Abstract: Performance data is collected for input/output operations executed at a storage device of a plurality of storage devices of a software-defined storage network. Based on the collected performance data, a time-based I/O performance profile for the storage device is determined. A characteristic time-based I/O performance profile is determined for a representative group of storage devices having common characteristics with the storage device and based on previously collected performance data for devices of the representative group. It is determined that the difference between the time-based I/O performance profile for the storage device and the characteristic time-based I/O performance profile exceeds a predetermined deviance threshold that is indicative of a probable failure of the storage device. An indication is generated that the storage device exceeded the predetermined deviance threshold.

Abstract: Techniques are disclosed for generating and utilizing a time-based distribution of I/O latency and other performance characteristics to identify potential device failures in a system that includes storage devices, such as a distributed software-defined storage system. A user interface is implemented that allows users to request and selectively view I/O latency and other data over a configurable time-based or histogram-based distribution. The user interface further enables comparison of the I/O latency distribution to data from other devices in the same class to identify potential failures.

Abstract: Performance data is collected for input/output operations executed at a storage device of a plurality of storage devices of a software-defined storage network. Based on the collected performance data, a time-based I/O performance profile for the storage device is determined. A characteristic time-based I/O performance profile is determined for a representative group of storage devices having common characteristics with the storage device and based on previously collected performance data for devices of the representative group. It is determined that the difference between the time-based I/O performance profile for the storage device and the characteristic time-based I/O performance profile exceeds a predetermined deviance threshold that is indicative of a probable failure of the storage device. An indication is generated that the storage device exceeded the predetermined deviance threshold.

Abstract: Techniques are disclosed for generating and utilizing a time-based distribution of I/O latency and other performance characteristics to identify potential device failures in a system that includes storage devices, such as a distributed software-defined storage system. A user interface is implemented that allows users to request and selectively view I/O latency and other data over a configurable time-based or histogram-based distribution. The user interface further enables comparison of the I/O latency distribution to data from other devices in the same class to identify potential failures.

Abstract: Monitoring the health of a computer system and suggesting an order of repair when problems within the computer system have been identified. Problem(s) and problem entity(s) within the computer system are identified during monitoring. Relationship(s) of the problem entities with other entities in the computer system are identified. A relationship type for each of the identified relationship(s) is determined. A combination of the identified problem(s), the identified problem entity(s), and the determined relationship type(s) is analyzed to determine an order in which repairs of one or more user-visible entities of the computing system should occur in order to address the identified problem(s). An alert comprising the determined order of the repairs is then presented to a user.

Abstract: Monitoring the health of a computer system based on the relationships of entities, and the intelligent presentation of alerts based thereon. A rule-based engine may perform the monitoring and alerting. Problem(s) and problem entity(s) within a computing system are identified during the monitoring. Relationship(s) of the problem entity(s) with other entities in the computer system are then identified. A relationship type for each of the identified relationship(s) is determined. A combination of the identified problem(s), the identified problem entity(s), and the determined relationship type(s) are analyzed to determine root cause(s) of the problem(s). Based on the root cause(s), an alert is presented to a user comprising one or more actions the user can take regarding one or more user-visible entities of the computer system to fix the identified problem(s). The alerts may be fewer in number and more intuitive due to the analysis.

Abstract: Monitoring the health of a computer system and suggesting an order of repair when problems within the computer system have been identified. Problem(s) and problem entity(s) within the computer system are identified during monitoring. Relationship(s) of the problem entities with other entities in the computer system are identified. A relationship type for each of the identified relationship(s) is determined. A combination of the identified problem(s), the identified problem entity(s), and the determined relationship type(s) is analyzed to determine an order in which repairs of one or more user-visible entities of the computing system should occur in order to address the identified problem(s). An alert comprising the determined order of the repairs is then presented to a user.