Abstract: Systems and methods for modeling live events are disclosed. A system can maintain results of simulations of a plurality of live events. The results can correspond to a plurality of conditional events that occur during each simulation. The system can receive selections of candidate outcomes for the conditional events to occur during a live event from a computing device, and identify a subset of the simulations having outcomes that correspond to the selections of the candidate outcomes. The system can generate an odds value based on a number of simulations in the subset and the total number of simulations for the live event, and can provide the odds value for presentation at the computing device.

Abstract: In one embodiment, a method for FPGA accelerated serverless computing comprises receiving, from a user, a definition of a serverless computing task comprising one or more functions to be executed. A task scheduler performs an initial placement of the serverless computing task to a first host determined to be a first optimal host for executing the serverless computing task. The task scheduler determines a supplemental placement of a first function to a second host determined to be a second optimal host for accelerating execution of the first function, wherein the first function is not able to accelerated by one or more FPGAs in the first host. The serverless computing task is executed on the first host and the second host according to the initial placement and the supplemental placement.

Abstract: Virtual machine (VM) proliferation may be reduced by determining the availability of existing VMs to perform a task. Tasks may be assigned to existing VMs instead of creating a new VM to perform the task. Furthermore, a coordinator may determine a grouping of VMs or VM hosts based on one or more factors associated with the VMs or the VM hosts, such as VM type or geographical location of the VM hosts. The coordinator may also assign one or more Virtual Server Agents (VSAs) to facilitate managing the group of VM hosts. In some embodiments, the coordinators may facilitate load balancing of VSAs during operation, such as during a backup operation, a restore operation, or any other operation between a primary storage system and a secondary storage system.

Abstract: Techniques for implementing an infrastructure orchestration service are described. A safety plan comprising a list of resources and operations based at least in part on a deployment configuration file can be received. Upon receiving approval of the safety plan, an operation corresponding to at least one of the list of resources can be prepared to be performed. The operation can be compared to the safety plan. If the operation is part of the safety plan, the operation can be performed. If the operation is not part of the safety plan, the deployment can be halted, and a notification that the deployment is not in compliance with the safety plan can be transmitted.

Abstract: Described herein are systems, methods, and software to manage communication rates between applications in a tiered application computing environment. In one implementation, a load service monitor load information associated with applications that each execute using one or more virtual nodes. The load service further determines that the load information associated with an application of the applications satisfy one or more load criteria and identifies at least one application that communicates requests to the application. Once identified, the load service communicates a notification to the at least one application to update a communication request configuration to the application.

Abstract: A system for managing access to a shared resource includes a plurality of nodes is described. The system may determine a quota for each of a plurality of nodes in view of one or more factors associated with a respective node and set a local counter stored in a memory of each of the nodes to the value of the relevant quota. In response to a request to access a resource made by an end device, the system may serve the request with a first node in the nodes, wherein the local counter stored in the memory of the first node is more than zero, and decrement the local counter stored in the memory of the first node by one after serving the request. Synchronization data is sent from each of the nodes, including the value of the local counter stored in the memory of the relevant node.

Abstract: In one embodiment, a method for FPGA accelerated serverless computing comprises receiving, from a user, a definition of a serverless computing task comprising one or more functions to be executed. A task scheduler performs an initial placement of the serverless computing task to a first host determined to be a first optimal host for executing the serverless computing task. The task scheduler determines a supplemental placement of a first function to a second host determined to be a second optimal host for accelerating execution of the first function, wherein the first function is not able to accelerated by one or more FPGAs in the first host. The serverless computing task is executed on the first host and the second host according to the initial placement and the supplemental placement.

Abstract: Disclosed are a service processing method and apparatus, an electronic device, and a computer-readable storage medium. The method includes: when receiving a User Interface (UI) request, creating a process instance corresponding to the UI request, and storing instance information of the process instance in a storage module (S101); determining a target process instance from the storage module, and determining a step to be executed of the target process instance based on target instance information of the target process instance (S102); searching, from a register, and executing a target method corresponding to the step to be executed, wherein the register includes all methods compiled according to a preset development specification (S103).

Abstract: Methods, systems, and computer storage media storing instructions for managing processing system efficiency. One of the methods includes obtaining data splitting a plurality of general-purpose processing units in a processing system into a high-priority domain and a low-priority domain, wherein the general-purpose processing units in the high-priority domain are assigned to perform one or more tasks comprising one or more high-priority tasks, and the general-purpose processing units in the low-priority domain are assigned to perform one or more low-priority tasks; and during runtime of the processing system, obtaining memory usage measurements that characterize usage of system memory by the high-priority domain and the low-priority domain; and adjusting, based on the memory usage measurements, a configuration of (i) the high-priority domain, (ii) the low-priority domain, or (iii) both to adjust utilization of the system memory by the general-purpose processing units.

