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Cisco 300-445 Exam (page: 1)
Cisco Designing and Implementing Enterprise Network Assurance
Updated on: 17-Feb-2026

Access free 300-445 actual exam questions, answers, explanations and user discussions.

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300-445 PDF with 68 Questions

QUESTION: 1

Exhibit:

An engineer works to optimize a website by reducing the page-load time to below 500 ms. The engineer set up a Cisco ThousandEyes page-load test to baseline the current website performance.
Which action should be recommended to reduce page-load time?

Optimize the AJAX query calling functions.
Move IMG elements to the bottom of the document body.
Implement lazy loading for objects on the page.
Use a CDN to load fonts faster.

Answer(s): C

Explanation:

In the context of Designing and Implementing Enterprise Network Assurance (300-445 ENNA), analyzing page-load metrics within Cisco ThousandEyes requires identifying the primary bottlenecks that contribute to the Total Page Load Time. The provided screenshot displays a "Page Breakdown" of 7 resources totaling 953 kB. A critical observation of the pie chart reveals that Images (the teal- colored segment) constitute the vast majority of the page's payload and resource count.

When the goal is to reduce the page-load time from 1023 ms to below 500 ms, the engineer must target the heaviest components. Lazy loading is a design pattern that defers the initialization of non- critical resources at page load time. Instead of loading all images simultaneously when the user first navigates to the URL, lazy loading ensures that images are only downloaded as they are about to enter the viewport. This significantly reduces the initial DOM load time and the total Page Load Time because the browser does not have to wait for large image files to be fully retrieved before declaring the page "loaded."

Alternative options are less effective in this specific scenario based on the data:

AJAX (XHR/Fetch): The chart shows that XHR and Fetch resources represent a negligible sliver of the total weight; optimizing them would yield minimal gains.

Moving IMG elements: While moving scripts to the bottom can help with rendering, moving image elements to the bottom of the body does not stop the browser from initiating the download requests immediately, thus failing to significantly reduce the total load time.

CDN for Fonts: The "Font" category is also a small fraction of the total 953 kB. While a CDN is a best practice for latency, it does not address the primary "weight" issue caused by the images.

Therefore, implementing lazy loading (Option C) is the most impactful recommendation. It directly addresses the largest resource consumer (Images) identified in the ThousandEyes Page Breakdown, allowing the engineer to reach the sub-500 ms performance target.

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QUESTION: 2

Refer to Exhibit:

A network engineer is deploying a Cisco ThousandEyes agent to monitor the network for a SaaS application without affecting the performance of the employee endpoints.
Which ThousandEyes agent must be deployed to obtain the network metrics from branch A?

Endpoint Agent
Application Agent
Enterprise Agent
Cloud Agent

Answer(s): C

Explanation:

In the framework of Designing and Implementing Enterprise Network Assurance (300-445 ENNA), selecting the appropriate ThousandEyes agent type is critical to balancing visibility requirements with infrastructure constraints. For Branch A, the primary objective is to gain network-layer metrics

(such as latency, packet loss, and jitter) and path visualization for a SaaS application while strictly avoiding any performance impact on employee endpoints.

The Enterprise Agent (Option C) is the correct choice because it is designed for "inside-out" monitoring from within the corporate network environment. These agents are lightweight software probes that can be deployed on existing network infrastructure, such as Cisco Catalyst 9300/9400 switches or Catalyst 8000 Edge Platforms, using Docker containers or virtual machines. By hosting the agent on the branch router or a dedicated local server, the engineer can execute synthetic tests to the SaaS provider's destination. This approach provides the necessary network vantage point from Branch A without requiring any software installation or resource consumption on the individual employee workstations (endpoints).

Other agent types do not satisfy the specific constraints of this scenario:

Endpoint Agents are installed directly on user devices (Windows/macOS) to provide "last-mile" visibility. However, they use the endpoint's CPU and memory, which contradicts the requirement to not affect endpoint performance.

Cloud Agents are maintained by Cisco in global ISP data centers.
While they provide "outside-in" visibility, they cannot capture internal branch network characteristics or the specific path from Branch A's internal local area network.

Application Agent is a non-standard term and does not exist as a standalone agent type within the ThousandEyes architecture.

Therefore, deploying an Enterprise Agent within the branch infrastructure ensures that the network engineer obtains high-fidelity network metrics while keeping employee devices entirely unburdened.

Introduction to ThousandEyes

This video provides an essential overview of how ThousandEyes agents function within a CCNP-level enterprise network assurance strategy.

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QUESTION: 3

Refer to the exhibit.

Which integration type should be configured between ThousandEyes and Grafana?

opentelemetry
custom-webhook
push-api
poll-api

Answer(s): A

Explanation:

In the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) curriculum, the evolution of network monitoring includes moving from periodic polling to real-time data streaming. The exhibit displays a curl command targeting the ThousandEyes API v7 /stream endpoint.
When integrating ThousandEyes with high-performance observability platforms like Grafana, the standardized and recommended method for machine-to-machine data exchange is through OpenTelemetry (OTel).

