Abstract:
The disclosed system and method acquire and store performance measurements relating to performance of a component in an information technology (IT) environment and log data produced by the IT environment, in association with corresponding time stamps. The disclosed system and method correlate at least one of the performance measurements with at least one of the portions of log data.
Abstract:
The disclosed system and method acquire and store performance measurements relating to performance of a component in an information technology (IT) environment and log data produced by the IT environment, in association with corresponding time stamps. The disclosed system and method correlate at least one of the performance measurements with at least one of the portions of log data.
Abstract:
A service monitoring system executing on one or more processors may have operations that are determined by control information. Control over the operation of the service monitoring system can be exerted through the use of a graphical interface. The graphical interface may present the control information of a new or existing correlation search definition for user interaction. The service monitoring system may maintain a data store of key performance indicator (KPI) data, where a KPI value in the data store is produced by a KPI-defining search query that derives the value from machine data associated with one or more entities that perform a monitored service. A correlation search definition of the service monitoring system determines how a search of the KPI data is conducted, how its data is evaluated to determine whether a triggering condition has been met, and, if so, determines what triggered action is to be initiated.
Abstract:
The disclosed embodiments relate to a system for monitoring a virtual-machine environment. During operation, the system identifies a parent and a set of two or more child components that are related to the parent component in the virtual-machine environment. Next, the system determines a performance metric for each child component in the set of two or more child components. The system then determines a child-component performance state for each child component in the set of two or more child components based on the performance metric for the child component and a child-component state criterion. Finally, the system determines a parent state for the parent component based on the child-component performance state for each child component in the set of two or more child components and a parent-component state criterion, wherein the parent-component state criterion includes a threshold percentage or number of child components that have a specified state.
Abstract:
The disclosed system and method acquire and store performance measurements relating to performance of a component in an information technology (IT) environment and log data produced by the IT environment, in association with corresponding time stamps. The disclosed system and method correlate at least one of the performance measurements with at least one of the portions of log data.
Abstract:
A scheduler manages execution of a plurality of data-collection jobs, assigns individual jobs to specific forwarders in a set of forwarders, and generates and transmits tokens (e.g., pairs of data-collection tasks and target sources) to assigned forwarders. The forwarder uses the tokens, along with stored information applicable across jobs, to collect data from the target source and forward it onto an indexer for processing. For example, the indexer can then break a data stream into discrete events, extract a timestamp from each event and index (e.g., store) the event based on the timestamp. The scheduler can monitor forwarders' job performance, such that it can use the performance to influence subsequent job assignments. Thus, data-collection jobs can be efficiently assigned to and executed by a group of forwarders, where the group can potentially be diverse and dynamic in size.
Abstract:
Techniques promote monitoring of hypervisor systems by presenting dynamic representations of hypervisor architectures that include performance indicators. A reviewer can interact with the representation to progressively view select lower-level performance indicators. Higher level performance indicators can be determined based on lower level state assessments. A reviewer can also view historical performance metrics and indicators, which can aid in understanding which configuration changes or system usages may have led to sub-optimal performance.
Abstract:
A virtual-machine environment can include a parent component (e.g., a host cluster, a host or a set of virtual machines) that is a parent to a set of two or more child components. For example, a host cluster can be a parent to multiple hosts; a host can be a parent to multiple virtual machines; and a set of virtual machines can be a parent to multiple virtual machines. Performance metrics for the child components can be monitored. A child-component performance state can be determined for each child component in the set of two or more child components using a corresponding monitored performance metric and a child-component state criterion (e.g., that maps performance-metric values to states). A parent performance state can be determined for the parent component using the child-component performance state for each child component in the set and a parent-component state criterion.
Abstract:
A scheduler manages execution of a plurality of data-collection jobs, assigns individual jobs to specific forwarders in a set of forwarders, and generates and transmits tokens (e.g., pairs of data-collection tasks and target sources) to assigned forwarders. The forwarder uses the tokens, along with stored information applicable across jobs, to collect data from the target source and forward it onto an indexer for processing. For example, the indexer can then break a data stream into discrete events, extract a timestamp from each event and index (e.g., store) the event based on the timestamp. The scheduler can monitor forwarders' job performance, such that it can use the performance to influence subsequent job assignments. Thus, data-collection jobs can be efficiently assigned to and executed by a group of forwarders, where the group can potentially be diverse and dynamic in size.
Abstract:
Techniques promote monitoring of hypervisor systems by presenting dynamic representations of hypervisor architectures that include performance indicators. A reviewer can interact with the representation to progressively view select lower-level performance indicators. Higher level performance indicators can be determined based on tower level state assessments. A reviewer can also view historical performance metrics and indicators, which can aid in understanding which configuration changes or system usages may have led to sub-optimal performance.