Abstract:
A virtualization host may implement variable timeslices for processing latency dependent workloads. Multiple virtual compute instances on a virtualization host may utilize virtual central processing units (vCPUs) to obtain physical processing resources, such as one or more central processing units (CPUs). A vCPU currently utilizing a CPU to performing processing work according to a scheduled timeslice may be preempted by a latency dependent vCPU before completion of the scheduled timeslice. The latency-dependent vCPU may complete processing work, and utilization of the CPU may be returned to the vCPU. A preemption compensation may be determined for the scheduled timeslice to increase the scheduled timeslice for the vCPU such that utilization for the vCPU is performed according to the increased scheduled timeslice.
Abstract:
Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
Abstract:
Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
Abstract:
Migrating servers from client networks to virtual machines (VMs) on a provider network. A migration appliance is installed or booted on the client network, and a migration initiator is instantiated on the provider network. A VM and associated volumes are instantiated on the provider network. The initiator sends a request for a boot sector to the appliance; the appliance reads the blocks from a volume on the client network, converts the blocks to a format used by the VM, and sends the blocks to the initiator. The initiator boots the VM using the boot sector and the VM begins execution. The initiator then retrieves all data blocks for the VM from volumes on the client network via the appliance, stores the data to the volumes on the provider network, and fulfills requests from the VM from either local volumes or the remote volumes via the appliance.
Abstract:
Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
Abstract:
Techniques for an optimization service of a service provider network to generate an architecture diagram that represents an architecture of a web-based application. The optimization service may use the architecture diagram to determine modifications or changes to make to the application. For example, the optimization service may compare the architecture diagram with optimized architecture diagrams that represent application best practices, and determine the modifications or change to make to the application to optimize the application and bring the application in-line with best practices. Further, the optimization service may use the architecture diagram to generate a visualization, and provide the user account with the visualization of the architecture diagram to show users their application architecture.
Abstract:
Techniques for managing dynamically scalable virtualized compute instances within a provider network are described. A dynamically scalable instance has a baseline performance level and a maximum performance level associated with a computing resource, such as a processor, a memory, a network interface, etc. In response to receive a request to launch a dynamically scalable instance, one or more services select a computer system to host the requested instance from a pool of instance-hosting computer systems of a provider network. The instance-hosting computer systems include a monitoring agent that reports computing resource usage data to the one or more services. The one or more services monitor the resource usage of the instance-hosting computer systems and migrate instances so that the dynamically scalable instances can operate up to the maximum level of performance.
Abstract:
Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
Abstract:
Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.
Abstract:
A service provider system may implement ECC-like features when executing computations on GPUs that do not include sufficient error detection and recovery for computations that are sensitive to bit errors. During execution of critical computations on behalf of customers, the system may automatically instrument program instructions received from the customers to cause each computation to be executed using multiple sets of hardware resources (e.g., different host machines, processor cores, or internal hardware resources). The service may provide APIs with which customers may instrument their code for execution using redundant resource instances, or specify parameters for applying the ECC-like features. The service or customer may instrument code to perform (or cause the system to perform) checkpointing operations at particular points in the code, and to compare intermediate results produced by different hardware resources. If the intermediate results do not match, the computation may be restarted from a checkpointed state.