International Business Machines Corporation

Ram Ravishankar

Harish Bharti

Ajay Mohindra

Sreekanth Ramakrishna Iyer

Nianjun Zhou

Sandeep Sukhija

Raman Harishankar

Rohit Ranchal

Rakesh Shinde

Sham Madhukar Vaidya

Grigorij Kaplan

Paul Van Riel

Alberto Eduardo De Queiroz Dias

Datasets can be synchronized across cloud-based computer environments using computer systems. A data map can be generated for source datasets for a plurality of computing environments, respectively, and an activation function can be determined based on the data map, for simultaneously activating a new dataset of a source system from one of the plurality of computing environments. A generation ID (identification) can be shared from the source system with one or more computing environments of the plurality of the computing environments, in response to receiving the activation function. The new dataset of the source system can be replicated across the one or more computing environments. A data synchronization trigger can be activated, using a synchronization coordinator module of the computer, and the data synchronization can be completed across the plurality of computing environments.

Synchronized activation of datasets in multicloud computing environment

A method includes: determining, by a computing device, transactions of a monolithic application; ranking, by the computing device, the transactions using predefined rules; selecting, by the computing device, a candidate transaction from the ranked list; determining, by the computing device, lines of application code of the monolithic application associated with the candidate transaction; mapping, by the computing device, respective ones of the determined lines of application code to a first operation and a second operation, wherein the first operation and the second operation are different types of operation; and defining, by the computing device, a target state design based on CQRS (Command Query Responsibility Segregation), the target state design including a first microservice that performs the first operation and a second microservice that performs the second operation.

Transforming select portions of a monolithic application to microservices

Similar to other Cloud Service, Solution as Services over Cloud, as single tenant technology, also requires support of agility and flexibility as a fundamental feature of Cloud computing. Different from other Cloud services, the agility and flexibility typically are not triggered by the typical performance metrics, but at the business level of metrics. A causality analysis method, system, and non-transitory computer readable medium using a causal graph depicting relationships among observable primitive metrics from infrastructure, middleware, and business metrics and latent business metrics of an application, include identifying a metric value resulting from measuring the system and application metrics, determining an impact of the measurement of the metrics on the business metrics associated with the measurable metrics in the causal graph, and determining an action to take with respect to the impact on the business metric based on the pre-defined business policies.

System, method and recording medium for causality analysis for auto-scaling and auto-configuration

When a service is requested at a platform in a collaborative services environment, a service orchestration engine accesses a service definition from a repository and schedules a number of tasks at a number of end points in accordance with a number of end point profiles and a number of policies associated with the end points.

Service oriented collaboration

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Irvine, CA, United States of America

Ram Ravishankar