Self-learning and best-practice profiling and alerting with relative and absolute capacity

摘要

For example, as indicated in the Incorporated Disclosures, rapid change from relatively little use of network bandwidth, to heavy overuse of network bandwidth (combined with a large number of endpoints attempting to access that network bandwidth) can often indicate an email virus or other maladjusted use of the system. In such cases, it could be appropriate to generate an alert, and bring the change to the attention of a human expert, or otherwise escalate the problem. Best practices In this Application, the phrase “best practices,” and variants thereof, can generally refer to business preferences (and to business rules imposed by management, or law or regulation), such as high utilization preferences often expressed by management. In such cases, one or more operators can enter descriptors of rules the system that it is desired the system follow, such as “processor cycle utilization 90%.” When these best practices are not followed, it could be appropriate to generate an alert, bring the change to the attention of a human expert, or otherwise escalate the problem. Profiling and alerting In this Application, the phrase “profiling and alerting,” and variants thereof, can generally refer to maintaining a profile of how the system normally behaves, absent stressors, and to identify any substantial changes from that profile. When a profile is seriously violated, it could be appropriate to generate an alert, bring the change to the attention of a human expert, or otherwise escalate the problem. In such cases, it can be appropriate to escalate the severity of the alert with increased severity of violation, increased time duration of the violation, and increased trajectory in the direction of further violation. Relative and absolute capaci-ty In this Application, the phrase “absolute capacity,” and variants thereof, can refer to an objective measure of system capacity, such as whether the system has 1 TB or 4 TB of memory. The phrase “relative capacity,” and variants thereof, can refer to a subjective measure of system capacity, such as when the system has 4 TB of physical memory, but 3.5 TB of that memory are allocated to a high-priority task whose interruption or pause would be untoward.