300-445 Exam Dumps - Cisco CCNP Enterprise Questions and Answers

According to theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)curriculum,ThousandEyes WAN Insightsis a predictive analytics solution designed to transform network management from a reactive to a proactive model.10In the scenario provided, the voice quality issues are recurring and peak-hour dependent, indicating a need for optimization rather than just standard real-time alerting.11

The most relevant capability for this scenario isanalyzing historical SD-WAN performance datato generatepath recommendations(Option B). WAN Insights integrates withCisco Catalyst SD-WAN Manager(vManage) andvAnalyticsto ingest massive volumes of telemetry.12It uses advanced statistical models to analyze the performance of all active circuits (MPLS, Internet, etc.) over time. If the system identifies that a different available path consistently delivers a higher Quality of Experience (QoE) or better adherence to the voice SLA during those peak windows, it generates a recommendation to adjust theApplication-Aware Routing (AAR)policy.1314

This predictive approach allows the administrator to fine-tune network policies in advance, ensuring that sensitive traffic like voice is automatically rerouted to the most stable path before the congestion impacts the users. Option A describes standard ThousandEyes synthetic testing, while Option C is incorrect because WAN Insights specifically uses existing SD-WAN telemetry rather tha15n generating its own synthetic voice16probes. Option D and E describe general NMS or security features not specific to WAN Insights' predictive mission. Thus, the proactive recommendation of alternative paths based on historical SLA adherence is the core function of WAN Insights for improving voice quality.171819

In theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)curriculum, troubleshooting endpoint connectivity requires a systematic analysis of local device logs and network environment changes. According to the log message provided inExhibitthere was a specific timeout error when the agent attempted to reach the ThousandEyes backend. The logs explicitly state: Request to: wss://c1.eb.thousandeyes.com/relay/connect timed out: 12002: The operation timed out.

Since the endpoint was relocated to a new network utilizingstatic IP assignment, and other endpoints on the same network are functioning correctly, the issue is highly localized to this specific device's configuration. In a static IP environment, human error during the manual entry of the IP address, subnet mask, default gateway, or DNS server is a common root cause of connectivity failure. If the gateway is incorrect, the agent cannot reach the internet; if the DNS is incorrect, it cannot resolve c1.eb.thousandeyes.com. Therefore, the best way to bring the endpoint online is to verify the accuracy of theIP settingsand test direct connectivity to the ThousandEyes relay URL.

The alternative options do not address the technical evidence found in the logs:

Option A:Moving the device back is a regressive step that does not resolve the need for the device to function in its new location.

Option B:Reinstalling software is a "brute force" method that rarely fixes underlying network-layer misconfigurations like an incorrect static IP.

Option C:A timeout error (12002) indicates a persistent connectivity blockage that will not resolve itself without administrative intervention.

Checking the static IP credentials ensures the device has a valid path to the internet to establish its secure websocket (WSS) connection to the ThousandEyes platform.

Within the framework ofDesigning and Implementing Enterprise Network Assurance (300-445 ENNA), network monitoring is categorized into two primary methodologies: active and passive monitoring.1Active monitoring(Option C) is characterized by the generation of synthetic or "probes" traffic specifically designed to measure network performance.2These probes simulate real-world user activity, such as HTTP requests, DNS queries, or ICMP pings, to baseline performance metrics like latency, jitter, and packet loss.

The core benefit of the active approach is its independence from actual user traffic. By sending a continuous ping or synthetic HTTP probe, an engineer can verify path availability and performance even during off-peak hours when no real users are on the network. In the context of Cisco ThousandEyes—a central platform in the ENNA certification—this is the primary mode of operation for Cloud, Enterprise, and Endpoint agents. For instance, a ThousandEyes network test proactively sends packets to a target IP or URL to visualize the hop-by-hop underlay and overlay paths.

Conversely, options A, B, and D representpassive monitoringtechniques. Passive monitoring involves observing and analyzing traffic that is already traversing the network.3Methods such asSNMP(Option A) provide device-level health data like CPU load and interface utilization, whilepacket captures(Option B) andNetFlow(Option D) analyze the characteristics of existing user flows to determine top talkers or traffic patterns. While passive monitoring is excellent for volume and utilization analysis, it lacks the proactive capability to test a path's performance before a user encounters a failure. Therefore, sending a synthetic probe like a continuous ping is the definitive example of active monitoring.

In theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)curriculum, capacity planning and optimization are driven by telemetry data such as NetFlow. When NetFlow identifies that delay and jitter—metrics highly impactful to real-time traffic—spike during peak hours, it indicates that high-priority packets are competing for resources with bulk data.

The most appropriate recommendation is totune the existing QoS configuration(Option C). This involves adjusting the Queuing and Scheduling policies on the routers to ensure that voice and video traffic (typically marked with EF and AF41/AF42 DSCP values) is serviced before other traffic classes during periods of congestion. This solution is targeted, cost-effective, and directly addresses the observed jitter issues without the need for massive capital expenditure.

Reviewing other options:

Option A:A complete QoS redesign is often unnecessary and too invasive for solving peak-hour jitter if a basic QoS framework is already in place.

Option B:Increasing bandwidth on "all" links is a "brute force" approach that is expensive and fails to address the underlying problem of traffic prioritization.

Option D:Hardware replacement is a last resort and would not resolve delay/jitter if the new hardware still lacks a properly tuned QoS policy.

In theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)curriculum, monitoring modern APIs often requires handling complex authentication flows, such as OAuth 2.0 with specific client credential parameters. The provided exhibit illustrates theHTTP Authenticationoptions available within a standard HTTP Server test: None, Basic, NTLM, Kerberos, and OAuth.

According to the ENNA implementation standards, while the HTTP Server test type supportsOAuth(Option C), its native implementation is limited. Specifically, it is designed to use a pre-existing token or a simple token refresh flow; it does not support the injection of custom parameters in the initial POST request required to obtain a token in many enterprise client-credential scenarios. Basic and NTLM (Options A and B) are legacy protocols that rely on simple username/password headers and cannot facilitate the multi-step token exchange process described.

To fulfill the requirement of a two-step flow (POST for token, followed by GET for resource), engineers must use more flexible test types:

Transaction scripts (Option D):These allow the engineer to write custom JavaScript using the ThousandEyes transaction library to programmatically handle the POST request, parse the resulting JSON token, and then pass that token into the subsequent GET request's header.

API tests (Option E):These are purpose-built for API monitoring and natively support the definition of variables and multi-step requests where the output of one call (the token) serves as the input for the next.

By utilizing these advanced test types, the engineer can successfully navigate complex authentication requirements that the standard HTTP Server test cannot accommodate.

In theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)architecture, a critical design consideration is the impact of the monitoring solution on the production environment. The primary advantage ofpassive monitoring(Option B) is its non-intrusive nature; it provides insights into network performance and traffic composition without injecting additional "synthetic" overhead into the data plane.

Passive techniques—such asCisco Meraki Insight (MI), NetFlow, and SNMP—rely on the telemetry generated by existing user traffic or the device's own control plane. For example, Meraki Insight analyzes HTTP/S flows as they naturally pass through a Meraki MX appliance to derive application performance scores, rather than sending separate probes.5This ensures that the monitoring tool itself does not consume bandwidth or contribute to network congestion, which is particularly vital in bandwidth-constrained branch environments or on high-utilization links.

In contrast,active monitoring(Options A and C) requires the deliberate generation of synthetic traffic, which can potentially skew results if the volume is too high or if the network is already at capacity. While active monitoring is essential for proactive troubleshooting (measuring performance before users complain), passive monitoring is the preferred method for long-term historical analysis of real user experience and infrastructure utilization because it captures what is actually happening on the wire. Option D is a shared capability; both types can measure specific services, but only passive monitoring does so while remaining transparent to the network load. Therefore, the lack of added traffic is the definitive advantage of the passive approach.

Within theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)framework, the transition from "polling" to "streaming" is a major architectural shift. To populate real-time dashboards in external observability platforms likeGrafana,Splunk, orAppDynamics, the architect should utilize theOpenTelemetry (OTel)integration (Option B).

ThousandEyes for OpenTelemetry is a push-based API built on the standardizedOpenTelemetry Protocol (OTLP). Unlike traditional REST API polling (Option A), which retrieves data at fixed intervals and can be subject to rate limiting and latency, the OTel integration allows ThousandEyes to stream granular network metrics as they are collected. These metrics—including latency, loss, jitter, and HTTP response times—are exported in a standardized format that is natively understood by modern observability backends. This allows the platform to populate complex visualizations such as time-series graphs, heatmaps, and multi-metric tables in near real-time, providing a "single pane of glass" view that correlates network performance with application and infrastructure telemetry.

