Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: Techniques are described herein to handle situations in which multiple systems can change different copies of the same data item. Optimistic locking and time stamps are used to ensure consistency between the systems without incurring the performance penalties associated with two-phase commit. Specifically, when propagating a change to a data item from a first system to a second system, the second system compares the first system's “pre-update” value of the data item with its current value of the data item. If the pre-update value from the first system does not match the current value in the second system, then a conflict has occurred. Upon detecting a conflict, both systems use timestamps associated with the respective conflicting changes to determine which conflicting change “wins”. The winning change is applied by all systems whose changes did not win.

Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: Techniques a provided for communication graph tracking in multi system operation in heterogeneous database systems, including retrieving two or more database commit logs from two or more corresponding heterogeneous databases. For each of the commit logs, a subset of information is extracted, including a correlation identifier, and event stream entries are produced based on that information and are stored. The event stream entries are then retrieved and event database entries are created based on the event stream entries. A request for a communication graph related to a particular correlation identifier is received and the event database is searched for matching entries. Those entries are used to generate a displayable communication graph for the particular correlation identifier, which is then provided in response to the request.

Abstract: When a particular event record requires a particular service, but that service has failed for the event, an error record that includes an aggregate identifier (AgID) is stored for the event in an error queue. Storing an error record in the error queue causes the service to notify a remediation team to fix the failed event. All events with the AgID in the error record are put on hold and an error record is created for each of these events. The remediation team generates a fixed version of the event record and causes the system to retry the failed service for the event based on the fixed version. If the fixed version of the event is successfully processed, then any other events with the same AgID that have error records in the error queue, are routed in order of enqueue time through the event processor to be handled.

Abstract: Techniques are described herein to handle situations in which multiple systems can change different copies of the same data item. Optimistic locking and time stamps are used to ensure consistency between the systems without incurring the performance penalties associated with two-phase commit. Specifically, when propagation a change to a data item from a first system to a second system, the second system compares the first system's “pre-update” value of the data item with its current value of the data item. If the pre-update value from the first system does not match the current value in the second system, then a conflict has occurred. Upon detecting a conflict, both systems use timestamps associated with the respective conflicting changes to determine which conflicting change “wins”. The winning change is applied by all systems whose changes did not win.

Abstract: When a particular event record requires a particular service, but that service has failed for the event, an error record that includes an aggregate identifier (AgID) is stored for the event in an error queue. Storing an error record in the error queue causes the service to notify a remediation team to fix the failed event. All events with the AgID in the error record are put on hold and an error record is created for each of these events. The remediation team generates a fixed version of the event record and causes the system to retry the failed service for the event based on the fixed version. If the fixed version of the event is successfully processed, then any other events with the same AgID that have error records in the error queue, are routed in order of enqueue time through the event processor to be handled.

Abstract: A pill verification system obtains a prescription filled at a pharmacy and gathers information of the pills being dispensed for a remote pharmacist to verify the prescription. As pills are dispensed to a pill vial to fill the prescription, a pill imaging system captures images of the pills, and a pill vial imaging system captures an image of the pill vial. The prescription, pill images, and pill vial image are transmitted to a remote verification system. A pharmacist is presented with the prescription, images of substantially all pills filling the prescription, and the pill vial of the prescription to verify the prescription is correct. The remote verification system may present prescriptions filled from many different pharmacies, permitting increased rate of verification and one pharmacist to support many pharmacies. The pharmacist's verification is transmitted to the pill verification system and displayed for a technician to complete verification of the pills.

Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: Techniques a provided for communication graph tracking in multi system operation in heterogeneous database systems, including retrieving two or more database commit logs from two or more corresponding heterogeneous databases. For each of the commit logs, a subset of information is extracted, including a correlation identifier, and event stream entries are produced based on that information and are stored. The event stream entries are then retrieved and event database entries are created based on the event stream entries. A request for a communication graph related to a particular correlation identifier is received and the event database is searched for matching entries. Those entries are used to generate a displayable communication graph for the particular correlation identifier, which is then provided in response to the request.

Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: A pill verification system obtains a prescription filled at a pharmacy and gathers information of the pills being dispensed for a remote pharmacist to verify the prescription. As pills are dispensed to a pill vial to fill the prescription, a pill imaging system captures images of the pills, and a pill vial imaging system captures an image of the pill vial. The prescription, pill images, and pill vial image are transmitted to a remote verification system. A pharmacist is presented with the prescription, images of substantially all pills filling the prescription, and the pill vial of the prescription to verify the prescription is correct. The remote verification system may present prescriptions filled from many different pharmacies, permitting increased rate of verification and one pharmacist to support many pharmacies. The pharmacist's verification is transmitted to the pill verification system and displayed for a technician to complete verification of the pills.

Abstract: Techniques a provided for performing multi-system operations in which changes are asynchronously committed in multiple systems. Metadata about the multi-system operation is injected into the commit logs of one system involved in a multi-system operation. An event stream is generated based on the commit logs of the one system, and is used to drive the operations that one or more other systems need to perform as part of the multi-system operation. A reconciliation system reads the logs of all systems involved in the multi-system operation and determines whether the multi-system operation completed successfully. Techniques are also provided for using machine learning to generate models of normal execution of different types of operations, detect anomalies, pre-emptively send expectation messages, and automatically suggest and/or apply fixes.

Abstract: A pill verification system obtains a prescription filled at a pharmacy and gathers information of the pills being dispensed for a remote pharmacist to verify the prescription. As pills are dispensed to a pill vial to fill the prescription, a pill imaging system captures images of the pills, and a pill vial imaging system captures an image of the pill vial. The prescription, pill images, and pill vial image are transmitted to a remote verification system. A pharmacist is presented with the prescription, images of substantially all pills filling the prescription, and the pill vial of the prescription to verify the prescription is correct. The remote verification system may present prescriptions filled from many different pharmacies, permitting increased rate of verification and one pharmacist to support many pharmacies. The pharmacist's verification is transmitted to the pill verification system and displayed for a technician to complete verification of the pills.

Abstract: A pill verification system obtains a prescription filled at a pharmacy and gathers information of the pills being dispensed for a remote pharmacist to verify the prescription. As pills are dispensed to a pill vial to fill the prescription, a pill imaging system captures images of the pills, and a pill vial imaging system captures an image of the pill vial. The prescription, pill images, and pill vial image are transmitted to a remote verification system. A pharmacist is presented with the prescription, images of substantially all pills filling the prescription, and the pill vial of the prescription to verify the prescription is correct. The remote verification system may present prescriptions filled from many different pharmacies, permitting increased rate of verification and one pharmacist to support many pharmacies. The pharmacist's verification is transmitted to the pill verification system and displayed for a technician to complete verification of the pills.