Abstract: A method of remediating configurations of a plurality of system services running in each of a plurality of hosts, wherein each of the hosts is configured with a virtualization software for supporting execution of virtual machines therein, includes the steps of: retrieving actual configurations of the system services, wherein the actual configurations are stored in accordance with a configuration schema of the system services and include a user configuration, which is a configuration initiated by the user, and a system configuration, which is a configuration initiated by the host in response to the user configuration; retrieving desired configurations of the system services from a desired configuration file; comparing each of the actual configurations with a corresponding one of the desired configurations; and upon determining that at least one actual configuration, which is not a system configuration, is different from a corresponding one of the desired configurations, replacing the at least one actual config

Abstract: Systems, methods, and computer-readable media for annotating process and user information for network flows. In some embodiments, a capturing agent, executing on a first device in a network, can monitor a network flow associated with the first device. The first device can be, for example, a virtual machine, a hypervisor, a server, or a network device. Next, the capturing agent can generate a control flow based on the network flow. The control flow may include metadata that describes the network flow. The capturing agent can then determine which process executing on the first device is associated with the network flow and label the control flow with this information. Finally, the capturing agent can transmit the labeled control flow to a second device, such as a collector, in the network.

Abstract: Self-tuning clusters for resilient microservices, including: receiving, by a services orchestrator within a cloud-computing environment and from a plurality of cloud computing instances, respective latency measurements corresponding to respective control plane operations directed to a shared resource of the plurality of cloud computing instances; determining, based on a current timeout value and on the respective latency measurements from the plurality of cloud computing instances, an updated timeout value for the shared resource; and providing, to each of the plurality of cloud computing instances, the updated timeout value for the shared resource.

Abstract: Migration of quantum services from quantum computing devices to quantum simulators is disclosed herein. In one example, a quantum computing device executes a migration service that receives a system stress indicator from a system monitor that tracks a status of the quantum computing device and/or a status of qubits maintained by the quantum computing device. The migration service determines, based on the system stress indicator, that a quantum service running on the quantum computing device is to be migrated. Upon determining that the quantum service is to be migrated, the migration service retrieves a QASM file that contains quantum programming instructions defining the quantum service. The QASM file is then transmitted to a quantum simulator running on a classical computing device for failover execution. In some examples, the classical computing device then executes a simulated quantum service within the quantum simulator based on the QASM file.

Abstract: A system for analyzing and clustering darknet traffic streams with word embeddings, comprising a data processing module which collects packets that are sent to non-existing IP addresses that belong to darknet's taps (blackholes) that are deployed over the internet: a port embedding module for performing port sequence embeddings by using a word embedding algorithm on the port sequences extracted from the data processing module while transforming the port sequences into a meaningful numerical feature vectors: a clustering module for performing temporal clustering of the feature vectors over time; and an alert logic and visualization module visualizes the data and provides alerts regarding a cluster that an analyst classified as malicious in the past.

Abstract: A method of scheduling a plurality of tasks in an autonomous vehicle system (AVS) includes, by a processor, prior to runtime of an autonomous vehicle, identifying a plurality of tasks to be implemented by the AVS of the autonomous vehicle, for each of the tasks, identifying at least one fixed parameter and at least one variable, and developing a schedule for each of the tasks. The schedule includes an event loop that minimizes an overall time for execution of the tasks. The method includes compiling the schedule into an execution plan, and saving the execution plan to a memory of the autonomous vehicle. During runtime of the autonomous vehicle, the processor receives data corresponding to the variables of the tasks, and uses the variables to implement the execution plan on the autonomous vehicle.

Abstract: Devices and techniques for implementing quality-of-service (QoS) parameters in a managed memory device having a number of memory dies are disclosed herein.

Abstract: Techniques for concurrently supporting virtual non-uniform memory access (virtual NUMA) and CPU/memory hot-add in a virtual machine (VM) are provided. In one set of embodiments, a hypervisor of a host system can compute a node size for a virtual NUMA topology of the VM, where the node size indicates a maximum number of virtual central processing units (vCPUs) and a maximum amount of memory to be included in each virtual NUMA node. The hypervisor can further build and expose the virtual NUMA topology to the VM. Then, at a time of receiving a request to hot-add a new vCPU or memory region to the VM, the hypervisor can check whether all existing nodes in the virtual NUMA topology have reached the maximum number of vCPUs or maximum amount of memory, per the computed node size. If so, the hypervisor can create a new node with the new vCPU or memory region and add the new node to the virtual NUMA topology.

Abstract: Various examples are disclosed for cluster resource management using adaptive memory demands. In some examples, a local memory estimate is determined for a workload. The local memory estimate is determined using a memory reclamation parameter for the workload executed by a current host of the workload. A destination memory estimate is also determined for the workload. The destination memory estimate is determined using a full memory estimate unreduced by memory reclamation parameters. The workload is executed using a host that is selected in view of an analysis that uses the local memory estimate for the current host and the destination memory estimate for at least one destination host.

Abstract: Disclosed are various approaches to anticipating future resource consumption based on user sessions. A message comprising a prediction of a future number of concurrent user sessions to be hosted by a virtual machine within a predefined future interval of time is received. It is then determined whether the future number of concurrent user sessions will cause the virtual machine to cross a predefined resource threshold during the predefined future interval of time. Then, a message is sent to a first hypervisor hosting the virtual machine to migrate the virtual machine to a second hypervisor.

Abstract: Systems and methods for data replication. A data processing service can present a user interface configured to receive a data fusion algorithm from a user, and a request to execute a job, each job including instructions to copy data from one of a plurality of source databases to one of a plurality of target databases, and can present a plurality of virtual machines, each virtual machine comprising: a processing unit configured to attempt to start the job requested by the user, when the job can be started, lock the job from the rest of the plurality of virtual machines, and execute the job according to the data fusion algorithm using a random access memory (RAM) memory bucket.