Abstract: Techniques for managing cloud computing resources hosting burstable performance instances are described. A host computer system of a provider network executes burstable performance compute instances. Compute capacity usage data is obtained from the host computer system, the compute capacity usage data including a first indication of a first compute capacity used by a first burstable performance compute instance. A first weight for the first burstable performance compute instance is calculated, the first weight being inversely related to the first compute capacity. A scheduler of the host computer system is updated with process prioritization weights, the process prioritization weights including a first process prioritization weight that is based at least in part on the first weight. The scheduler allocates compute capacity based on the process prioritization weights.

Abstract: This disclosure describes techniques for increasing the baseline performance of a burstable instance to an increased performance level for a limited time period. For example, a user may schedule a time period which the burstable instance has access to 100% of a CPU, instead of competing with other burstable instances even during periods of bursting as in prior techniques. In some cases, the user uses credits to reserve the time periods at which the increased performance level is requested. After receiving the reservation, a resource system selects computing resources to host the burstable instance such that the burstable instance, can operate at the requested increased performance level. After the time period has ended, the burstable instance may return to the baseline performance level.

Abstract: Techniques and technologies for migrating workloads between different VM instance types based on changes in resource utilization over a period of time. Selecting one VM instance type to host workloads can result in use of a VM instance type that is optimized for the workload during one timeframe of a period of time, but is over-provisioned or under-provisioned for the workload during another timeframe of a period of time. Accordingly, a service provider network may analyze historical utilization patterns of workloads over a period of time, and identify different VM instance types that are optimized for the workloads during different timeframes of the period of time. The service provider network may then cause the workloads to be migrated between the different VM instance types over the period of time such that the workloads are hosted on VM instances that are optimized for the current resource utilization of the workloads.

Abstract: Disclosed are various embodiments for an emulation layer for overcoming incompatibilities in virtual machine instance migration. In one embodiment, a virtual machine instance configured for a first computing architecture is executed in a first computing device having the first computing architecture. The virtual machine instance from the first computing device is migrated to a second computing device having a second computing architecture. The virtual machine instance is executed in the second computing device using an emulation layer that emulates the first computing architecture in the second computing architecture.

Abstract: Various techniques for managing heat and backwards-incompatible updates in cloud-based networks are described. In an example method, a virtualized resource, is identified. At least one first host may include an updated version of an element and at least one second host may include a previous version of the element. The updated version may be incompatible with the previous version. A first desirability index corresponding to the at least one first host may be less than a second desirability index corresponding to the at least one second host. The virtualized resource may be live-migrated from the source host to a target host among the at least one first host.

Abstract: Generally described, one or more aspects of the present application relate to an instance resource oversubscription service for scheduling a burst period for a running virtual machine instance based on a time window specified by a user of the virtual machine instance. For example, the instance resource oversubscription service can predict future resource usage and identify the appropriate timing and physical host machine for letting the user burst (e.g., temporarily use the virtual machine instance in a manner than consumes a higher amount of computing resources such as CPU cycles, memory, network bandwidth, etc.). In doing so, the instance resource oversubscription service may consider, for example, the historical and current resource utilization levels of the virtual machine instances running on a set of available physical host machines and the burst period scheduling requests from other users of the instance resource oversubscription service.