Predictive diagnosis of SLA violations in cloud services by seasonal trending and forecasting with thread intensity analytics
US-9692662-B2 · Jun 27, 2017 · US
US10127695B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10127695-B2 |
| Application number | US-201715445763-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 28, 2017 |
| Priority date | Feb 29, 2016 |
| Publication date | Nov 13, 2018 |
| Grant date | Nov 13, 2018 |
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Techniques are described for generating period profiles. According to an embodiment, a set of time series data is received, where the set of time series data includes data spanning a plurality of time windows having a seasonal period. Based at least in part on the set of time-series data, a first set of sub-periods of the seasonal period is associated with a particular class of seasonal pattern. A profile for a seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern is generated and stored, in volatile or non-volatile storage. Based on the profile, a visualization is generated for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.
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What is claimed is: 1. A method comprising: receiving a set of time series data that includes data spanning a plurality of time windows having a seasonal period; associating, based at least in part on the set of time series data, a first set of sub-periods of the seasonal period with a particular class of seasonal pattern; wherein, after associating the first set of sub-periods with the particular class of seasonal pattern, a second set of sub-periods is not associated with the particular class of seasonal pattern; generating and storing, in volatile or non-volatile storage, a profile for the seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern; causing, based on the profile, a visualization for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern. 2. The method of claim 1 , wherein associating the particular seasonal class is one of a first class for dense highs, a second class for sparse highs, a third class for dense lows, or a fourth class for sparse lows. 3. The method of claim 2 , wherein the visualization identifies which sub-periods of the seasonal period are sparse highs. 4. The method of claim 1 , wherein the visualization identifies a buffer in values that fall within sub-periods associated with the particular class of seasonal pattern. 5. The method of claim 1 , wherein data within sub-periods that have been classified differently are displayed in different colors. 6. The method of claim 1 , wherein sub-periods that have been classified differently are displayed in different colors on a calendar interface. 7. The method of claim 1 , wherein values from the profile are displayed in a manner that is based on how the sub-periods have been classified. 8. The method of claim 1 , further comprising selecting or restricting values to display from the profile based on how the sub-periods have been classified. 9. The method of claim 8 , further comprising displaying only values from sub-periods that have been classified as sparse highs. 10. The method of claim 1 , wherein the visualization is marked to distinguish between different classifications of sub-periods. 11. One or more non-transitory computer-readable media storing instructions, which, when executed by one or more hardware processors, cause performance of operations comprising: receiving a set of time series data that includes data spanning a plurality of time windows having a seasonal period; associating, based at least in part on the set of time series data, a first set of sub-periods of the seasonal period with a particular class of seasonal pattern; wherein, after associating the first set of sub-periods with the particular class of seasonal pattern, a second set of sub-periods is not associated with the particular class of seasonal pattern; generating and storing, in volatile or non-volatile storage, a profile for the seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern; causing, based on the profile, a visualization for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern. 12. The one or more non-transitory computer-readable media of claim 11 , wherein associating the particular seasonal class is one of a first class for dense highs, a second class for sparse highs, a third class for dense lows, or a fourth class for sparse lows. 13. The one or more non-transitory computer-readable media of claim 12 , wherein the visualization identifies which sub-periods of the seasonal period are sparse highs. 14. The one or more non-transitory computer-readable media of claim 11 , wherein the visualization identifies a buffer in values that fall within sub-periods associated with the particular class of seasonal pattern. 15. The one or more non-transitory computer-readable media of claim 11 , wherein data within sub-periods that have been classified differently are displayed in different colors. 16. The one or more non-transitory computer-readable media of claim 11 , wherein sub-periods that have been classified differently are displayed in different colors on a calendar interface. 17. The one or more non-transitory computer-readable media of claim 11 , wherein values from the profile are displayed in a manner that is based on how the sub-periods have been classified. 18. The one or more non-transitory computer-readable media of claim 11 , the instructions further causing operations comprising selecting or restricting values to display from the profile based on how the sub-periods have been classified. 19. The one or more non-transitory computer-readable media of claim 18 , the instructions further causing operations comprising displaying only values from sub-periods that have been classified as sparse highs. 20. The one or more non-transitory computer-readable media of claim 11 , wherein the visualization is marked to distinguish between different classifications of sub-periods.
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