Abstract: In some examples, a host name that is known to correspond to a first source component may be identified. The host name may be searched in a second source component. A topological linkage may be inferred between the first and the second source component in response to finding the host name in the second source component.

Abstract: A computer-implemented method includes determining a plurality of bulk sets for querying database records. The method also includes assigning a plurality of keysets to the plurality of bulk sets, with each keyset comprising a unique set of dimension attribute values from the database records. The method also includes calculating a predicted load score of each bulk set. The method also includes performing a transfer of a keyset from a first bulk set to a second bulk set when the transfer reduces a difference between predicted load scores of the first bulk set and the second bulk set. The method also includes, after the transfer, executing bulk queries using the plurality of bulk sets.

Abstract: According to an example, a batch processing system is to determine a cluster of related metrics. A stability of a baseline for a metric in the cluster is determined. A frequency of execution of batch jobs for calculating baselines for metrics is determined based on the stability.

Abstract: Examples relate to calculating normalize metrics. The examples disclosed herein calculate respective normalized first metric values for each of a plurality of first metric values that are on a time scale and respective normalized second metric values for each of the plurality of raw second metric values that are on the time scale, where the plurality of first metric values are associated with a first metric, and the plurality of second metric values are associated with a second metric. An extremum of the normalized first metric value and the normalized second metric value at each time of the time scale is averaged to calculate a plurality of extremum baseline values. Examples herein calculate a plurality of sleeve values of the plurality of extremum baseline values based on a standard deviation of the plurality of extremum baseline values.

Abstract: In some examples, a host name that is known to correspond to a first source component may be identified. The host name may be searched in a second source component. A topological linkage may be inferred between the first and the second source component in response to finding the host name in the second source component.

Abstract: Examples relate to calculating normalize metrics. The examples disclosed herein calculate respective normalized first metric values for each of a plurality of first metric values that are on a time scale and respective normalized second metric values for each of the plurality of raw second metric values that are on the time scale, where the plurality of first metric values are associated with a first metric, and the plurality of second metric values are associated with a second metric. An extremum of the normalized first metric value and the normalized second metric value at each time of the time scale is averaged to calculate a plurality of extremum baseline values. Examples herein calculate a plurality of sleeve values of the plurality of extremum baseline values based on a standard deviation of the plurality of extremum baseline values.

Abstract: A computer-implemented method includes determining a plurality of bulk sets for querying database records. The method also includes assigning a plurality of keysets to the plurality of bulk sets, with each keyset comprising a unique set of dimension attribute values from the database records. The method also includes calculating a predicted load score of each bulk set. The method also includes performing a transfer of a keyset from a first bulk set to a second bulk set when the transfer reduces a difference between predicted load scores of the first bulk set and the second bulk set. The method also includes, after the transfer, executing bulk queries using the plurality of bulk sets.

Abstract: According to an example, a batch processing system is to determine a cluster of related metrics. A stability of a baseline for a metric in the cluster is determined. A frequency of execution of batch jobs for calculating baselines for metrics is determined based on the stability.