Abstract: Systems, apparatus, articles of manufacture, and methods are disclosed. An example apparatus disclosed herein is to determine whether to drop a data packet of a data stream or forward the data packet based on (a) a payload of the data packet and (b) historic information associated with the data stream. The example apparatus is also to operate on the data packet based on the determination.

Abstract: Methods, apparatus, systems and articles of manufacture to determine provenance for data supply chains are disclosed. Example instructions cause a machine to at least, in response to data being generated, generate a local data object and object metadata corresponding to the data; hash the local data object; generate a hash of a label of the local data object; generate a hierarchical data structure for the data including the hash of the local data object and the hash of the label of the local data object; generate a data supply chain object including the hierarchical data structure; and transmit the data and the data supply chain object to a device that requested access to the data.

Abstract: A method is described. The method includes performing the following within a data center: a) recognizing that excess power derived from one or more ambient sources is available; b) determining allocations of respective portions of the excess power for different units of hardware within the data center; c) determining respective higher performance and higher power operational states for certain functional blocks within the different units of the hardware to utilize the excess power.

Abstract: Technologies for migrating data between edge accelerators hosted on different edge locations include a device hosted on a present edge location. The device includes one or more processors to: receive a workload from a requesting device, determine one or more accelerator devices hosted on the present edge location to perform the workload, and transmit the workload to the one or more accelerator devices to process the workload. The one or more processor is further to determine whether to perform data migration from the one or more accelerator devices to one or more different edge accelerator devices hosted on a different edge location, and send, in response to a determination to perform the data migration, a request to the one or more accelerator devices on the present edge location for transformed workload data to be processed by the one or more different edge accelerator devices.

Abstract: Technologies for collecting metrics associated with a processing resource (e.g., central processing unit (CPU) resources, accelerator device resources, and the like) over a time window are disclosed. According to an embodiment presented herein, a network device receives, in an edge network, a request to provide one or more metrics associated with a processing resource, the request specifying a window indicative of a time period to capture the one or more metrics. The network device obtains the one or more metrics from the processing resource for the specified window and provides the obtained one or more metrics in response to the request.

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

Abstract: Technologies for collecting metrics associated with a processing resource (e.g., central processing unit (CPU) resources, accelerator device resources, and the like) over a time window are disclosed. According to an embodiment presented herein, a network device receives, in an edge network, a request to provide one or more metrics associated with a processing resource, the request specifying a window indicative of a time period to capture the one or more metrics. The network device obtains the one or more metrics from the processing resource for the specified window and provides the obtained one or more metrics in response to the request.

Abstract: Technologies for migrating data between edge accelerators hosted on different edge locations include a device hosted on a present edge location. The device includes one or more processors to: receive a workload from a requesting device, determine one or more accelerator devices hosted on the present edge location to perform the workload, and transmit the workload to the one or more accelerator devices to process the workload. The one or more processor is further to determine whether to perform data migration from the one or more accelerator devices to one or more different edge accelerator devices hosted on a different edge location, and send, in response to a determination to perform the data migration, a request to the one or more accelerator devices on the present edge location for transformed workload data to be processed by the one or more different edge accelerator devices.

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

Abstract: Methods, systems, and use cases for extended P2P communication with edge networking are discussed, including an edge computing device with a memory device and processing circuitry. The processing circuitry receives a request from a second edge computing device to perform a P2P exchange. A set of services for execution by the processing circuitry during the P2P exchange is determined. The processing circuitry further determines whether an enhanced edge service is available to substitute at least one service of the set of services. The enhanced edge service is associated with processing resources that are external to the edge computing device. Based on a successful determination that the enhanced edge service is available, the processing resources of the edge computing system that are external to the edge computing device are utilized to execute the enhanced edge service in place of the at least one service during the P2P exchange.

Abstract: Methods and apparatus to coordinate edge platforms are disclosed. A disclosed example apparatus includes to control processing of data associated with edges includes an orchestrator analyzer to determine a first performance requirement of a first microservice of an application and a second performance requirement of a second microservice of the application. The apparatus also includes an orchestrator controller to assign the first microservice and the second microservice across first and second edge nodes between a source network and a destination network by: assigning the first microservice to the first edge node based on a first capability of the first edge node satisfying the first performance requirement of the first microservice, and assigning the second microservice to the second edge node based on a second capability of the second edge node satisfying the second performance requirement of the second microservice.

