Abstract: An intelligent conflict detection system. The system provides semantic expression of edits and history-aware conflict detection in a large-scale service allowing multiple users to simultaneously work with the same document, which may result in conflicting edits. When submitted, changes to a version of a document are compared to all versions of the document created since the document was sourced. Edits to documents are expressed as intents describing the changes in terms of an action and object of that action based on a characteristic of the data being edited. Comparing the intent of current edits against the historical intent of the edits made in prior versions originating from the same source document allows the system to intelligently assess whether the edits are in conflict. History-aware semantic analysis results in users being prompted less frequently to resolve conflicts, which improves the user experience.

Abstract: A scalable eventual consistency system. The system uses logical document journaling to provide eventual consistency across partitions in a large-scale service. The system allows for transactional edits to massively interconnected graphs of documents through parallelization without sacrificing linear scalability. The system separates the authority for edits from the replicated storage allowing efficient transactions and linear scalability. All document writes are written to document-specific partitions in a journal where they are queued until the changes are propagated to view-based partitions of a store. By continually checking the journal and attempting to replicate any pending document writes to the store, the system provides eventual consistency without complicated synchronization mechanisms.

Abstract: An intelligent conflict detection system. The system provides semantic expression of edits and history-aware conflict detection in a large-scale service allowing multiple users to simultaneously work with the same document, which may result in conflicting edits. When submitted, changes to a version of a document are compared to all versions of the document created since the document was sourced. Edits to documents are expressed as intents describing the changes in terms of an action and object of that action based on a characteristic of the data being edited. Comparing the intent of current edits against the historical intent of the edits made in prior versions originating from the same source document allows the system to intelligently assess whether the edits are in conflict. History-aware semantic analysis results in users being prompted less frequently to resolve conflicts, which improves the user experience.

Abstract: An intelligent conflict detection system. The system provides semantic expression of edits and history-aware conflict detection in a large-scale service allowing multiple users to simultaneously work with the same document, which may result in conflicting edits. When submitted, changes to a version of a document are compared to all versions of the document created since the document was sourced. Edits to documents are expressed as intents describing the changes in terms of an action and object of that action based on a characteristic of the data being edited. Comparing the intent of current edits against the historical intent of the edits made in prior versions originating from the same source document allows the system to intelligently assess whether the edits are in conflict. History-aware semantic analysis results in users being prompted less frequently to resolve conflicts, which improves the user experience.

Abstract: An intelligent conflict detection system. The system provides semantic expression of edits and history-aware conflict detection in a large-scale service allowing multiple users to simultaneously work with the same document, which may result in conflicting edits. When submitted, changes to a version of a document are compared to all versions of the document created since the document was sourced. Edits to documents are expressed as intents describing the changes in terms of an action and object of that action based on a characteristic of the data being edited. Comparing the intent of current edits against the historical intent of the edits made in prior versions originating from the same source document allows the system to intelligently assess whether the edits are in conflict. History-aware semantic analysis results in users being prompted less frequently to resolve conflicts, which improves the user experience.

Abstract: A scalable eventual consistency system. The system uses logical document journaling to provide eventual consistency across partitions in a large-scale service. The system allows for transactional edits to massively interconnected graphs of documents documents through parallelization without sacrificing linear scalability. The system separates the authority for edits from the replicated storage allowing efficient transactions and linear scalability. All document writes are written to document-specific partitions in a journal where they are queued until the changes are propagated to view-based partitions of a store. By continually checking the journal and attempting to replicate any pending document writes to the store, the system provides eventual consistency without complicated synchronization mechanisms.

Abstract: A fault monitoring, detection and analysis system obtains data (e.g. online service facts) from different data sources. Many times the data obtained from the different data sources is in different formats. The data is classified (e.g. into error, performance and usage events/facts) based on user configured multi-dimensional (time, topology, functional area) filter criteria. The data from the different data sources is normalized into a standard format and stored. The data may also be grouped and duplicates may be removed before and/or after the normalized data is stored. Analysis is performed on the normalized data. For example, the analysis may monitor for expected events, unexpected events, detect abnormal behavior of the system, and the like. Different users may submit different jobs to the system to obtain data from the data store. A reporting service exposes one or more views of the data and/or the analysis of the data.