Abstract:
A data storage system may be configured to allocate replica-sets in a balanced manner and mark some of these balanced replica-sets as being spares. As one or more drives or machines fail, the data storage system may move all copies of an affected replica-set to a marked spare replica-set and mark the affected replica-set as being inactive or invalid. As the failed drives are replaced, the data storage system may reconfigure those inactive replica-sets and use them as new spares. The data storage system may implement a coordinator module that handles the balancing and allocation of spares within a sub-cluster. The coordinator may also reallocate entire replica-sets across sub-clusters to maintain balance at the cluster level.
Abstract:
Methods and systems for simulating a search, for the purpose of evaluating one or more scoring functions used in ordering item listings for presentation in a search results page are described. Consistent with some embodiments, a simulation platform includes a real-time simulation module that receives search result sets for search queries that result in the conclusion of a transaction. The result set is then processed by the simulation platform with one or more test scoring functions, such that the resulting position of the item listing that has resulted in the transaction can be compared with the actual position at which the item listing was displayed in the actual search results. For each test scoring function, an average rank shift metric is determined, and displayed, thereby providing a metric with which to base decisions about which scoring functions to use in the production system.
Abstract:
Systems and methods of cloud deployment optimization are disclosed. In some example embodiments, a method comprises running original instances of an application concurrently on original servers to implement an online service, receiving, by the original instances of the application original requests for one or more functions of the online service, receiving a command to deploy a number of additional instances of the application, transmitting synthetic requests for the function(s) of the online service to one of the original servers according to a predetermined optimization criteria, deploying the number of additional instances of the application on additional servers using a copy of the original instance of the application, and running the deployed additional instances of the application on their corresponding additional servers concurrently with the original instances of the application being run on their corresponding original servers.
Abstract:
A data storage system may be configured to allocate replica-sets in a balanced manner and mark some of these balanced replica-sets as being spares. As one or more drives or machines fail, the data storage system may move all copies of an affected replica-set to a marked spare replica-set and mark the affected replica-set as being inactive or invalid. As the failed drives are replaced, the data storage system may reconfigure those inactive replica-sets and use them as new spares. The data storage system may implement a coordinator module that handles the balancing and allocation of spares within a sub-cluster. The coordinator may also reallocate entire replica-sets across sub-clusters to maintain balance at the cluster level.
Abstract:
In various example embodiments, a system and method for managing a server cluster are provided. An example method may include scheduling a first job on a first node, using a first resource manager, establishing a service for a second resource manager on a second node, wherein the service is allocated node resources of the second node, and attempting to schedule a second job on the first node, using the first resource manager. The method may include preempting the service on the second node, using the second resource manager, in response to the attempt to schedule the second job on the first node, and deallocating the node resources of the second node from the service. The method may include advertising, using a node manager of the first resource manager, available node resources of the second node, and scheduling the second job on the second node, using the first resource manager.
Abstract:
Methods and systems for simulating a search, for the purpose of evaluating one or more scoring functions used in ordering item listings for presentation in a search results page are described. Consistent with some embodiments, a simulation platform includes a real-time simulation module that receives search result sets for search queries that result in the conclusion of a transaction. The result set is then processed by the simulation platform with one or more test scoring functions, such that the resulting position of the item listing that has resulted in the transaction can be compared with the actual position at which the item listing was displayed in the actual search results. For each test scoring function, an average rank shift metric is determined, and displayed, thereby providing a metric with which to base decisions about which scoring functions to use in the production system.
Abstract:
Systems and methods of cloud deployment optimization are disclosed. In some example embodiments, a method comprises running original instances of an application concurrently on original servers to implement an online service, receiving, by the original instances of the application original requests for one or more functions of the online service, receiving a command to deploy a number of additional instances of the application, transmitting synthetic requests for the function(s) of the online service to one of the original servers according to a predetermined optimization criteria, deploying the number of additional instances of the application on additional servers using a copy of the original instance of the application, and running the deployed additional instances of the application on their corresponding additional servers concurrently with the original instances of the application being run on their corresponding original servers.
Abstract:
Systems and methods of cloud deployment optimization are disclosed. In some example embodiments, a method comprises running original instances of an application concurrently on original servers to implement an online service, receiving, by the original instances of the application original requests for one or more functions of the online service, receiving a command to deploy a number of additional instances of the application, transmitting synthetic requests for the function(s) of the online service to one of the original servers according to a predetermined optimization criteria, deploying the number of additional instances of the application on additional servers using a copy of the original instance of the application, and running the deployed additional instances of the application on their corresponding additional servers concurrently with the original instances of the application being run on their corresponding original servers.
Abstract:
A data storage system may be configured to allocate replica-sets in a balanced manner and mark some of these balanced replica-sets as being spares. As one or more drives or machines fail, the data storage system may move all copies of an affected replica-set to a marked spare replica-set and mark the affected replica-set as being inactive or invalid. As the failed drives are replaced, the data storage system may reconfigure those inactive replica-sets and use them as new spares. The data storage system may implement a coordinator module that handles the balancing and allocation of spares within a sub-cluster. The coordinator may also reallocate entire replica-sets across sub-clusters to maintain balance at the cluster level.
Abstract:
Systems and methods of cloud deployment optimization are disclosed. In some example embodiments, a method comprises running original instances of an application concurrently on original servers to implement an online service, receiving, by the original instances of the application original requests for one or more functions of the online service, receiving a command to deploy a number of additional instances of the application, transmitting synthetic requests for the function(s) of the online service to one of the original servers according to a predetermined optimization criteria, deploying the number of additional instances of the application on additional servers using a copy of the original instance of the application, and running the deployed additional instances of the application on their corresponding additional servers concurrently with the original instances of the application being run on their corresponding original servers.