Cisco 300-445 Dumps Questions Answers

In theDesigning and Implementing Enterprise Network Assurance (300-445 ENNA)framework, managing a large-scale deployment of Endpoint Agents requires efficient categorization throughAgent Labels. Agent labels are used to group agents for targeted test assignment and data filtering based on specific attributes like location, OS, or naming conventions.

ThousandEyes supports the use ofwildcards (specifically the * symbol)within label filters to allow for dynamic and scalable grouping. In this scenario, the organization has adopted a naming convention of agentname-network. To capture all agents connected to the "corporate" network regardless of the unique agentname prefix, the engineer should use the filter*-corporate(Option A) in the hostname or agent name field. The asterisk functions as a placeholder for any string of characters, ensuring that any agent ending with "-corporate" is automatically added to the label as soon as it registers with the ThousandEyes platform.

Other options are incorrect for the following reasons:

agentname-* (Option B):This would only match agents that literally start with the string "agentname-", which is a placeholder and not a representative filter for a group of uniquely named agents.

agent*corporate (Option C):This filter is overly broad and lacks the specific hyphen delimiter used in the organization's naming convention, potentially leading to the inclusion of unintended agents.

No wildcard (Option D):Wildcards are a documented and essential feature of the ThousandEyes label system to facilitate automated management in enterprise environments.

By implementing wildcard-based labels, the network administrator ensures that new agents are seamlessly integrated into the assurance strategy without the need for manual manual intervention.

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.