According to the ENNA architecture guidelines, the ThousandEyes Streaming API allows users to push granular test metrics (such as network latency, packet loss, and jitter) to external collectors in an OTel-compatible format. In the provided JSON payload, the "type" field is a mandatory parameter that defines the integration protocol. For Grafana, which natively supports OpenTelemetry Protocol (OTLP) via its OpenTelemetry Collector, the value must be set to "opentelemetry" (Option A). This tells the ThousandEyes streaming engine to encapsulate the data according to the OTel semantic conventions, ensuring that Grafana can correctly interpret and visualize the metrics without additional custom parsing logic.

While other options exist in the ThousandEyes ecosystem, they do not fit the specific API call shown for this use case:

Custom Webhooks (Option B) are typically used for event-driven alerts and notifications (e.g., sending a POST request when a threshold is breached) rather than continuous high-fidelity metric streaming.

Push-api and poll-api (Options C and D) are not valid "type" values within the context of the v7 /stream endpoint, as the streaming service specifically utilizes the OpenTelemetry framework for real-time delivery.

By selecting opentelemetry, the network engineer enables a robust "push-based" integration that provides real-time visibility into application performance and network health, leveraging Grafana's advanced dashboarding capabilities to analyze ThousandEyes telemetry data alongside other enterprise infrastructure metrics.

Introduction to ThousandEyes for OpenTelemetry

This video provides a foundational understanding of how ThousandEyes uses modern streaming frameworks to export critical performance data to external observability platforms.

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QUESTION: 4

DRAG DROP

Drag and drop the Cisco Network Assurance platforms from the left onto the corresponding business cases on the right.

See Explanation for the Answer.

Answer(s): A

Explanation:

AppDynamics

Catalyst Center

ThousandEyes

Meraki

In the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) architecture, each platform is positioned to address a distinct domain of visibility and management within the modern IT visibility framework.

AppDynamics (matched to Case 1) is specifically engineered for Full-Stack Observability and Application Performance Monitoring (APM). Its unique focus is linking technical application performance--such as code-level execution and database queries--directly to business outcomes and real-time business metrics. By doing so, it allows organizations to pinpoint how application latency impacts revenue or user satisfaction, making it the primary choice for business impact analysis.

Catalyst Center, formerly DNA Center (matched to Case 2), serves as the foundational controller for campus and enterprise network infrastructure. It leverages AI-driven insights to automate network operations, enforce security policies, and provide at-a-glance health monitoring for local devices and clients. It is the definitive management system for connecting and securing "inside" the corporate network perimeter.

ThousandEyes (matched to Case 3) provides "Internet Intelligence" and is the key solution for monitoring the service delivery chain across environments the enterprise does not own. By utilizing a global network of Cloud, Enterprise, and Endpoint agents, it provides end-to-end visibility from any user location to any application (SaaS or Cloud) over any network (Internet, ISP, or WAN).

Meraki (matched to Case 4) is a cloud-first platform designed for managing highly distributed network environments and IoT deployments. It provides end-to-end visibility through a simplified dashboard that integrates wireless health, switching, and security across thousands of sites, making it ideal for lean IT teams managing distributed retail or branch locations.

Each platform utilizes different data collection methods--active synthetic testing for ThousandEyes and passive monitoring/AI telemetry for Catalyst Center--to ensure comprehensive network assurance across the entire enterprise ecosystem.

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QUESTION: 5

Refer to the exhibit.

An engineer must use Cisco ThousandEyes testing to monitor their Cisco Catalyst SD-WAN fabric.
Which SD-WAN component is being monitored by ThousandEyes?

underlay
IPsec tunnels
overlay
GRE tunnels

Answer(s): A

Explanation:

In the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) curriculum, understanding the visibility gap between the SD-WAN overlay and the transport underlay is a core competency. The provided exhibit illustrates a ThousandEyes Enterprise Agent deployed on a Branch Edge Router performing tests across two distinct paths: Internet (reaching a destination at 64.100.249.90) and MPLS (reaching a destination at 172.29.0.2).

According to the ENNA architecture guidelines, ThousandEyes is primarily utilized to provide hop-by- hop visibility into the underlay network.
While SD-WAN controllers like vManage provide native monitoring for the overlay--the logical IPsec tunnels (Option B) that form the SD-WAN fabric--they often lack granular visibility into the physical service provider paths (the underlay) that carry those tunnels. The exhibit specifically highlights the agent probing the transport networks (Transport VPN0) directly, bypassing the overlay tunnels to measure the raw performance of the ISP and MPLS circuits.

