Closer Look

Before tearing down your Quick Start deployment, there are two additional steps you can take to watch Aether in action. The first is to bring up the Aether Management Plane (AMP), which includes Dashboards showing different aspects of Aether’s runtime behavior. The second is to enable packet capture, and then run an analysis tool to trace the flow of packets into and out of SD-Core.

Install AMP

The Aether Management Platform (AMP) is implemented by two Kubernetes applications: Runtime Operational Control (ROC) and a Monitoring Service.1 AMP can be deployed on the same cluster as SD-Core by executing the following Make target:

$ make aether-amp-install

Once complete, kubectl will show the aether-roc and cattle-monitoring-system namespaces running in support of these two services, respectively, plus new atomix pods in the kube-system namespace. Atomix is the scalable key-value store that keeps the ROC data model persistent.

1

Note that what the implementation calls ROC, Chapter 6 refers to generically as Service Orchestration.

You can access the dashboards for the two subsystems, respectively, at

http://<server_ip>:31194
http://<server_ip>:30950

The programmatic API underlying the Control Dashboard, which was introduced in Section 6.4, can be accessed at http://10.76.28.113:31194/aether-roc-api/ in our example deployment (where Aether runs on host 10.76.28.113).

There is much more to say about the ROC and the Aether API, which we return to in the section on Runtime Control. For now, we suggest you simply peruse the Control Dashboard by starting with the dropdown menu in the upper right corner. For example, selecting Devices will show the set of UEs registered with Aether, similar to the screenshot in Figure 2. In an operational setting, these values would be entered into the ROC through either the GUI or the underlying API. For the Quick Start scenario we’re limiting ourselves to in this section, these values are loaded from deps/amp/5g-roc/templates/roc-5g-models.json.

Figure 2. Screenshot of the ROC dashboard, showing known Devices. The dropdown menu on the right lists other available pages.

Turning to the Monitoring Dashboard, you will initially see Kubernetes-related performance stats. Select the 5G Dashboard option to display information reported by SD-Core. Similar to Figure 3, the page shows an active (green) UPF, and once you rerun the RAN simulator (gNBsim), some number of active base stations and connected devices. The bottom panel shows the UPF throughput, which due to gNBsim’s focus on stressing the control plane, typically shows only minimal activity.

Figure 3. Screenshot of the monitoring subsystem’s 5G dashboard.

When you are done experimenting with AMP, type the following to tear it down:

$ make aether-amp-uninstall

Run Ksniff and Wireshark

In addition to the trace output generated by the simulator, a good way to understand the inner working of Aether is to use Ksniff (a Kubernetes plugin) to capture packets and display their headers as they flow into and out of the microservices that implement Aether. Output from Ksniff can then be fed into Wireshark.

To install the Ksniff plugin on the server running Aether, you need to first install krew, the Kubernetes plugin manager. Instructions on doing that can be found online. Once that’s done, you can install Ksniff by typing:

$ kubectl krew install sniff

You can then run Ksniff in the context of a specific Kubernetes pod by specifying their namespace and instance names, and then redirecting the output to Wireshark. If you don’t have a desktop environment on your Aether server, you can either view the output using a simpler packet analyzer, such as tshark, or by redirecting the PCAP output in a file and transfer it a desktop machine for viewing in Wireshark.

For example, the following captures and displays traffic into and out of the AMF, where you need to substitute the name of the AMP pod you learned from kubectl in place of amf-5887bbf6c5-pc9g2.

$ kubectl sniff -n omec amf-5887bbf6c5-pc9g2 -o - | tshark -r -

Of course, you’ll also need to restart the RAN emulator to generate workload for this tool to capture.