Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. A processor may, in response to identification of a suspension of user(s) for one of one or more services, generate a suspension value indicative of the suspension and transmit the suspension value to a corresponding one of third party platforms of the service(s), respectively. The suspension value usable by the corresponding third party platform to determine whether to deny request(s) from the user for the distributed service, or not. A service of the service(s) comprises a distributed service provided by a plurality of hosts. In response to the service corresponding to the suspension including the distributed service, the suspension value may be transmitted to the first host, and the suspension value may be propagated to the one or more second hosts, respectively. Other embodiments may be described and/or claimed.

Abstract: Annotating time series data points with alert information is described. A system retrieves a time series data point and a corresponding alert trigger condition from a time series database. The system evaluates whether the time series data point meets the corresponding alert trigger condition. The system outputs an alert notification associated with the time series data point and the corresponding alert trigger condition if the time series data point meets the corresponding alert trigger condition. The system annotates the time series data point, in the time series database, with alert information associated with the corresponding alert trigger condition if the time series data point meets the corresponding alert trigger condition.

Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. A processing device may collect set(s) of policy parameter values from one or more third party platforms, respectively, by communication with remote interface(s) employed on the one or more third party platforms, respectively; each set of policy parameter values defines a threshold for issuing a user suspension for a service provided by a respective one of the third party platforms; collect one or more sets of usage metrics for the one or more services from the one or more third party platforms, respectively, by communication with the remote interface(s); the communication with the remote interface(s) to collect the sets of usage metric(s) is asynchronous with communications by which the remote interface(s) received the usage metrics. Other embodiments may be described and/or claimed.

Abstract: A self-monitoring time series database system which enforces usage policies is described. A time series database system receives an alert trigger condition for a system user, wherein the system user is associated with multiple time series data points corresponding to multiple subsystems of the time series database system. The time series database system aggregates the multiple time series data points in an internal time series data point, which is internal to the time series database system, associated with the system user. The time series database system evaluates whether the internal time series data point associated with the system user meets the alert trigger condition. The time series database system reduces a level of access by the system user to the time series database system in response to an evaluation that the internal time series data point associated with the system user meets the alert trigger condition.

Abstract: A self-monitoring time series database system is described. A time series database system receives an alert trigger condition associated with multiple time series data points corresponding to multiple subsystems of the time series database system. The time series database system aggregates the multiple time series data points in an internal time series data point that is internal to the time series database system. The time series database system evaluates whether the internal time series data point meets the alert trigger condition. The time series database system outputs an alert notification associated with the internal time series data point and the alert trigger condition if the internal time series data point meets the alert trigger condition.

Abstract: A time series database system receives a trigger condition associated with time series data points corresponding to subsystems of the system. The system aggregates the time series data points associated with a first time into a first internal time series data point. The system aggregates the time series data points associated with a second time into a second internal time series data point if the first internal time series data point does not meet the trigger condition. The system calculates a projected internal time series data point based on the first internal time series data point and the second internal time series data point if the second internal time series data point does not meet the trigger condition. The system outputs a projected alert notification associated with the projected internal time series data point and the trigger condition if the projected internal time series data point meets the trigger condition.

Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. The PEaaS may allow customer service providers to define policies for usage restrictions to be implemented across their distributed systems/platforms. The policy enforcement mechanisms of the PEaaS may prevent users from overloading the systems/platforms of the customer service providers. The PEaaS may also include mechanisms for asynchronously (or “lazy”) tracking user infractions or suspensions. The lazy tracking mechanism may track and perform asynchronous (async) computation of infraction records and suspension sets/lists. Other embodiments may be described and/or claimed.

Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. A processor may, in response to identification of a suspension of user(s) for one of one or more services, generate a suspension value indicative of the suspension and transmit the suspension value to a corresponding one of third party platforms of the service(s), respectively. The suspension value usable by the corresponding third party platform to determine whether to deny request(s) from the user for the distributed service, or not. A service of the service(s) comprises a distributed service provided by a plurality of hosts. In response to the service corresponding to the suspension including the distributed service, the suspension value may be transmitted to the first host, and the suspension value may be propagated to the one or more second hosts, respectively. Other embodiments may be described and/or claimed.

Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. The PEaaS may allow customer service providers to define policies for usage restrictions to be implemented across their distributed systems/platforms. The policy enforcement mechanisms of the PEaaS may prevent users from overloading the systems/platforms of the customer service providers. Other embodiments may be described and/or claimed.

Abstract: A time series database system receives a request from a user device for first time series data within a first time range, the first time series data being a subset of second time series data within a second time range, the second time series data being stored in a persistent storage. The system determines whether all of the first time series data is stored in a memory. The system retrieves the second time series data from the persistent storage if all of the first time series data is not stored in the memory. The system stores the second time series data, excluding any part of the second time series data associated with a current time period, into the memory. The system causes the first time series data, being a subset of the second time series data retrieved from the persistent storage, to be outputted to the user device.

Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. A processor may, in response to identification of a suspension of user(s) for one of one or more services, generate a suspension value indicative of the suspension and transmit the suspension value to a corresponding one of third party platforms of the service(s), respectively. The suspension value usable by the corresponding third party platform to determine whether to deny request(s) from the user for the distributed service, or not. A service of the service(s) comprises a distributed service provided by a plurality of hosts. In response to the service corresponding to the suspension including the distributed service, the suspension value may be transmitted to the first host, and the suspension value may be propagated to the one or more second hosts, respectively. Other embodiments may be described and/or claimed.

Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. The PEaaS may allow customer service providers to define policies for usage restrictions to be implemented across their distributed systems/platforms. The policy enforcement mechanisms of the PEaaS may prevent users from overloading the systems/platforms of the customer service providers. The PEaaS may also include mechanisms for asynchronously (or “lazy”) tracking user infractions or suspensions. The lazy tracking mechanism may track and perform asynchronous (async) computation of infraction records and suspension sets/lists. Other embodiments may be described and/or claimed.

Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. A processor may, in response to identification of a suspension of user(s) for one of one or more services, generate a suspension value indicative of the suspension and transmit the suspension value to a corresponding one of third party platforms of the service(s), respectively. The suspension value usable by the corresponding third party platform to determine whether to deny request(s) from the user for the distributed service, or not. A service of the service(s) comprises a distributed service provided by a plurality of hosts. In response to the service corresponding to the suspension including the distributed service, the suspension value may be transmitted to the first host, and the suspension value may be propagated to the one or more second hosts, respectively. Other embodiments may be described and/or claimed.

Abstract: Systems, methods, and computer-readable media for providing a Policy Enforcement as a Service (PEaaS) are described. A processing device may collect set(s) of policy parameter values from one or more third party platforms, respectively, by communication with remote interface(s) employed on the one or more third party platforms, respectively; each set of policy parameter values defines a threshold for issuing a user suspension for a service provided by a respective one of the third party platforms; collect one or more sets of usage metrics for the one or more services from the one or more third party platforms, respectively, by communication with the remote interface(s); the communication with the remote interface(s) to collect the sets of usage metric(s) is asynchronous with communications by which the remote interface(s) received the usage metrics. Other embodiments may be described and/or claimed.

Abstract: Transforming time series data points from concurrent processes is described. A time series database system writes, to a queue, a first time series data point received from a first process. The time series database system writes, to the queue, a second time series data point received from a second process that executes concurrently with the first process. The time series database system removes the first time series data point and the second time series data point from the queue. The time series database system creates transformed time series data by applying a transformation to the first time series data point and the second time series data point. The time series database system outputs the transformed time series data to a user device.

Abstract: Provisioning timestamp-based storage units for time series data is described. A time series database system determines a remaining time period for a first storage unit to reach a storage capacity, the first storage unit storing first data with a first minimum timestamp. The time series database system provisions a second storage unit if the remaining time period for the first storage unit satisfies the provisioning threshold and stores second data with a second minimum timestamp to the second storage unit. The time series database system dispatches a query for third time series data to any storage unit if a time span from a minimum timestamp to a maximum timestamp associated with the storage unit includes at least part of a time range associated with the third time series data. The time series database system responds to the query for the third time series data based on dispatching the query.

Abstract: A time series database system receives a request from a user device for first time series data within a first time range, the first time series data being a subset of second time series data within a second time range, the second time series data being stored in a persistent storage. The system determines whether all of the first time series data is stored in a memory. The system retrieves the second time series data from the persistent storage if all of the first time series data is not stored in the memory. The system stores the second time series data, excluding any part of the second time series data associated with a current time period, into the memory. The system causes the first time series data, being a subset of the second time series data retrieved from the persistent storage, to be outputted to the user device.

Abstract: Transforming time series data points from concurrent processes is described. A time series database system writes, to a queue, a first time series data point received from a first process. The time series database system writes, to the queue, a second time series data point received from a second process that executes concurrently with the first process. The time series database system removes the first time series data point and the second time series data point from the queue. The time series database system creates transformed time series data by applying a transformation to the first time series data point and the second time series data point. The time series database system outputs the transformed time series data to a user device.

Abstract: Provisioning timestamp-based storage units for time series data is described. A time series database system determines a remaining time period for a first storage unit to reach a storage capacity, the first storage unit storing first data with a first minimum timestamp. The time series database system provisions a second storage unit if the remaining time period for the first storage unit satisfies the provisioning threshold and stores second data with a second minimum timestamp to the second storage unit. The time series database system dispatches a query for third time series data to any storage unit if a time span from a minimum timestamp to a maximum timestamp associated with the storage unit includes at least part of a time range associated with the third time series data. The time series database system responds to the query for the third time series data based on dispatching the query.

Abstract: A self-monitoring time series database system is described. A time series database system receives an alert trigger condition associated with multiple time series data points corresponding to multiple subsystems of the time series database system. The time series database system aggregates the multiple time series data points in an internal time series data point that is internal to the time series database system. The time series database system evaluates whether the internal time series data point meets the alert trigger condition. The time series database system outputs an alert notification associated with the internal time series data point and the alert trigger condition if the internal time series data point meets the alert trigger condition.