Amazon Technologies, Inc.

Nikolay Krasilnikov

Alexey Gadalin

Anton Valter

Oleksii Tsai

Theodore Joseph Maka'iwi DeRego

Rudresh Amin

Benjamin Wojtowicz

Upendra Bhalchandra Shevade

Weili Zhong McClenahan

John Edsel Santos

Guy Sebastian Parton

Julius Mueller

Ethan John Faust

Dimitrios Elissaios

Yuan-An Liu

Sanket Modak

James Gowans

Jose Matias Dobovsek

Maya Kathleen Hess

Disclosed are various embodiments for automated deployment and management of distributed units (DUs) in a radio-based network. In one embodiment, it is determined to deploy a radio-based network at least partially using infrastructure of a cloud provider network. A radio access network (RAN)-enabled edge server of the cloud provider network is deployed to a physical location of the radio-based network. The RAN-enabled edge server is configured to perform a set of distributed unit (DU) functions for the radio-based network.

Automated deployment and management of distributed units in radio-based networks

Resources may be isolated for potentially fraudulent virtual compute instances. Resource utilization of virtual compute instances at a host system may be monitored. A virtual compute instance may be identified for fraud mitigation based on the monitored resource utilization. Availability of hardware resources to the identified virtual compute instance may be modified, whereas the availability of the hardware resources may remain for other virtual compute instances not identified for fraud mitigation.

Isolating resources for potentially fraudulent virtual compute instances

A testing manager at a provider network configures a multi-network-function test sandbox for a first network function developed by a first vendor. To configure the sandbox, the testing manager causes the first network function to be run at a first server and verifies network connectivity between the first network function and another network function which is not developed by the first vendor. The testing manager causes a test to be run, which includes transmission of messages from the first network function to the second network function. A result of the test is provided via a programmatic interface.

Automated cloud-based network function interoperability testing

Systems and methods are described for implementing an event tracing system for an open radio access network ('RAN'). A RAN implementation may be distributed across multiple components, including both special-purpose components such as radio units and general purpose components such as local or cloud-based servers. A RAN event tracing system may thus be used to troubleshoot issues with the RAN implementation by collecting information from distributed components regarding events that occur on these components during the translation of data into radio signals and vice versa. The RAN event tracing system may be used to search for events associated with a particular identifier, such as a radio network temporary identifier, and to display representations of radio frames that were generated by the components and display information regarding the events that led to the placement of particular resource elements onto the radio frames.

Radio access network event tracing system

A control plane server of a virtualized computing service determines that connectivity is to be established between a first portion and a second portion of a distributed application. The first portion runs at a first edge location of a provider network, and the second portion runs at a second edge location. The control plane server transmits metadata associated with the second edge location to a connectivity manager at the first edge location. The metadata is used to establish a secure network channel between the connectivity manager and the second edge location. A message from the first portion of the distributed application is sent to the second portion via the channel.

Managed connectivity between cloud service edge locations used for latency-sensitive distributed applications

State information of a radio-based application, used to process messages of the application, is made accessible from a first compute instance and a second compute instance at a virtualization server. The first instance is assigned to process a first portion of a workload of the application, including a message which comprises a result of a network function executed at a network function accelerator of the server. In response to determining that a condition for migrating workload from the first compute instance has been met, an additional message of the first portion is directed to the second compute instance. The second compute instance processes the additional message using the state information.

Enhancing availability of radio-based applications using multiple compute instances and virtualized network function accelerators at cloud edge locations

Generally described, one or more aspects of the present application relate to an instance cloning service for cloning a running virtual machine instance and configuring the resources of the new virtual machine instance created by cloning the running virtual machine instance. For example, the instance cloning service can create the new virtual machine instance and attach it to a storage volume to which the original virtual machine instance is attached. The instance cloning service may subsequently move the new virtual machine instance to another storage volume (e.g., based on a user request or based on the performance of the instances). Alternatively, upon cloning, the instance cloning service may attach the new virtual machine instance to a new storage volume. For example, the instance cloning service may use copy-on-write to provide the new virtual machine instance with its own storage volume.