Abstract: One embodiment provides an apparatus. The apparatus includes detector circuitry and monitor logic local to a computing device. The detector circuitry is to generate local sensor data based, at least in part, on a sensor signal received from a sensor incorporated in the local computing device. The monitor logic is to identify an event based, at least in part, on the local sensor data. The generating and identifying is independent of operation of an operating system and/or an application executing on the local computing device.

Abstract: Methods and apparatus for scale out hardware-assisted tracing schemes for distributed and scale-out applications. In connection with execution of one or more applications using a distributed processing environment including multiple compute nodes, telemetry and tracing data are obtained using hardware-based logic on the compute nodes. Processes associated with applications are identified, as well as the compute nodes on which instances of the processes are executed. Process instances are associated with process application space identifiers (PASIDs), while processes used for an application are associating with a global group identifier (GGID) that serves as an application ID. The PASIDs and GGIDs are used to store telemetry and/or tracing data on the compute nodes and/or forward such data to a tracing server in a manner that enables telemetry and/or tracing data to be aggregated on an application basis.

Abstract: Methods, apparatus, systems and articles of manufacture to determine provenance for data supply chains are disclosed. Example instructions cause a machine to at least, in response to data being generated, generate a local data object and object metadata corresponding to the data; hash the local data object; generate a hash of a label of the local data object; generate a hierarchical data structure for the data including the hash of the local data object and the hash of the label of the local data object; generate a data supply chain object including the hierarchical data structure; and transmit the data and the data supply chain object to a device that requested access to the data.

Abstract: Technologies for collecting metrics associated with a processing resource (e.g., central processing unit (CPU) resources, accelerator device resources, and the like) over a time window are disclosed. According to an embodiment presented herein, a network device receives, in an edge network, a request to provide one or more metrics associated with a processing resource, the request specifying a window indicative of a time period to capture the one or more metrics. The network device obtains the one or more metrics from the processing resource for the specified window and provides the obtained one or more metrics in response to the request.

Abstract: Technologies for monitoring service level agreement (SLA) performance in an end-to-end SLA monitoring architecture include a network functions virtualization (NFV) SLA controller configured to manage SLA agents initialized in various network processing components of the end-to-end SLA monitoring architecture. To do so, the NFV SLA controller is configured to provide instruction to the SLA agents indicating which types of telemetry data to monitor and receive the requested telemetry data, as securely collected and securely packaged by the SLA agents. The NFV SLA controller is further configured to securely analyze the received telemetry data to determine one or more performance metrics and compare performance benchmarks against the performance metrics to generate an SLA report that includes the results of the comparison. Other embodiments are described and claimed.

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

Abstract: Technologies for migrating data between edge accelerators hosted on different edge locations include a device hosted on a present edge location. The device includes one or more processors to: receive a workload from a requesting device, determine one or more accelerator devices hosted on the present edge location to perform the workload, and transmit the workload to the one or more accelerator devices to process the workload. The one or more processor is further to determine whether to perform data migration from the one or more accelerator devices to one or more different edge accelerator devices hosted on a different edge location, and send, in response to a determination to perform the data migration, a request to the one or more accelerator devices on the present edge location for transformed workload data to be processed by the one or more different edge accelerator devices.

Abstract: Methods, software, and apparatus for implementing local service chaining (LSC) with virtual machines (VMs) or virtualized containers in Software Defined Networking (SDN). In one aspect a method is implemented on a compute platform including a plurality of VMs or containers, each including a virtual network interface controller (vNIC) communicatively coupled to a virtual switch in an SDN. LSCs are implemented via a plurality of virtual network appliances hosted by the plurality of VMs or containers. Each LCS comprises a sequence (chain) of services performed by virtual network appliances defined for the LSC. In connection with performing the chain of services, packet data is forwarded between VMs or containers using a cut-through mechanisms under which packet data is directly written to receive (Rx) buffers on the vNICs in a manner that bypasses the virtual switch. LSC indicia (e.g.

Abstract: Methods and apparatus for accelerating VM-to-VM Network Traffic using CPU cache. A virtual queue manager (VQM) manages data that is to be kept in VM-VM shared data buffers in CPU cache. The VQM stores a list of VM-VM allow entries identifying data transfers between VMs that may use VM-VM cache “fast-path” forwarding. Packets are sent from VMs to the VQM for forwarding to destination VMs. Indicia in the packets (e.g., in a tag or header) is inspected to determine whether a packet is to be forwarded via a VM-VM cache fast path or be forwarded via a virtual switch. The VQM determines the VM data already in the CPU cache domain while concurrently coordinating with the data to and from the external shared memory, and also ensures data coherency between data kept in cache and that which is kept in shared memory.