Techniques are provided for managing resources among clusters of computing devices in a computing system. Resource reassignment message are generated for indicating that servers are reassigned and in response to resource compute loads exceed or fall below certain thresholds. Techniques also include establishing communications with the reassigned servers to assign compute loads without physically relocating the servers from one cluster to another cluster.

Methods and apparatus for client-directed placement of remotely configured service instances are described. One or more placement target options are selected for a client of a network-accessible service based on criteria such as service characteristics of the placement targets. The selected options, including a particular placement target that includes instance hosts configurable from remote control servers, are indicated programmatically to the client. A determination is made that a service instance is to be configured at the particular placement target on behalf of the client. A remote control server is configured to issue administrative commands to an instance host at the particular placement target to configure the service instance.

Methods and apparatus for client-directed placement of remotely configured service instances are described. One or more placement target options are selected for a client of a network-accessible service based on criteria such as service characteristics of the placement targets. The selected options, including a particular placement target that includes instance hosts configurable from remote control servers, are indicated programmatically to the client. A determination is made that a service instance is to be configured at the particular placement target on behalf of the client. A remote control server is configured to issue administrative commands to an instance host at the particular placement target to configure the service instance.

Systems, methods, and devices, including computer-readable media, for reducing medication side effects using digital therapeutics. In some implementations, a system analyzes tracking data, user data, and medication data for various users to determine a degree to which different digital therapeutics program parameters reduce a likelihood or severity of undesired effects of medications. The system generates data that associates the parameters of the digital therapeutics programs with effects of the medications. The system receives data indicating a medication prescribed for a user of a mobile device and, based on the generated data, selects one or more digital therapeutics program parameters to activate or adjust a particular digital therapeutic program to provide interactions to the user.

Systems, methods, and devices, including computer-readable media, for reducing medication side effects using digital therapeutics. In some implementations, a system analyzes tracking data, user data, and medication data for various users to determine a degree to which different digital therapeutics program parameters reduce a likelihood or severity of undesired effects of medications. The system generates data that associates the parameters of the digital therapeutics programs with effects of the medications. The system receives data indicating a medication prescribed for a user of a mobile device and, based on the generated data, selects one or more digital therapeutics program parameters to activate or adjust a particular digital therapeutic program to provide interactions to the user.

Techniques are disclosed for generating intent-based policies and applying the policies to traffic of a computer network. In one example, a policy controller for the computer network receives traffic statistics for traffic flows among a plurality of application workloads executed by a first set of computing devices. The policy controller correlates the traffic statistics into session records for the plurality of application workloads. The policy controller generates, based on the session records for the application workloads, application firewall policies for the application workloads. Each of the application firewall policies define whether traffic flows between application workloads are to be allowed or denied. The policy controller distributes the application firewall policies to a second set of one or more computing devices for application to traffic flows between instances of the application workloads.

Techniques are disclosed for generating intent-based policies and applying the policies to traffic of a computer network. In one example, a policy controller for the computer network receives traffic statistics for traffic flows among a plurality of application workloads executed by a first set of computing devices. The policy controller correlates the traffic statistics into session records for the plurality of application workloads. The policy controller generates, based on the session records for the application workloads, application firewall policies for the application workloads. Each of the application firewall policies define whether traffic flows between application workloads are to be allowed or denied. The policy controller distributes the application firewall policies to a second set of one or more computing devices for application to traffic flows between instances of the application workloads.

Implementations described and claimed herein provide systems and methods for intelligent node type selection in a telecommunications network. In one implementation, a customer set is obtained for a communications node in the telecommunications network. The customer set includes an existing customer set and a new customer set. A set of customer events is generated for a node type of the communications node using a simulator. The set of customer events is generated by simulating the customer set over time through a discrete event simulation. An impact of the customer events is modeled for the node type of the communications node. The node type is identified from a plurality of node types for a telecommunications build based on the impact of the customer events for the node type.

Implementations described and claimed herein provide systems and methods for intelligent node type selection in a telecommunications network. In one implementation, a customer set is obtained for a communications node in the telecommunications network. The customer set includes an existing customer set and a new customer set. A set of customer events is generated for a node type of the communications node using a simulator. The set of customer events is generated by simulating the customer set over time through a discrete event simulation. An impact of the customer events is modeled for the node type of the communications node. The node type is identified from a plurality of node types for a telecommunications build based on the impact of the customer events for the node type.

The automatic classification of network devices in a network. Specifically, the disclosure entails the designation of network device roles to network devices, as well as the clustering of network devices into logical groups. The association of network devices with network device roles and logical groups may be contingent on the connections between the network devices and a set of network device classification heuristics.