Abstract: A system for providing adaptive metric pruning includes a processor; a memory; and one or more modules stored in the memory and executable by a processor to perform operations including: receive, by a collector, metadata associated with the business transaction running in a monitored environment; train a machine learning system by providing training data and an anticipated result for the training data to the machine learning system to generate rules for retaining given metadata; predict a retention requirement for the received metadata by providing the received metadata to the machine learning system to apply the generated rules and generate a result for retaining the received metadata; and provide a user interface to display the generated result for retaining the received metadata including a recommendation on how to retain the received metadata according to the result for retaining the received metadata.

Abstract: Instead of processing a complex query having multiple interdependent levels of subqueries as-is, each level is processed to return results in subsets. Each level of subquery can be chunked or the results broken into subsets using pagination. The smaller subsets of the results are streamed back to the requestor and the next level of subquery to continue processing the complex query to substantially decrease the user's time to value when running a complex query by returning some immediate results for display which are refined and eventually converge on the full results as each chunked query runs.

Abstract: In one aspect, a machine learning system for performing predictive analytics on database wait events is disclosed. The machine learning system includes a processor; a memory; and one or more modules stored in the memory and executable by a processor to perform operations including: receive database wait event data indicative wait events associated with database calls running on a monitored database; receive database performance data indicative of performance of the monitored database; correlate the received database wait event data with the received database performance data to obtain a correlation result; predict a performance issue with the monitored database based on the correlation result; and provide a user interface to display the predicted performance issue.

Abstract: An interface is provided for a user to create a custom dashboard for providing application performance data. The dashboard may be created from one or more widgets, such as graphs, charts, and other display components, and each widget may be individually configured with parameters. The dashboard may be configured to display data for one or more particular transactions, transaction types, or transactions that meet specified criteria. Once created, the dashboard may be shared through a website URL, e-mail, or other method.

Abstract: A system monitors asynchronous transactions over a different number of threads by capturing data and tracking transitions in the particular framework. Once an asynchronous method is called, the transition framework may be tracked while executing a asynchronous method call. Within a .NET framework, monitoring may include tracking a task object return, continuation method calls at the completion of a method, and tracking the continuation method as it executes other code. The asynchronous method may then be correlated within a business transaction using the returned task object data.

Abstract: A system uses agents to monitor a distributed business transaction as well as monitor changes in software configuration. An agent may detect a file load, such a class load, obtain portions of the file such as functions, and perform a hash on the byte code functions. A hash tree may then be constructed and compared to previous states of the system. The hash tree may be generated, for example, at each file loading detected, so that system states can be compared. Differences in hash trees are detected and the changes are reported to an administrator of the system that provides the distrusted business transaction.

Abstract: In one aspect, a method for metric payloads ingestion and playback is disclosed. The method includes receiving time series of metric payloads for a plurality of performance metrics indicating performance of a node or machine and storing the received time series of metric payloads in a payload tracking table of a database. The storing includes storing the received time series of metric payloads in different layers and partitioned regions of the payload tracking table. The layers represent time ranges corresponding to time points when the time series of metric payloads are received. The partitioned regions are assigned to received certain ones of the received time series of metric payloads. The method includes replaying the stored time series of metric payloads from a select one or more of the partitioned region or layer or both.

Abstract: In one aspect, a system for distributed consistent hash backed time rollup of performance metric data is disclosed. The system includes a plurality of collectors configured to receive, time series metrics data for a plurality of performance metrics from one or more agents instrumented into monitored applications; a plurality of aggregators communicatively connected to the collectors and configured to aggregate the received time series metric data for the plurality of performance metrics, wherein each aggregator is assigned to aggregate all received time series metrics data for one or more of the plurality of performance metrics; and a coordinator communicatively connected to the plurality of collectors and plurality of aggregators and configured to provide collectors with information on availability of the plurality of aggregators.

Abstract: In one aspect, a system for pre-fetching performance data in a monitored environment is disclosed. The system can include a processor; a memory; and one or more modules stored in the memory. The one or more modules are executable by the processor to perform operations including: record queries that request for application performance data with latencies longer than a threshold; learn access patterns in the recorded queries with latencies longer than the threshold; pre-fetch and cache the application performance data requested by the recorded queries before the same recorded queries are requested next time; and provide the pre-fetched application performance data from the cache when the same recorded queries are requested next time.

Abstract: Instead of processing a query as-is, the query is chunked or broken down into a sequence of smaller chunked queries and the chunked results of those smaller queries are streamed back to the requester. Chunking the query and streaming the chunked results can substantially decrease the user's time to value when running a query by returning some immediate results for display which are refined and eventually converge on the full results as each chunked query runs.

Abstract: The disclosed technology includes ranking entities in real-time to show the relative importance of those entities. The ranking is based on attributes of the entities that vary in real-time. An example of an entity is a process (e.g., an executing computer program) and the associated attributes can include the process' current CPU memory consumption. While the process runs, its CPU and memory consumption vary in real-time.

Abstract: The present technology utilizes agents to monitor and report data from Java virtual machines (JVM) to a controller as part of application performance monitoring. When a JVM is loaded, code defining an interface for agents is loaded as well. A determination may be made as to whether the loaded agent implements the interface defined at the JVM. If the loaded agent does not implement the interface, for example if it is missing one or more methods defined by the interface, the agent class may be modified to define the missing methods. The modification to the agent class may be made after compilation but before the class is loaded into the JVM.

Abstract: A method, an apparatus, and a computer program product which capture and use analytics data relating to the internal activity of software programs executing in a message-passing runtime environment, such as that provided by Objective-C. The invention exploits the well documented interfaces of these environments together with their dynamic runtime capabilities to insert data collection and analysis code into an application without modification of the target application.