A key advantage of the OTel approach isdata portabilityandcorrelation. By applying metadata tags to ThousandEyes tests, the data can be filtered and categorized within the external dashboard to match the organization's business logic (e.g., grouping by region or application tier). This enables SREs and NetOps teams to quickly identify if a performance dip in an application dashboard correlates with a spike in internet latency measured by ThousandEyes. Options C and D do not provide the streaming data pipeline required for real-time external dashboard population. Thus,OpenTelemetryis the definitive choice for high-fidelity, real-time observability integration.

In the ThousandEyes platform, alert rules are the primary mechanism for notifying operations teams when performance thresholds are breached. When configuring alerts forEndpoint Agent HTTP Server tests, the available metrics are limited to those that the Endpoint Agent captures during its synthetic browser-based or network-layer probes.

The two correct metrics for this test type areResponse Time(Option A) andError Type(Option C).

Response Time:This metric measures the time-to-first-byte. It is essential for detecting degradations in web application performance as seen from the user's specific machine.

Error Type:This allows administrators to trigger alerts based on specific HTTP response codes or protocol errors (e.g., DNS failures or SSL handshake issues).

Other options are incorrect because they apply to different agent types or monitoring layers:

BGP Reachability (Option B):BGP metrics are not applicable to Endpoint Agent tests. These metrics require the BGP route visualization layer, which is typically associated with Cloud or Enterprise Agents monitoring public internet paths.

Interface Throughput (Option D):This is an infrastructure-level metric rather than a synthetic application metric. While ThousandEyes can monitor device health via SNMP, it is not a metric used in a synthetic HTTP Server test.

By utilizing Response Time and Error Type, an architect can ensure that the operations team is alerted as soon as users experience slow loading or actual failures when accessing critical internal or SaaS-based web applications.

Under theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)guidelines, the integration between ThousandEyes andCisco Secure Client(formerly AnyConnect) is designed to provide visibility into the hybrid workforce experience. The integration primarily leveragesnetwork performance data from the user's device(Option C) to diagnose connectivity and application issues.

This data is collected by theThousandEyes Endpoint Agent, which is deployed as a module within the Cisco Secure Client.10The agent captures real-time telemetry from the user's laptop or workstation, includingWi-Fi signal strength,CPU and memory utilization, andlocal network gateway latency. Specifically, for remote users, it monitors the health of the VPN tunnel and the performance of applications as seen from the end-user's vantage point.

When a user reports a "slow application," this integrated telemetry allows IT teams to determine if the root cause is the user's home Wi-Fi, a saturated VPN concentrator, or an issue within the ISP underlay. The agent performsAutomated Session Testing (AST), which maps the network path as soon as a user joins a critical meeting or accesses a SaaS tool, providing a granular view of every hop between the device and the service destination. Unlike hardware configuration data (Option A) or behavioral analytics (Option B), the focus here is strictly on thenetwork performance metricsthat impact digital experience.

Therefore, the collection of device-centric network performance data is the core function of the Cisco Secure Client and ThousandEyes integration.

According to theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)architecture, ThousandEyes provides a suite of native, "out-of-the-box" integrations specifically designed foralert notifications. These integrations are configured via theManage > IntegrationsorAlert Rules > Notificationstabs and allow the platform to push instant event data to a variety of collaboration, IT operations, and observability tools.

The verified list of native notification integrations includes:

ServiceNow (A):Facilitates direct incident management and automated ticketing workflows.

PagerDuty (B):Allows for automated incident escalation and on-call routing based on ThousandEyes alerts.

MS Teams (C) & Slack (H):Enable real-time chatops by pushing alert details and permalinks directly into specified channels for team collaboration.

Splunk (D):Utilizes theCisco ThousandEyes App for Splunkto ingest alert data for historical analysis and correlation within a SIEM or logging platform.

AppDynamics (F):Sends alert notifications directly into an AppDynamics instance, allowing application owners to correlate network issues with APM metrics.12

Webex (G):Integrates with theWebex Control Huband specific Webex spaces to provide unified visibility for collaboration performance.34

AWS (Option E)is not a nativealert notificationdestination5in this context; instead, ThousandEyes integrates with AWS for "Cloud Insights" (ingesting VPC Flow Logs) and "Test Recommendations" rather than acting as a receiver for event notifications like a chat or ITSM tool. By utilizing these native integrations, enterprise teams ensure that the right stakeholders are notified through their preferred communication channels the moment a performance threshold is breached, drastically improving response times across the organization.