Abstract:
Embodiments are directed towards the visualization of machine data received from computing clusters. Embodiments may enable improved analysis of computing cluster performance, error detection, troubleshooting, error prediction, or the like. Individual cluster nodes may generate machine data that includes information and data regarding the operation and status of the cluster node. The machine data is received from each cluster node for indexing by one or more indexing applications. The indexed machine data including the complete data set may be stored in one or more index stores. A visualization application enables a user to select one or more analysis lenses that may be used to generate visualizations of the machine data. The visualization application employs the analysis lens to produce visualizations of the computing cluster machine data.
Abstract:
Embodiments are directed towards generating data models that may give semantic meaning for unstructured data or structured data that may include data generated and/or received by search engines, including a time series engine. Data models also may be generated to provide semantic meaning to structured data. A data model may be composed of a hierarchical data model objects analogous to an object-oriented programming class hierarchy. Users may employ a data modeling application to produce reports using search objects that may be part of, or associated with the data model. The data modeling application may employ the search object and the data model to generate a query string for searching a data repository to produce a result set. A data modeling application may map the result set data to data model objects that may be used to generate reports.
Abstract:
A metric value is determined for each event in a set of events that characterizes a computational communication or object. For example, a metric value could include a length of a URL or agent string in the event. A subset criterion is generated, such that metric values within the subset are relatively separated from a population's center (e.g., within a distribution tail). Application of the criterion to metric values produces a subset. A representation of the subset is presented in an interactive dashboard. The representation can include unique values in the subset and counts of corresponding event occurrences. Clients can select particular elements in the representation to cause more detail to be presented with respect to individual events corresponding to specific values in the subset. Thus, clients can use their knowledge system operations and observance of value frequencies and underlying events to identify anomalous metric values and potential security threats.
Abstract:
A disclosed computer-implemented method includes receiving and indexing the raw data. Indexing includes dividing the raw data into time stamped searchable events that include information relating to computer or network security. Store the indexed data in an indexed data store and extract values from a field in the indexed data using a schema. Search the extracted field values for the security information. Determine a group of security events using the security information. Each security event includes a field value specified by a criteria. Present a graphical interface (GI) including a summary of the group of security events, other summaries of security events, and a remove element (associated with the summary). Receive input corresponding to an interaction of the remove element. Interacting with the remove element causes the summary to be removed from the GI. Update the GI to remove the summary from the GI.
Abstract:
Embodiments are directed towards managing within a cluster environment having a plurality of indexers for data storage using redundancy the data being managed using a generation identifier, such that a primary indexer is designated for a given generation of data. When a master device for the cluster fails, data may continue to be stored using redundancy, and data searches performed may still be performed.
Abstract:
A first feature (e.g., chart or table) includes a reference to a dynamic pointer. Independently, the pointer is defined to point to a second feature (e.g., a query). The first feature is automatically updated to reflect a current value of the second feature. The reference to the pointer and pointer definition are recorded in a central registry, and changes to the pointer or second feature automatically cause the first feature to be updated to reflect the change. A mapping between features can be generated using the registry and can identify interrelationships to a developer. Further, changes in the registry can be tracked, such that a developer can view changes pertaining to a particular time period and/or feature of interest (e.g., corresponding to an operation problem).
Abstract:
A first feature (e.g., chart or table) includes a reference to a dynamic pointer. Independently, the pointer is defined to point to a second feature (e.g., a query). The first feature is automatically updated to reflect a current value of the second feature. The reference to the pointer and pointer definition are recorded in a central registry, and changes to the pointer or second feature automatically cause the first feature to be updated to reflect the change. A mapping between features can be generated using the registry and can identify interrelationships to a developer. Further, changes in the registry can be tracked, such that a developer can view changes pertaining to a particular time period and/or feature of interest (e.g., corresponding to an operation problem).
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-levet 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.
Abstract:
Embodiments are directed towards a dynamic change evaluation mechanism, whereby items having a detected possible change are scheduled for re-evaluation for possible changes at a higher frequency than items detected to not have previously changed, while those items detected as not to have changed are dynamically scheduled for re-evaluation based on an evaluation backlog that may be in turn based, in part, on a time from when an item is assigned an expiration time to when the item is evaluated. In one embodiment, a possibly changed item may be assigned a new expiration time independent of the evaluation backlog. In another embodiment, if no change is detected, then the item may be assigned a new expiration time as a function of a previous expiration time and on the evaluation backlog.
Abstract:
A method, system, and processor-readable storage medium are directed towards calculating approximate order statistics on a collection of real numbers. In one embodiment, the collection of real numbers is processed to create a digest comprising hierarchy of buckets. Each bucket is assigned a real number N having P digits of precision and ordinality O. The hierarchy is defined by grouping buckets into levels, where each level contains all buckets of a given ordinality. Each individual bucket in the hierarchy defines a range of numbers—all numbers that, after being truncated to that bucket's P digits of precision, are equal to that bucket's N. Each bucket additionally maintains a count of how many numbers have fallen within that bucket's range. Approximate order statistics may then be calculated by traversing the hierarchy and performing an operation on some or all of the ranges and counts associated with each bucket.