International Business Machines Corporation

Kyndryl, Inc.

Kalpesh Sharma

Albee Jhoney

Mahantesh Meti

Nalini M

Veeresh Bushetti

Hariharan N Venkitachalam

Muniyandi Perumal Thevar

Shaleen Tongia

Avinash Chandra

Prasanna Holla

A computer-implemented method, in accordance with one embodiment, includes receiving a taxonomy specifying entities of a business service and levels of said entities. Time series data about the entities is collected and stored. Impactor propagation paths between entities is identified. A territory of a health impact of each entity is also identified. A health score for each of the entities, considering impacts on a health of the entity by at least one other entity, is computed based on the data, the propagation paths, and the territories of the entities. At least one of the health scores is output.

Service health assessment

A computer-implemented method, in accordance with one embodiment, includes collecting data relating to development of a software product, the collected data including a plurality of different types of data relating to the development of the software product. A portion of the collected data is selected based on a characteristic of an intended user, the portion of the collected data including a plurality of the types of data. The selected portion of the collected data is transformed into data visualizations representing the data, the different types of the data having different data visualizations relative to one another. The data visualizations are output in a single visual representation for display to the intended user.

Generation of data visualizations on a single visual representation

A computer-implemented method, in accordance with one aspect of the present invention, includes collecting data existing in a development system that relates to the code change request, in response to receiving a code change request to merge new code with existing code. Factors from the collected data are computed for assessing a risk of promoting the new code, the factors including at least: a developer information factor, a developer availability factor, and an environment health analysis factor. The factors are processed to compute a confidence score for the code change request. If the confidence score is in a first predefined range, the new code corresponding to the code change request is promoted for merging with the existing code, without human intervention. If the confidence score is in a second predefined range, an indication that human intervention is needed before promoting the code is output.

Code change request management and human gate free deployment based on data collected from a development system

An adaptive log system and method may include calculating a complexity of the change set, comparing a current log message with a previous log message created as a result of the test operation during a previous run, to determine a log difference between the current log message and the previous log message, determining a module sensitivity for each module of the change set, identifying a trust level of a developer of the change set, dynamically adjusting log level settings, and analyzing a serviceability of the change set made to the continuous delivery pipeline based on: (i) the complexity of the change set, (ii) the log difference, (iii) the module sensitivity of each module of the change set, and (iv) the trust level of the developer, wherein, as a function of the analyzing, the sufficiency of log messages for each module of the change set is determined.

Intelligent generation of log messages by a SAAS offering in a continuous pipeline

A method, system, and computer program product to integrate service management tools with enterprise product development tools to determine Ops readiness scores. The method may include receiving one or more logs of bug tracking information from a client module, where the bug tracking information corresponds to one or more applications with one or more production bugs. The method may also include compiling the one or more logs. The method may also include receiving reports of at least Ops issues of the one or more applications and latest requirements of the one or more applications from a company module, where the latest requirements include at least current deliverables. The method may also include mapping the compiled one or more logs and the reports. The method may also include generating an Ops readiness score for each of the current deliverables, based on the mapping.

Prevent application outages through operations driven development

A method for generating location-based advertisement includes receiving a selection of a first radio station from a user of a mobile device, receiving an electronic program guide from the first radio station including a plurality of advertisement time slots, where each advertisement time slot in the plurality of advertisement time slots includes an advertisement sequence for a first advertisement content, receiving a second advertisement content from a second radio station located in a geographic location matching a real-time geographic location of the user as determined by a location-based service of the mobile device, substituting the first advertisement content in the advertisement sequence of one of the plurality of advertisement time slots with the second advertisement content from the second radio station, and broadcasting the second advertisement content to the user via the mobile device.

Location-based advertising using hybrid radio

Intelligent generation of log messages by a SaaS offering in a continuous pipeline

A method, computer program product, and system for risk monitoring of continuous software delivery include a first plurality of test data. The first plurality of test data is associated with one or more software components. In response to receiving a changelog, a change in the received plurality of test data is determined. A risk profile for the one or more software components is generated, in response to receiving the first plurality of test data and the received changelog. A component code graph is generated, based on the risk profile associated with the one or more software components and a risk value associated with the generated risk profile is calculated, based on the component code graph.

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Bengaluru, India

Kalpesh Sharma