ACROSS - SLA Monitoring Telemetry Dataset

This dataset includes compute telemetry data collected from a Server-Client setup deployed across a 5G network in a period of 3.5 days in the context of Test Case 4.6 (TC4.6) for the ACROSS project.The dataset is used to train forecasting models that continuously monitor a system's compute telemetry data and ensure that Service Level Agreements (SLAs) issued by the system's operators are maintained under different system operating conditions. These include SLAs related to CPU usage, memory allocation and bandwidth. When a potential SLA violation is detected, alerts are passed to other system components, such as the Automation Event Handler, which triggers the Policy Executor to evaluate the event and determine whether adaptation is required.The setup includes a Streaming Server that streams a video consumed by a Streaming Client. Both the client and the server are deployed in dedicated Kubernetes clusters. Given the above setup, the collected telemetry data includes multiple univariate measurements from four different points of view:The Streaming Server, deployed as a container in a Kubernetes pod.The Streaming Client, deployed as a container in a Kubernetes pod.The Server K8-Cluster, that is the K8 cluster that contains the Server container.The Client K8-Cluster, that is the K8 cluster that contains the Client container.The measurements were taken from Prometheus endpoints, in 1-second intervals, collecting telemetry data from the services and the K8 clusters with a scrape-period of 30 seconds. For each measured instance, a total of 288,435 values were collected.