Red Hat, Inc.

International Business Machines Corporation

Benjamin Michael Parees

Clayton Palmer Coleman

Cesar Augusto Wong

Daniel McPherson

Kevin David Himberger

David Michael Eads

Guy Laden

Gregory Chockler

Michal Fojtik

Gabriel Garcia Montero

Nitin Gaur

Douglas Berg

Dustin K Amrhein

Jake Palmer

Jordan Thomas Liggitt

Ymir Vigfusson

Derek W Carr

David Michael Enyeart

Latha Sivakumar

Lalatendu Shishusankar Mohanty

Vadim Pavlovich Rutkovsky

Luis Eduardo Guillen-Sanchez

Rodolfo Henrique Carvalho

Dan McBryde Willey

William Trevor King

Phillip J Rau

Martin Nagy

Scott C Dodson

Douglas Richard Hellmann

Yoav Tock

Roie Melamed

James R Thorpe

Prasad Rajendra Vishnubhotla

Eli Luboshitz

Stephen Tweedie

Processing logic may obtain a version of software that is running on a client. Processing logic may obtain a second version of the software which is an update to the version of software that is running on the client. Processing logic may send the second version to the client with one or more conditions that are associated with the second version, for the client to determine whether or not to update to the second version.

Conditional update recommendations based on local system state

Processing logic may obtain health data from each of a plurality of clients. The health data includes attributes of a respective one of the plurality of clients, a health status of the respective one of the plurality of clients, and a software version of the respective one of the plurality of clients. Processing logic may determine a conditional risk that is associated with at least one of the attributes and the software version, in view of the health data, and store the conditional risk in memory. Processing logic can make the conditional risk, which includes the attributes and the software version, available to a client.

Automated conditional update

Dynamic container-based application resource tuning and resizing is disclosed. One or more container resource constraint values associated with a first container are accessed. One or more application resource constraint values based on the one or more container resource constraint values are determined. A first application execution of an application is initiated in the first container. The one or more application resource constraint values are provided to the first application execution. An analysis of a plurality of resource usage metrics generated during the first application execution of the application is performed. Each resource usage metric quantifies a use of a corresponding resource associated with the first container during the first application execution. One or more optimized container resource constraint values are determined based on the analysis.

Dynamic container-based application resource tuning and resizing

Application permissions can be set in a cloud computing environment based on a user's authorization level in the cloud computing environment. For example, a system can determine that a user has a particular authorization level in a cloud computing environment. The system can determine that the user is to have particular permissions for a continuous integration tool by mapping the particular authorization level to the particular permissions. The system can then set a permission setting for the continuous integration tool to limit the user to the particular permissions.

Setting application permissions in a cloud computing environment

Implementations provide for container clustering in a container-based architecture. A method of the disclosure includes generating by a processing device executing a container deploying an instance of an application image, a domain name server (DNS) query to request identification of other containers in a container cluster. The other containers deploy other instances of the application image. The method also includes in responsive to the DNS query, receiving the identification of each of the other containers in the container cluster. The method further includes configuring, without manual intervention, the container as a member of the container cluster in view of the identification of each of the other containers.

Container clustering in a container-based architecture

A pipeline object recommendation system may be configured to analyze a software development project for development attributes. The system may then generate a pipeline object corresponding to the development project based on the plurality of development attributes. The system may then present the pipeline object.

Developing workflow-based recommendations based on organizational patterns and observed behavior

Managing resources used during a development pipeline. A method of the disclosure includes analyzing historical resource usage of an application development system during different stages of a development pipeline for an application. The application development system includes a set of computing resources. The method also includes determining a current resource usage for a current stage of the development pipeline for the application. The method further includes determining an estimated resource usage for a later stage of the development pipeline for the application based on one or more of the current resource usage or the historical resource usage. The method further includes configuring the set of computing resources of the application development system for the later stage of the development pipeline based on the estimated resource usage.

Managing resources used during a development pipeline

Embodiments of the invention provide a method, system and computer program product for optimized continuous query processing in an in memory data grid (IMDG). In an embodiment of the invention, a method for optimized continuous query processing in an IMDG includes receiving a request to add an object to an IMDG. The method also includes evaluating a continuous query upon the object in order to produce a result. The method yet further includes adding an attribute to the object referencing the continuous query and assigning a value to the attribute of the result. The method even yet further includes inserting the object with the attribute into the IMDG. Finally, the method includes returning the value of the attribute in lieu of repeating an evaluation of the continuous query in response to receiving a request to repeat an evaluation of the continuous query in respect to the object.

Optimizing continuous query operations in an in memory data grid (IMDG)

The present disclosure provides new methods and systems for managing applications in a deployment pipeline. For example, a policy of a first environment and a policy of a second environment are detected. A request to move an application from the first environment to the second environment is received. Configuration data of the first environment is incompatible with the second environment. A configuration data set associated with the application is detected and includes various pieces of configuration data. Based on the various policies and the configuration data set, actions to be implemented in the configuration data set are determined, including actions associated with each piece of configuration data. The actions are implemented on the pieces of configuration data to obtain a reconfigured configuration data set that includes different configuration data than that of the first environment. The application and the reconfigured configuration data set are moved to the second environment.

Application management in an application deployment pipeline

Usage instrumented workload scheduling is disclosed. For example, a plurality of nodes host first and second pluralities of guests. An orchestrator includes a usage monitor, a workload classifier, and a scheduler, and executes on a processor to track, by the usage monitor, respective usage patterns of a plurality of accounts including a first account. A first workload is received from the first account, which has a first account factor based on the respective usage patterns of the first account. The first workload is assigned by the workload classifier to a first workload type of a plurality of workload types. The first workload is assigned by the scheduler to the first plurality of guests based on the first account factor and the first workload type.

Usage instrumented workload scheduling

Automatic parameter value generation is disclosed. It is determined that a parameter value generation trigger associated with a parameter has occurred. A parameter value in accordance with a format of the parameter value is obtained. At least one location associated with a first component to which the parameter value is to be communicated is determined. The parameter value is communicated to the at least one location, and a parameter value refresh policy associated with the first component is determined.

Automatic parameter value generation

Implementations provide for an add-on image framework for a Platform-as-a-Service (PaaS) system. A method of the disclosure includes launching a build container for a build process based on a base image of an application of a multi-tenant Platform-as-a-Service (PaaS) system. The base image provides a core functionality of the application. The method also includes providing a source code for the application to the build container. The method further includes extracting content from an add-on image and assembling an application image using the base image, the source code and the extracted add-on image content in the build container.

Add-on image for a platform-as-a-service system

Growing community of inventors

Durham, NC, United States of America

Benjamin Michael Parees