Pass the Cisco CCNP Enterprise 300-445 Questions and answers with CertsForce

In the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) framework, baselining is the process of establishing a " normal " performance profile for network infrastructure to enable the detection of anomalies. When the metric of interest is the internal health of a physical device, such as CPU utilization on a core router, SNMP (Simple Network Management Protocol) is the industry-standard data source.

SNMP provides direct visibility into the device ' s control plane and hardware performance. By polling specific Object Identifiers (OIDs) from the router ' s Management Information Base (MIB), a monitoring system like Cisco Catalyst Center or a third-party NMS can collect granular data on CPU cycles, memory allocation, and temperature. This " inside-out " telemetry is essential for baselining because it reflects the actual resource consumption of the router during various traffic loads.

Conversely, ThousandEyes tests (Options A, B, and D) provide " outside-in " synthetic data. While DNS resolution time (Option A), HTTP response times (Option B), and Path Visualization (Option D) are excellent for measuring end-to-end service delivery and network transit health, they do not report on the router ' s internal hardware state. For instance, a router could have 99% CPU utilization (indicating a potential crash), yet a ThousandEyes path test might still show a " green " path if the data plane (ASICs) is still forwarding packets efficiently. Therefore, to establish a reliable baseline for hardware-specific metrics like CPU, SNMP data (Option C) is the only appropriate source among the choices.

In the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) curriculum, understanding the distinction between different monitoring methodologies is fundamental to architecting an effective assurance strategy. When an engineer deploys a ThousandEyes Enterprise Agent on a Meraki MX appliance, they are implementing active monitoring .

Active monitoring, as defined in standard network assurance frameworks like RFC 7799, involves the generation of synthetic traffic or " probes " that are sent across the network to a specific destination. These probes, which can utilize protocols such as ICMP, TCP, or HTTP/S, simulate real user transactions to measure performance metrics including latency, packet loss, jitter, and path visualization. The Enterprise Agent acts as a dedicated vantage point, executing these tests at scheduled intervals to provide a proactive baseline of network and application health. This allows the engineer to identify performance degradation or outages even when no real users are actively using the application, ensuring that issues are detected before they impact the business.

It is important to contrast this with passive monitoring (Option B). In the Meraki ecosystem, Meraki Insight (MI) natively performs passive monitoring by observing and analyzing actual user traffic flows (HTTP/S data) as they traverse the MX appliance without injecting additional traffic. While passive monitoring is excellent for understanding real-world user experience and server response times, it relies on existing traffic and cannot provide hop-by-hop path visualization across the Internet in the same way active synthetic probing does.

By integrating the ThousandEyes Enterprise Agent—which runs as a containerized service within the MX architecture—the engineer gains the benefits of active monitoring directly from the branch edge. This eliminates the need for separate hardware and provides deep, " outside-in " and " inside-out " visibility into SaaS application performance. Therefore, the deployment of a ThousandEyes agent explicitly enables active monitoring (Option A) to supplement the native passive capabilities of the Meraki platform.

According to the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) best practices for collaboration monitoring, Microsoft Teams (as well as Webex and Zoom) is monitored using a combination of Scheduled and Dynamic tests (Option D).

Scheduled Tests: These are used to proactively monitor the reachability and performance of the Microsoft Teams infrastructure. The Teams template typically includes scheduled HTTP Server tests to teams.microsoft.com and login.microsoftonline.com, along with network-layer tests to the Teams Transport Relay (e.g., worldaz.tr.teams.microsoft.com). These provide a continuous baseline of connectivity regardless of whether a user is currently in a call.

Dynamic Tests: These are a unique feature for collaboration monitoring. When an Endpoint Agent detects that the Teams application has initiated a real-time media session (audio or video call), it automatically triggers a Dynamic Test to the specific IP and port being used for that call. This allows IT teams to see the exact network path—including hop-by-hop latency and loss—of the actual call traffic while the session is active.

Real User Tests (Option C) are generally not used for Teams monitoring in the same way they are for web-based SaaS apps. Because most users utilize the Teams desktop client rather than the browser, the RUM browser extension cannot capture the rich telemetry of the desktop application ' s internal signaling and media streams. Therefore, the specialized " Automated Session Testing " provided by Dynamic Tests , combined with the proactive health checks of Scheduled Tests , constitutes the complete assurance strategy for Microsoft Teams.

In the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) architecture, the deployment of ThousandEyes Enterprise Agents on switching infrastructure is designed to be highly flexible, catering to different management styles and network scales. Modern Cisco switches, specifically the Catalyst 9300 and 9400 Series , support the execution of containerized applications directly on the switch ' s hardware through the Cisco IOS XE Application Hosting framework. 1

Application Hosting (Option A) refers to the manual method using the Cisco IOS XE Command Line Interface (CLI). An engineer can use app-hosting commands to install, configure, and manage the Docker-based Enterprise Agent. 2 This provides granular control over resource allocation and networking for the container. Catalyst Center (Option B) provides a GUI-driven, automated workflow to deploy agents at scale across an entire campus fabric. 3 It simplifies the lifecycle management by handling the installation and activation across multiple switches simultaneously. For switches acting as edge devices in an SD-WAN fabric, Catalyst SD-WAN Manager (Option C) orchestrates the deployment through centralized policies and templates, allowing the agent to be pushed as part of a device configuration. Finally, while the ThousandEyes Portal (Option D) is the management plane for tests, it is also where the Docker image and Account Group Token are obtained for any of the aforementioned deployment methods.

Each method provides the same end result: an Enterprise Agent running " on-box " to provide deep visibility into the network path starting directly from the access or core layer. Therefore, All of the above (Option E) is the correct answer as it encompasses the manual, automated, and orchestrated methods available for switch-based deployment as per the 300-445 ENNA official guidelines.

For the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) exam, monitoring remote workforces requires a strategy that captures both the user ' s local environment and the regional internet health. In a scenario involving Cisco AnyConnect VPN, the " last mile " connectivity of the employee is often the most significant variable in application performance.

Utilizing the ThousandEyes Endpoint Agent (Option D) is the most effective way to monitor this environment. Because the agent resides directly on the remote employee ' s machine, it can monitor the performance of the web application both " inside " and " outside " the VPN tunnel. It provides visibility into the local Wi-Fi signal strength, the health of the AnyConnect client, and the latency experienced as traffic traverses the VPN headend. This allows engineers to differentiate between a slow home internet connection and an issue with the VPN concentrator.

Deploying ThousandEyes Cloud Agents (Option A) serves as a critical baseline. By running tests from Cloud Agents in the same regions as the remote employees, the engineer can determine if the " internet " in that region is healthy. If a Cloud Agent in London shows a perfect response time while an Endpoint Agent in London shows high latency, the engineer can immediately isolate the problem to the user ' s specific setup or the VPN path, rather than a regional ISP outage.

Other options are less suitable for monitoring the remote employee ' s experience :

AppDynamics (Option B) provides server-side code visibility but cannot see the user ' s home Wi-Fi or local network path.

Enterprise Agents on the VPN concentrator (Option C) can monitor the path from the data center to the app, but they cannot see the path from the user to the concentrator.

Enterprise Agents in the data center (Option E) provide an " inside-out " view of the app ' s health but miss the entire remote access experience.