An apparatus to facilitate provenance audit trails for microservices architectures is disclosed. The apparatus includes one or more processors to: obtain, by a microservice of a service hosted in a datacenter, provisioned credentials for the microservice based on an attestation protocol; generate, for a task performed by the microservice, provenance metadata for the task, the provenance metadata including identification of the microservice, operating state of at least one of a hardware resource or a software resource used to execute the microservice and the task, and operating state of a sidecar of the microservice during the task; encrypt the provenance metadata with the provisioned credentials for the microservice; and record the encrypted provenance metadata in a local blockchain of provenance metadata maintained for the hardware resource executing the task and the microservice.

An apparatus to facilitate provenance audit trails for microservices architectures is disclosed. The apparatus includes one or more processors to: obtain, by a microservice of a service hosted in a datacenter, provisioned credentials for the microservice based on an attestation protocol; generate, for a task performed by the microservice, provenance metadata for the task, the provenance metadata including identification of the microservice, operating state of at least one of a hardware resource or a software resource used to execute the microservice and the task, and operating state of a sidecar of the microservice during the task; encrypt the provenance metadata with the provisioned credentials for the microservice; and record the encrypted provenance metadata in a local blockchain of provenance metadata maintained for the hardware resource executing the task and the microservice.

A method includes causing, by a processor, a graphical user interface (GUI) to be output by a display. The GUI includes a first user input field identifying a target key performance indicator (KPI) associated with a network. A second user input field identifying a KPI peak-usage frequency. A third user input field identifying a peak-usage relationship. The method also includes creating a first monitoring profile based on the target KPI for the KPI peak-usage frequency for the peak-usage relationship. Storing the first monitoring profile. Monitoring the target KPI for the KPI peak-usage frequency based on the first monitoring profile. Collecting target KPI data over a period defined by the KPI peak-usage frequency. Determining a peak-usage during the period defined by the KPI peak-usage frequency based on the collected target KPI data. Periodically reporting peak-usage data based on the first monitoring profile.

A method for providing updated network slice information to a network slice selection function (NSSF includes registering, by a network slice management function (NSMF) with a network function (NF) repository function (NRF), an NF profile corresponding to the NSMF and subscribing, by the NSMF with the NRF, for status updates corresponding to NF instances belonging to network slice instances created by the NSMF. The method further includes receiving, by the NSMF from the NRF, a notification message including one or more network traffic load level updates related to at least one of the NF instances, processing the one or more network traffic load level updates to generate network slice instance configuration information for at least one of the network slice instances, and providing, by the NSMF, the network slice instance configuration information to a NSSF managing the at least one of the network slice instances.

Systems and methods provide a logical-physical warranty that is applied to nodes at a logical grouping level, such as a cluster. A logical warranty is associated with the nodes in the logical group or cluster in addition to each node's original individual warranty. The logical warranty stretches the expiration dates for individual warranties to a worst-case date inside the logical group. Customers build, teardown and extend the clusters, and the logical warranty is assigned to nodes in the cluster. The logical warranty is associated with a cluster of a defined size, such as a number of nodes expected, which can be expanded in the future as needed. The logical warranty ensures that there is uniform Service Level Agreement (SLA) for the nodes in the cluster during the warranty lifetime thereby simplifying the support for the cluster.

Techniques for generating and monitoring service level objectives (SLOs) are disclosed. The techniques include an SLO platform performing: storing a first SLO definition of a first SLO including a first error budget for a first metric associated with a first service; storing a second SLO definition of a second SLO including a second error budget for a second metric associated with a second service; obtaining first telemetry data from a first data source associated with the first service; obtaining second telemetry data from a second data source associated with the second service; monitoring the first SLO at least by computing the first metric based on the first telemetry data and evaluating the first metric against the first error budget; and monitoring the second SLO at least by computing the second metric based on the second telemetry data and evaluating the second metric against the second error budget.

In one embodiment, a device obtains user experience metrics for a plurality of sessions with an online application. The device detects a plurality of anomalies from among the user experience metrics. The device determines, based on a correlation between the plurality of anomalies, that a particular path entity is a root cause of the plurality of anomalies. The particular path entity comprises an egress service provider or data center of the online application. The device provides an indication of the particular path entity being the root cause of the plurality of anomalies.

Systems and methods that adaptively model network traffic to predict network capacity utilization and quality of experience into the future. The adaptive model of network traffic may be used to recommend capacity upgrades based on a score expressed in a QoE space.

Systems and methods for managing network traffic receives, at a grade of service device, network traffic information for a plurality of network traffic channels from a network device separate from the grade of service device. The network traffic information is compared to a threshold to determine a behavior value for each network traffic channel. Each network traffic channel is mapped to a grade of service according to the behavior value.

Systems and methods for managing network traffic receives, at a grade of service device, network traffic information for a plurality of network traffic channels from a network device separate from the grade of service device. The network traffic information is compared to a threshold to determine a behavior value for each network traffic channel. Each network traffic channel is mapped to a grade of service according to the behavior value.