Reimagining How We Monitor
and Assure Network Services

In many instances, they can identify, isolate, troubleshoot, and resolve problems...
at the level of individual devices and network layers is still important for segmenting issues, but CSPs need to more quickly connect the dots between underlying problems and application-layer degradations. At the same time, operations teams need to be able to spot signs of unresolved problems in the underlying infrastructure—even if they present as sporadic, seemingly minor issues that modern self-healing networks can quickly adapt around.

Taking a more active approach

To address these blind spots, CSPs around the globe are adopting active assurance to complement passive monitoring. With active assurance, they can proactively test end-to-end networks and services by injecting synthetic traffic into the network. It’s like placing a CSP-controlled end-user device anywhere in the network to act as a probe. 

By emulating real users—including mimicking the full set of user behaviors, even under load, from anywhere users might access a service—CSPs can proactively identify issues. They can maintain real-time visibility into both the network- and service-level experience to validate and police SLAs. And they can run active testing continually—prior to activating new services, automatically when something in the environment changes, or on demand to troubleshoot an issue. With active assurance, CSPs can:

Keep up with dynamic 5G networks

Unlike passive monitoring, active assurance can react to continually changing infrastructure. It uses the same authentication, runs the same applications, and traverses the same network paths as real subscriber traffic, allowing CSPs to measure services exactly as users experience them. That’s a huge benefit, as CSPs don’t have to rearchitect their visibility strategy every time the infrastructure changes, as they would relying on passive probes.

Gain continuous visibility

As paths change, as the network dynamically updates, active assurance can proactively test 24/7/365. Operations teams don’t have to wait until real users are impacted to find out about a degradation or an outage. In many instances, they can identify, isolate, troubleshoot, and resolve problems before subscribers even notice them.

Accelerate root cause analysis

Assurance platforms can now use artificial intelligence and machine learning (AI/ML) to accelerate issue identification. In 5G SA networks, these capabilities become absolutely essential. With ML-based active assurance intelligence, CSPs can follow the end-to-end service path in complex 5G networks and sub-segment service components to quickly diagnose issues. This is especially useful for troubleshooting sporadic issues and ensuring that seemingly minor problems don’t turn into large-scale outages.

Proactively “stress-test” networks

With the ability to emulate user behavior and generate synthetic traffic anywhere in the network, CSPs can continually and proactively test all links. They can measure from multiple points in the network—for example, one agent simulating an end device connected over the Radio Access Network (RAN) and backhaul, another testing through the mobile core. And they can quickly detect emerging issues, often before they impact real users and SLAs.

Bring lab validation testing to the live network

CSPs have long relied on lab tools to precertify new infrastructure, providing a “birth certificate” to verify that a component is ready for live traffic. With active assurance, they can bring this same testing to the live network, recertifying infrastructure for any new service or network change. They can even integrate active testing into continuous


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