access statistics for each of the data items, the age of each of the data items, and the administrator-defined importance value of each of the data items.