Virtual machine cloning and resource configuration

This disclosure leverages multi-attach to block store volumes for more reliable live migration of virtualized resources. A block storage client of a virtualized resource operating on a source host in a first data center can be attached to a block storage volume stored on block storage hosts in the first data center. State data associated with the virtual machine can be transmitted from the source host to a target host, after which the virtual machine can run on the target host and operations of the virtualized resources may be ceased on the source host. Failure of the migration may require roll back to the source host. The source host may remain connected to the volume while the target host client connects to the volume, such that the volume may be accessed by the block storage client on the source host after rollback to provide uninterrupted operation of the virtual machine.

Multiple simultaneous volume attachments for live migration between cloud regions and edge locations

Techniques for a device with NUMA a memory architecture to migrate virtual resources between NUMA nodes to reduce resource contention between virtual resources running on the NUMA nodes. In some examples, the device monitors various metrics and/or operations of the NUMA nodes and/or virtual resources, and detect events that indicate that virtual resources running on a same NUMA node are contending, or are likely to contend, for computing resources of the NUMA node. Upon detecting such an event, the device may migrate a virtual resource from the NUMA node to another NUMA node on the device that has an availability of computing resources. The device may then migrate the virtual resource from the overcommitted NUMA node onto the NUMA node that has availability to run the virtual resource. In this way, devices may reduce resource contention among virtual resources running on a same NUMA node.

Migrating virtual resources between non-uniform memory access (NUMA) nodes

Various techniques for emulating edge locations in cloud-based networks are described. An example method includes generating an emulated edge location in a region. The emulated edge location can include one or more first computing resources in the region. A host in the region may launch a virtualized resource a portion of the one or more first computing resources. Output data that was output by the virtualized resource in response to input data can be received and reported to a user device, which may provide a request to migrate the virtualized resource to a non-emulated edge location. The non-emulated edge location may include one or more second computing resources that are connected to the region by an intermediary network. The virtualized resource can be migrated from the first computing resources to at least one second computing resource in the non-emulated edge location.

Emulated edge locations in cloud-based networks for testing and migrating virtualized resources

This disclosure describes systems, devices, and techniques for migrating virtualized resources between the main region and edge locations. Live migration enables virtualized resources to remain operational during migration. Edge locations are typically separated from secure data centers via the Internet, a direct connection, or some other intermediate network. Accordingly, to place virtualized resources within an edge location, the virtualized resources must be migrated over a secure communication tunnel that can protect virtualized resource data during transmission over the intermediate network. The secure communication tunnel may have limited data throughput. To efficiently utilize resources of the secure communication tunnel, and to reduce the impact of migrations on virtualized resource operations, virtualized resource migrations may be carefully scheduled in advance. For instance, virtualized resources may be selectively migrated at times-of-day in which they are likely to be relatively idle, or at times when the communication tunnel is predicted to have sufficient bandwidth.

Dynamic scheduling for live migration between cloud regions and edge locations

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.

Controlling placement of virtualized resources based on desirability index for host pools

This disclosure describes systems, devices, and techniques for migrating virtualized resources from outdated hosts during requested reboots of the virtualized resources, in order to update the outdated hosts. In an example method, a pending reboot a virtualized resource occupying a first host can be identified. At least one component of the first host may be determined to be outdated. In response to identifying the pending reboot and determining that the at least one component is outdated, the virtualized resource may be migrated to a second host. The first host may update the at least one component.

Transparent reboot interception migration to facilitate virtualization host updates

This disclosure describes systems, devices, and techniques for live migrating virtualized resources between the main region and edge locations. Live migration enables virtualized resources to remain operational during migration. Edge locations are typically separated from secure data centers via the Internet, a direct connection, or some other intermediate network. Accordingly, to place virtualized resources within an edge location, the virtualized resources must be migrated over a secure communication tunnel that can protect virtualized resource data during transmission over the intermediate network. The secure communication tunnel may have limited data throughput. To efficiently utilize resources of the secure communication tunnel, virtualized resource data may be transferred over the tunnel in a two-stage process. The disclosed technology provides various techniques for dynamically selecting which virtualized resource data, and how much virtualized resource data, is transferred over each of the pre-copy and post-copy stages.

Growing community of inventors

Seattle, WA, United States of America

Nikolay Krasilnikov