By monitoring the underlay (Option A), the engineer can identify if high latency or packet loss is caused by a specific hop within the service provider's infrastructure or at a peering point. This "underlay visibility" is critical for troubleshooting SD-WAN performance issues where the overlay may report a tunnel down, but the root cause lies in a BGP routing change or physical fiber cut in the provider network. ThousandEyes Enterprise Agents, natively integrated into Catalyst 8000 and ISR 4000 platforms, allow for this persistent underlay monitoring without additional hardware.

Overlay (Option C): While ThousandEyes can monitor overlay performance, the exhibit's focus on the raw IP addresses (Internet and MPLS) in the transport VPN indicates an underlay test.

IPsec/GRE Tunnels (Options B & D): These represent the transport mechanisms of the overlay. ThousandEyes probes the path under these tunnels to ensure the transport health is sufficient to support the fabric.

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QUESTION: 6

An engineer deployed a Cisco ThousandEyes Enterprise Agent on a Meraki MX to monitor a critical SaaS application.
Which kind of monitoring has the engineer set up?

active monitoring
passive monitoring
agentless monitoring
server monitoring

Answer(s): A

Explanation:

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.

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QUESTION: 7

Refer to the exhibit.

An engineer must configure Cisco ThousandEyes SSO to use Microsoft Entra ID using the configuration shown in the exhibit.
Which feature must be set to override to complete the configuration?

Service Provider Issuer
Logout Page URL
Login Page URL
Identity Provider Issuer

Answer(s): D

Explanation:

In the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) architecture, secure administrative access via Single Sign-On (SSO) is a critical component of platform governance. The exhibit illustrates the ThousandEyes SSO configuration panel being integrated with Microsoft Entra ID (formerly Azure AD).
When configuring SAML-based authentication, the "Identity Provider Issuer" (Option D) is a unique identifier provided by the IdP (Microsoft) that must match exactly between the two systems.

According to ENNA implementation guidelines, ThousandEyes populates default fields based on standard SAML metadata. However, Microsoft Entra ID often utilizes a specific GUID-based format for the Issuer URL (e.g., https://sts.windows.net/tenant-id/) that may differ from the generic URL format expected by the platform's initial auto-fill. To ensure a successful SAML handshake, the engineer must select the "Override" checkbox next to the Identity Provider Issuer field. This action unlocks the field, allowing the engineer to manually paste the exact string provided in the Entra ID Federation Metadata document. If this value is not overridden and matched precisely, the SAML assertion will be rejected, resulting in a failed authentication attempt.

While the Login and Logout URLs (Options B and C) are also critical, they are typically correctly identified during the initial setup or metadata import; the Identity Provider Issuer is the most frequent point of mismatch requiring an manual override in Entra ID environments due to its strict "Audience Restriction" requirements. The Service Provider Issuer (Option A) is generally a fixed value (https://app.thousandeyes.com) that rarely requires overriding as it defines ThousandEyes' own identity to the IdP.

Therefore, selecting the override for the Identity Provider Issuer is the necessary step to complete the integration and allow enterprise users to authenticate securely using their corporate credentials.

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QUESTION: 8

An architect needs to analyze network path metrics from their internal network, specifically from the access layer to a cloud-hosted web server.1 Which ThousandEyes agent is most appropriate for this task?

Synthetic Agent
Enterprise Agent
Cloud Agent
Endpoint Agent

Answer(s): B

Explanation:

In the framework of Designing and Implementing En8terprise Network Assurance (300-445 ENNA), selecting the correct agent type depends heavily on the vantage point required for the specific observation. For this scenario, the architect must collect metrics from the internal network access layer--the point closest to where the users or devices reside within the corporate perimeter-- towards a cloud-hosted destination.

The Enterprise Agent (Option B) is the most appropriate choice because it is specifically designed to be deployed on infrastructure owned and managed by the organization. These agents are "inside- out" vantage points that can be installed directly on Cisco Catalyst 9300 or 9400 Series switches at the access layer using Docker containers. By deploying an Enterprise Agent at the access layer, the architect gains visibility into the entire network path, starting from the internal LAN, traversing the edge/WAN, and reaching into the cloud-hosted web server. This allows for the identification of issues such as local congestion, ISP peering problems, or cloud provider latency.

Other options do not meet the criteria:

Synthetic Agent (Option A): This is a distractor term. All ThousandEyes agents (Cloud, Enterprise, and Endpoint) are synthetic agents because they all perform active synthetic testing.

Cloud Agent (Option C): These are pre-deployed by Cisco in global ISP data centers and provide an "outside-in" view.14 While useful for monitoring public-facing availability, they cannot provide visibility into the internal network or the access layer of the organization.

Endpoint Agent (Option D): While these are installed on end-user machines and provide a "user- centric" view, they are generally not used for infrastructure-level path analysis from the access layer switches themselves.

Thus, the Enterprise Agent is the definitive choice for monitoring from the access layer to the cloud.

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