Amadeus S.a.s.

Vincent Boulineau

Jacques Bonaud

Michel Demazeau

David Renaudie

Serge Beuzit

Jean Michel Collomb

Nicolas Isch

Ahmed Oulabas

Guillaume Deacken Owanssango

Mohand Arezki Kessaci

A method of determining a primary storage location for a data record in a distributed system comprising a plurality of data stores physically located in corresponding geographic locations, includes initialising a machine learning mapping model using topology information of the distributed system, and determining a set of training feature vectors derived from metadata values associated with prior location requests. The model is trained using the training feature vectors and a corresponding set of target primary storage locations. A location request that includes a plurality of metadata values and is associated with a data record is received, and the metadata values are processed to determine a prediction feature vector comprising a plurality of prediction feature values. The model is executed using the prediction feature vector to identify one data store of the plurality of data stores as the primary storage location for the data record associated with the location request.

Machine learning systems and methods for data placement in distributed storage

A computer-implemented method for testing a functionality of a computing platform, the computing platform comprising a first microservice, the method comprising: receiving, by an injector microservice, a test configuration file; determining from the test configuration file: a test input message; a test input communication mechanism; and a test output communication mechanism. The method further comprises: generating a test identifier for identifying that a message is being used for testing purposes; transmitting, by the injector microservice, the test input message to the first microservice using the test input communication mechanism, wherein the test input message comprises the test identifier; identifying, by the injector microservice, an output message transmitted via the test output communication mechanism that comprises the test identifier; and recording, by the injector microservice, the output message comprising the test identifier.

Method and device for testing microservice-based computing platforms

The present invention describes a system and a method for dynamically optimising the computing resources allocated to a client application in different data regions of one or more service providers. A number of monitoring modules are provided in each data regions, which are configured to collect operational information from each data region, which is communicated to the other data regions. As such, all data regions are aware of the operational environment of the other data regions.

Method and a system for managing the computing resources in data regions

A method and a system are provided for optimising Virtual Machine (VM) instances () of a Virtual Machine (VM) cluster () in a cloud computing platform () to avoid the use of VM instances () with degraded performance. The optimisation process of the VM instances () comprises the steps of identifying and optimising VM instances () with degraded performance in VM clusters (). The performance of the deficient VM instances may be optimised by requesting for each deficient VM instance () a corresponding replacement VM instance () to be created by the IaaS (), and accordingly maintain the best performing VM instance from each pair of deficient and replacement VM instances ().

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Antibes, France

Vincent Boulineau