Abstract: A global transaction system receives a transaction request for a plurality of database services of microservices. The global transaction system receives a plurality of local commit decisions of local commit requests from local transaction managers of the database services of the microservices. The local commit request corresponds to the transaction request for each database. The global transaction system generates a physical commit request to each of the local transaction managers based on the local commit decisions and a global commit decision. Each local transaction manager submits the physical commit request to each database server of the database services corresponding to the transaction request.

Abstract: Software defined storage service (SDS) provides users with remote data volumes spread across multiple storage nodes across multiple failure domains. A distributed volume may be spread across replicas (e.g., failure domains), each replica having a number of partitions stored on storage nodes associated with a particular failure domain. In the event of a node failure, a partition stored on the failed node may be dynamically moved and remapped to another node in the same failure domain or within another failure domain that is different from a failure domain that includes a partition that is complementary to the partition stored on the failed node. The partition move and remapping may be transparent to a user. A partition move may occur while a distributed volume is in use by a client device or in an idle (e.g., offline) mode.

Abstract: Software defined storage service (SDS) provides users with remote data volumes spread across multiple storage nodes across multiple failure domains. A distributed volume may be spread across replicas (e.g., failure domains), each replica having a number of partitions stored on storage nodes associated with a particular failure domain. In the event of a node failure, a partition stored on the failed node may be dynamically moved and remapped to another node in the same failure domain or within another failure domain that is different from a failure domain that includes a partition that is complementary to the partition stored on the failed node. The partition move and remapping may be transparent to a user. A partition move may occur while a distributed volume is in use by a client device or in an idle (e.g., offline) mode.

Abstract: A leader control plane node of a set of control plane nodes of a node cluster, may receive a request to store data in a distributed storage system including a set of access manager nodes. The leader control plane node may generate cache data identifying an instruction from the leader control plane node to one or more access manager nodes managed by the leader control plane node of the plurality of access manager nodes, the instruction instructing the one or more access manager nodes to store the data indicated in the request. The leader control plane node may then transmit a replication instruction to one or more follower control plane nodes of the plurality of control plane nodes to replicate the cache data in a respective cache of the one or more follower control plane nodes.

Abstract: Defects are identified in a pre-production version of an application. Input used to test the pre-production version is derived from input received by a production version of the application. Input to the production version may be selectively filtered and/or amplified before being provided as test input to the pre-production version. In this way, the makeup and rate of the test input can be controlled while maintaining the character, pattern, and unpredictable nature of real-world input. Defects may be identified when the test input causes the pre-production version to crash, hang, write to an error log, or otherwise manifest or report a malfunction. In addition to identifying defects, filtered and amplified input may also be used to perform regression testing, load testing, performance testing, etc.

Abstract: Defects are identified in a pre-production version of an application. Input used to test the pre-production version is derived from input received by a production version of the application. Input to the production version may be selectively filtered and/or amplified before being provided as test input to the pre-production version. In this way, the makeup and rate of the test input can be controlled while maintaining the character, pattern, and unpredictable nature of real-world input. Defects may be identified when the test input causes the pre-production version to crash, hang, write to an error log, or otherwise manifest or report a malfunction. In addition to identifying defects, filtered and amplified input may also be used to perform regression testing, load testing, performance testing, etc.

Abstract: A replicated key-value store is implemented using a “last-write-wins” consensus protocol. To improve throughput and latency in cross-data-center configurations, a system deploys a cross-cluster, learner-only member to a cluster of nodes (e.g., a data center). The cross-cluster, learner-only member submits key-values received at local leader members to remote clusters. Conflicts between the key-values and initial values at the remote clusters are resolved using a “last-write-wins” consensus protocol.

Abstract: A global transaction system receives a transaction request for a plurality of database services of microservices. The global transaction system receives a plurality of local commit decisions of local commit requests from local transaction managers of the database services of the microservices. The local commit request corresponds to the transaction request for each database. The global transaction system generates a physical commit request to each of the local transaction managers based on the local commit decisions and a global commit decision. Each local transaction manager submits the physical commit request to each database server of the database services corresponding to the transaction request.

Abstract: A replicated key-value store is implemented using a “last-write-wins” consensus protocol. To improve throughput and latency in cross-data-center configurations, a system deploys a cross-cluster, learner-only member to a cluster of nodes (e.g., a data center). The cross-cluster, learner-only member submits key-values received at local leader members to remote clusters. Conflicts between the key-values and initial values at the remote clusters are resolved using a “last-write-wins” consensus protocol.

Abstract: In an example embodiment, clusters of nodes in a network are monitored. Then the monitored data may be stored in an open time-series database. Data from the open time-series database is collected and labeled it as training data. Then a model is built through machine learning using the training data. Additional data is retrieved from the open time-series database. The additional data is left as unlabeled. Anomalies in the unlabeled data are computed using the model, producing prediction outcomes and metrics. Finally, the prediction outcomes and the network.

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: A method to optimize calls to a service by components of an application running on an application server is provided. The method includes receiving a first call and a second call, the first call made to a service by a first one of a plurality of components included in the application, and the second call made to the service by a second one of the plurality of components; selecting one of a plurality of optimizations, the plurality of optimizations including orchestrating the first call and the second call into a third call to the service; and, in response to the selecting of the orchestrating of the first call and the second call into the third call as the one of the plurality of optimizations, orchestrating the first call and the second call into the third call.

Abstract: A method to optimize calls to a service by components of an application running on an application server is provided. The method includes receiving a first call and a second call, the first call made to a service by a first one of a plurality of components included in the application, and the second call made to the service by a second one of the plurality of components; selecting one of a plurality of optimizations, the plurality of optimizations including orchestrating the first call and the second call into a third call to the service; and, in response to the selecting of the orchestrating of the first call and the second call into the third call as the one of the plurality of optimizations, orchestrating the first call and the second call into the third call.

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 an example embodiment, clusters of nodes in a network are monitored. Then the monitored data may be stored in an open time-series database. Data from the open time-series database is collected and labeled it as training data. Then a model is built through machine learning using the training data. Additional data is retrieved from the open time-series database. The additional data is left as unlabeled. Anomalies in the unlabeled data are computed using the model, producing prediction outcomes and metrics. Finally, the prediction outcomes and metrics are used to move or reduce workloads from problematic clusters of nodes in the network.

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: 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 one embodiment, the invention provide a method comprising: generating a user interface to allow a user to make an input relating to a first component of an application; and if the input is related to an artifact, then presenting selected information about the artifact to the user. In another embodiment, invention provides a method comprising: collecting information about artifacts referenced by a statement in a first component of an application; and outputting run-time data for each artifact referenced by the statement to facilitate debugging of the first component.

Abstract: A method to optimize calls to a service by components of an application running on an application server is provided. The method includes receiving a first call and a second call, the first call made to a service by a first one of a plurality of components included in the application, and the second call made to the service by a second one of the plurality of components; selecting one of a plurality of optimizations, the plurality of optimizations including orchestrating the first call and the second call into a third call to the service; and, in response to the selecting of the orchestrating of the first call and the second call into the third call as the one of the plurality of optimizations, orchestrating the first call and the second call into the third call.

Abstract: A web page development application provides simultaneous display of a browser view and the corresponding descriptor language source view. The application provides graphical editing of the browser view. The corresponding descriptor language source view is automatically generated so as to be consistent with the browser view upon prompting by the user. The web page development application allows separate editing of the browser view and corresponding descriptor language source view and cross-synchronization such that changes to one view will automatically update the other view when prompted by the user.