Lab 11: KPM Monitoring rApp with OCUDU

Experimental

This is an experimental blueprint intended for Non-Terrestrial Network (NTN) evaluation in an emulated environment.

This lab has two parts:

1. Deploy the network. You deploy an emulated 5G Standalone (SA) network with an OCUDU Non-Terrestrial Network (NTN) gNB and an OAI UE. FlexRIC acts as the Near-RT RIC and connects to the gNB over the E2 interface.
2. Monitor the network. You use the Monitoring service of the BubbleRAN rApp SDK to create a MonitoringJob that collects Key Performance Measurement (KPM) metrics from the gNB. When the job is created, the SMO automatically deploys a monitoring xApp. The xApp subscribes to the KPM service model over E2 and stores the collected metrics in the Victoria Metrics database in the cluster.

Network Deployment

ocudu-oai-net.yaml

apiVersion: athena.trirematics.io/v1
kind: Network
metadata:
    name: ocudu-zmq-ntn
    namespace: trirematics
spec:
    slices:
        -   plmn: "00101"
            dnn: internet
            network-mode: IPv4
            service-type: 1
            differentiator: 0x000000
            ipv4-range: 12.1.1.0/24
            ipv6-range: 2001:db8:1::/64
    access:
        -   name: gnb
            stack: 5g-sa
            model: ocudu/monolithic-gnb-ntn
            identity:
                an-id: 30
                tracking-area: 1
            radio:
                device: zmq
            annotations:
                terminals.roles.athena.t9s.io/oai-ue: "oai-ue-ntn.oai-ue.oai-ue.t9s.local"
            cells:
                -   band: n256
                    arfcn: 437000
                    bandwidth: 5MHz
                    subcarrier-spacing: 15kHz
            core-networks:
                - minimal.ocudu-zmq-ntn
            controller: flexric.ocudu-zmq-ntn
    core:
        -   name: minimal
            stack: 5g-sa
            model: oai-cn/minimal
            identity:
                region: 0
                cn-group: 4
                cn-id: 5
    edge:
        -   name: flexric
            stack: 5g-sa
            model: mosaic5g/flexric

    dns:
        ipv4:
            default: 8.8.8.8
            secondary: 8.8.4.4
---
apiVersion: athena.trirematics.io/v1
kind: Terminal
metadata:
    name: oai-ue
    namespace: trirematics
spec:
    vendor: oai
    stack: 5g-sa
    model: terminal/oai-ue-ntn
    preferred-access: gnb.ocudu-zmq-ntn
    target-cores:
        - minimal.ocudu-zmq-ntn
    identity:
        imsi: "001010000000001"
        pin: "1234"
        opc: "0xc42449363bbad02b66d16bc975d77cc1"
        key: "0xfec86ba6eb707ed08905757b1bb44b8f"
        sqn: "0xff9bb4000001"
    slice:
        dnn: internet
        network-mode: IPv4
        service-type: 1
        differentiator: 0x000000
    radio:
        device: zmq
        formation: "1x1"
        bands:
            - n256
    readiness-check:
        method: ping
        target: google-ip
        interface-name: oaitun_ue1

Deploy the network:

brc install network ocudu-oai-net.yaml

tip

The ocudu-oai-net.yaml file does not define a monitoring xApp. The SMO deploys one automatically when the rApp creates the MonitoringJob.

Run brc observe and wait until every Element shows 1/1 Y.

Then check that the UE is connected by sending three pings to the gateway:

brc test rtt oai-ue gateway -- -c 3

KPM Monitoring rApp

The following rApp creates a MonitoringJob named kpm-monitoring, then waits until the job is running:

mon-rapp-ocudu.py

from br_rapp_sdk import MonitoringServices
from br_rapp_sdk.monitoring_services.monitoring_types import *
import time

if __name__ == "__main__":

    # Initialize the A1Services
    monitoring_services = MonitoringServices()

    # Define the monitoring information for KPM
    kpm_monitoring_info = MonitoringObjectInformation(
        target="flexric.ocudu-zmq-ntn",
        monitoringTypeId="mosaic5g/monitoring-c",
        monitoringObject=MonitoringObject(
            monitoringStatements=MonitoringStatements(
                serviceModels=[
                    ServiceModel(name="KPM", periodicity="1000")
                ],
                profiles=["ocudu"],
                database=DatabaseType(
                    victoriaMetrics=VictoriaMetricsDatabase(scenario="test_kpm_ntn")
                )
            )
        )
    )


    # Print the monitoring information in YAML format
    print("KPM Monitoring Object Information: \n", kpm_monitoring_info.yaml())

    # Apply the monitoring object
    monitoring_name = "kpm-monitoring"
    result = monitoring_services.apply_monitoring(
        monitoring_name=monitoring_name,
        monitoring_object=kpm_monitoring_info
    )
    # Check if the monitoring object was applied successfully
    if result.status == 'success':
        monitoring_id = result.data.get('monitoring_id')
        print(f"KPM Monitoring Object applied successfully: {monitoring_id}")
    else:
        print(f"Error applying KPM Monitoring Object: {result.error}")
        exit(1)
    

    # Wait until the monitoring object is "Running"
    while True:
        status = monitoring_services.get_monitoring_status(monitoring_id=monitoring_id)

        phase = status.data.get('status', {}).get('phase') if status.status == 'success' else 'error'

        print(f"KPM status: {phase}")
                
        if phase == "Running":
            print("KPM Monitoring Objects is Running.")
            break

        time.sleep(3)
    

The MonitoringJob defines:

• Target: flexric.ocudu-zmq-ntn, the FlexRIC instance that the OCUDU gNB connects to.
• Service model: KPM, reported every 1000 ms (periodicity="1000"), with the ocudu profile.
• Database: Victoria Metrics. The scenario label (test_kpm_ntn) tags every sample from this job, so you can filter on it when you query the data later.

danger

Before you run the rApp:

• Install the BubbleRAN rApp SDK if it is not already installed: pip3 install br-rapp-sdk.
• Run the rApp from a machine with access to the cluster, and make sure your kubeconfig file is at ~/.kube/config.

Run the rApp:

python3 ./mon-rapp-ocudu.py

The rApp prints the MonitoringJob in YAML format, followed by KPM Monitoring Object applied successfully and the job ID. It then prints the job status every few seconds and exits once the status is Running.

Run brc observe again. A new xApp whose name starts with monitoring-c.dynxapp (for example, monitoring-c.dynxapp1e18f4-flexric.ocudu-zmq-ntn) appears in the list. Wait until it shows 1/1 Y, which means it is deployed and running.

Follow the xApp logs to see the KPM reports. Replace the name with the one shown by brc observe:

brc extract logs monitoring-c.dynxapp1e18f4-flexric.ocudu-zmq-ntn

In a second terminal, generate uplink traffic from the UE for 60 seconds:

brc test throughput oai-ue ul gateway -- -t 60

While the test runs, watch the xApp logs. The uplink throughput metric DRB.UEThpUl should increase.

Uninstall

Remove the network and the MonitoringJob:

brc remove network ocudu-oai-net.yaml
brc remove monitoringjob kpm-monitoring

Run brc observe to confirm that all Elements and rApp jobs are gone.

💬 Questions

1. Which KPM metrics does the OCUDU gNB report? Are any metrics missing compared with the OAI gNB in Lab 5?
2. Compare the uplink throughput reported by the KPM xApp with the result of brc test throughput. Do the values match? Explain any difference.
3. Follow Visualizing Data in Grafana to plot the collected KPM metrics in Grafana.