International Business Machines Corporation

Peng Chen

Jing Min Xu

Lin Y Yang

Fan Jing Meng

Xiao Xun Zhang

Yuan Wang

Hai Shan Wu

Tian Cheng Liu

Girish Bhimrao Chafle

Bao Hua Yang

Feng Wang

Tong Tm Jia

Rubber band braider

A method, system, and computer program product, include extracting information related to one or more processes of one or more applications running on a virtual machine from a memory of the virtual machine, building at least one first application signature based on the extracted information, and identifying the one or more applications running on the virtual machine by matching the at least one first application signature with one or more second application signatures previously stored.

Method, system, and computer program product for application identification in a cloud platform

A computing device receives template files and parameters associated with the template files, where the template files comprise scripts, and where the associated parameters comprise a user preference associated with an efficiency of the image. The computing device may determine dependencies between layers of the scripts based on a unified image model. The unified image model may generate a logic tree that includes nodes, where each one of the nodes represents each one of the layers of the scripts. The computing device may generate an efficient logic tree based on the logic tree and the user preference of a generated image model. The generated image model may generates the efficient logic tree by changing the dependencies of the nodes in the logic tree based on the user preference. Based on the generated efficient logic tree the computing device may build the image.

Self-adaptive building container images

Embodiments are directed to a computer implemented method for generating a drift detector. The method includes generating, using a processor system, drift cases based at least in part on known drift set data of a computer system. The method further includes injecting, using the processor system, the drift cases into the computer system to generate a first data set. The method further includes applying, using the processor system, cleaning rules to the first data set to reduce a size of the first data set and generate a cleaned data set. The method further includes extracting one or more features of the cleaned data set. The method further includes normalizing the extracted one or more features of the cleaned data set. The method further includes training a machine learning system using the extracted and normalized one or more features of the cleaned data, wherein an output of the machine learning system comprises the drift detector.

Learning-based drift detection tool

Techniques for log-based diagnosis for declarative-deployed applications can comprise: based on a labeled deployment declaration, classifying, by a device operatively coupled to a processor, a runtime log associated with an application, resulting in a classified runtime log. Techniques can also comprise: based on the classified runtime log, training, by the device, an aggregation model to represent a defined state of the application.

Log-based diagnosis for declarative-deployed applications

A method or apparatus for monitoring a system by detecting misbehaving components in the system is presented. A computing device receives historical data points based on a set of monitored signals of a system. The system has components that are monitored through the set of monitored signals. For each monitored component, the computing device performs unsupervised machine learning based on the historical data points to identify expected states and state transitions for the component. The computing device identifies one or more steady components based on the identified states of the monitored components. The computing device also receives real-time data points based on monitoring the set of signals from the system. For each identified steady component, the computing device examines the received real-time data points for deviation from the expected state and state transitions of the steady component. The computing device reports anomaly in the system based on the detected deviations.

Detection of misbehaving components for large scale distributed systems

A computer-implemented method obtains an action sequence that includes a plurality of actions executed on behalf of a plurality of users for achieving at least one goal. An event sequence that includes a plurality of events associated with types of the plurality of actions is generated from the obtained action sequence. An association model based on the generated event sequence is determined. The association model defines a chronological relationship among events associated with the at least one goal.

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Beijing, China

Peng Chen