Microsoft Technology Licensing, LLC

Idx Investment Corporation

Adi Eldar

Roy Ben Ofer

Yehezkel Shraga Resheff

Laurence Keselbrener

Benjamin Mark Zhitomirsky

Shahar Davidovich

Methods, systems, apparatuses, and computer-readable storage mediums described herein are configured to automatically allocate or deallocate computing resources based on a prediction of performance metrics behavior. For instance, the historical behavior of compute metrics (or a time series obtained therefor) is analyzed to detect a seasonality (i.e., a seasonal pattern) and a trend therefor. A prediction of the metrics' behavior for a future time frame is determined based on the seasonality and the trend. Based on the prediction, computing resources are allocated or deallocated at or prior to the future time frame occurring. For example, if a prediction is made that a particular metric will increase, additional compute resources are allocated to handle the increase ahead of the predicted metric increase. If a prediction is made that a particular metric will decrease, compute resources are deallocated at the time the metric is predicted to decrease.

Computing resource autoscaling based on predicted metric behavior

Dominant sequences that are representative of logged events can be artificially created. Initially, a graph comprising multiple nodes and edges between pairs of nodes is generated from logged information. The weights, or values, associated with edges are incremented as the log data reveals a temporal relationship between two nodes. Subsequently, a set of candidate trajectories, with each candidate trajectory representing a sequence of events, are generated by repeatedly traversing the generated graph in a random manner by commencing at randomly selected nodes and then proceeding in a random manner to subsequent nodes in accordance with the edge values, for a random quantity of steps. The candidate trajectories are filtered to eliminate those that are impossible or improbable based on a comparison between individual candidate trajectories and the quantity of occurrences within the logs. Scoring is based both on a quantity of occurrences as well as a quantity of steps.

Artificial creation of dominant sequences that are representative of logged events

Embodiments relate to efficiently performing an inner join on segments from a data source, where the segments have wildcards in join columns. An algorithm for an inner segment join operator may build a location map that describes locations, by segment and column, of values in the join columns of rows in the segments. A map of wildcard locations, by segment and column, may also be constructed. The location map may be supplemented with information from the wildcard map. The data source is scanned and contents of rows in the data source are queried against the location map to join rows with segments that match due to either matching values or wildcard presence. A user interface may be provided to facilitate construction of joins using the inner segment join operator.

Join operation and interface for wildcards

An image publishing system provides a distribution mechanism whereby images are forwarded automatically to users in accordance with a set of publication rules. The rules determine which images are to be sent to which users. The images are forwarded to users as they become available on an image archive storage device. This overcomes the requirement of users having to manually request the transmission of each individual image they would like to view. Progressive image streaming techniques employing compression are used to transmit images in encoded layers of increasing accuracy and quality. Means is also provided permitting users to view any image queued for transmission at a publication server, regardless of how much of the image has been received by a client computer. This allows images whose data transmission has not even begun yet to be viewed by a user. A user interrupts the normal background process at any time and requests to view a particular image. If the required data is not found locally, it is requested form the publication server and given high priority. The requested data is received, decoded and immediately displayed to the user.

Growing community of inventors

Kiryat-Ono, Israel

Adi Eldar