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| Section | Weight | Objectives |
|---|---|---|
| Deployment and Configuration | 38% | - Prisma SD-WAN Deployment
|
| Operations and Monitoring | 38% | - Monitoring and Troubleshooting
|
| Planning and Design | 24% | - Architecture Design
|
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NEW QUESTION # 50
Which statements accurately describes how the Prisma SD-WAN zone-based firewall functions within a branch network?
Answer: A
Explanation:
The Prisma SD-WAN (ION) device includes a native, application-aware Zone-Based Firewall (ZBFW) that provides comprehensive security within the branch without the mandatory requirement for additional hardware.2 The fundamental principle of this architecture is the grouping of interfaces and sub-interfaces into logical Security Zones.3 Once these zones are defined (e.g., LAN, WAN, Guest, IoT), the administrator can create security policies that govern the traffic permitted to flow between them.4 Unlike traditional routers that rely on stateless Access Control Lists (ACLs) which are difficult to manage and lack application visibility, the Prisma SD-WAN ZBFW is stateful and application-aware.5 This means it can apply granular control over North-South traffic (flows moving between the LAN and the WAN/Internet) and East-West traffic (flows moving between different segments within the LAN, such as from a Guest zone to a Corporate zone).6 By using security zones, an ION device can ensure that even if two local networks are connected to the same physical appliance, they remain completely isolated unless a specific policy explicitly allows communication.
This "Zero Trust" approach at the branch edge allows organizations to segment vulnerable devices (like IoT) from critical internal resources and strictly control how users access the internet or the corporate data center.7 The ZBFW works in tandem with the global controller to ensure that security postures are consistent across all branch locations, eliminating the complexity of manual ACL management at each site.8
NEW QUESTION # 51
When troubleshooting an issue at a site that is running on two cellular links from two carriers, the operations team shared some evidence shown in the graph below:
(SNR Graph showing Carrier-1 in blue dropping to near 0 dB and Carrier-2 in green staying relatively stable between 4.5 dB and 6.5 dB)
For the time duration shown in the graph, what are two inferences about the site's traffic that can be made? (Choose two.)
Answer: A,B
Explanation:
Comprehensive and Detailed Explanation at least 150 to 250 words each from Palo Alto Networks SD-WAN Engineer documents:
In Prisma SD-WAN, the Signal-to-Noise Ratio (SNR) is a critical metric used to monitor the health and performance of cellular WAN interfaces. SNR measures the strength of the desired signal relative to the background noise level; higher values indicate a cleaner signal, while lower values suggest that noise is overwhelming the signal, typically leading to increased packet loss, high latency, and reduced throughput.
Analyzing the provided graph, Carrier-1 (blue line) shows a severe drop in SNR, plummeting from approximately 4.5 dB to nearly 0.3 dB between 15:00 and 23:00. An SNR value this low is indicative of a failing or highly unstable link that cannot reliably sustain data traffic, directly supporting Inference A-that Carrier-1 experienced significant performance degradation. In contrast, Carrier-2 (green line) maintains a much higher and more consistent SNR throughout the same period.
Prisma SD-WAN's AppFabric uses application-based path selection and SLA monitoring to ensure the best possible user experience. When the system detects that a primary path (like Carrier-1) has degraded below acceptable thresholds-often triggered by high loss or latency resulting from poor signal quality-it will dynamically steer application flows to an alternative healthy path. Therefore, Inference D is correct: because Carrier-1's quality became untenable while Carrier-2 remained stable, the ION device would have likely initiated a path switchover to move traffic from the degraded Carrier-1 to the healthier Carrier-2.
NEW QUESTION # 52
A customer wants to deploy Prisma SD-WAN ION devices at small home offices that use consumer-grade broadband routers. These routers typically use Symmetric NAT and do not allow static port forwarding.
Which standard mechanism does Prisma SD-WAN utilize to successfully establish direct Branch-to-Branch (Dynamic) VPN tunnels through these Symmetric NAT devices?
Answer: C
Explanation:
Comprehensive and Detailed Explanation
Prisma SD-WAN utilizes STUN (Session Traversal Utilities for NAT) to facilitate NAT Traversal for its Secure Fabric overlay.
Discovery: When an ION device connects to the internet behind a NAT router, it reaches out to the Prisma SD-WAN Controller. The controller acts as a STUN server, identifying the public IP address and port that the ION's traffic is originating from.
Symmetric NAT Challenge: In Symmetric NAT, the mapping changes for every destination. However, the Prisma SD-WAN architecture is designed to handle this by having the controller coordinate the connection attempt.
Hole Punching: The controller shares the discovered public mapping information between two peer ION devices. They then simultaneously initiate traffic to each other's public IP/Port (a technique called "UDP Hole Punching"). This tricks the intermediate NAT devices into allowing the inbound traffic, establishing a direct P2P IPSec tunnel without requiring manual port forwarding or static IPs at the edge.
NEW QUESTION # 53
In which modes can a Prisma SD-WAN branch be deployed?
Answer: D
Explanation:
Comprehensive and Detailed Explanation
Prisma SD-WAN (formerly CloudGenix) defines three distinct Operational Modes for a branch site, which determine how the ION device processes traffic and interacts with the network.
Analytics Mode (Monitor): In this mode, the ION device is typically deployed inline or in a "promiscuous" monitor state to gain visibility into network traffic without actively enforcing path selection policies.1 It "learns" applications, bandwidth usage, and network characteristics (auditing) but does not steer traffic or block flows.2 This is often used during Proof of Concepts (POVs) or the initial "burn-in" phase of a deployment to generate reports without risking network disruption.
Control Mode: This is the full production state. In Control Mode, the ION device actively enforces Path Policies, QoS Policies, and Security Policies. It builds Secure Fabric VPN tunnels, steers traffic based on application SLAs (e.g., sending voice over MPLS and bulk data over Broadband), and handles failover events.3 This is the required mode for a fully functional SD-WAN site.
Disabled Mode: This mode effectively shuts down the site's SD-WAN functionality from the controller's perspective. It is an administrative state used when a site is being decommissioned, provisioned but not yet live, or isolated for troubleshooting. In this state, the device does not participate in the fabric.
NEW QUESTION # 54
A branch manager reports slow network performance, and the network administrator wants to use Prisma SD- WAN Copilot to quickly identify if a specific user, by source IP address, is consuming excessive bandwidth as well as which applications are contributing to this consumption. How can Copilot assist in this investigation?
Answer: C
Explanation:
Prisma SD-WAN Copilot is an AI-powered operational tool designed to simplify network management through Natural Language Processing (NLP). Traditionally, identifying a bandwidth "hog" required manual navigation through multiple dashboards, such as WAN Clarity and the Flow Browser, to correlate source IP addresses with specific application flows and timestamps. Copilot transforms this workflow by allowing administrators to interact with the system using conversational queries.
When an administrator inputs a query like "Show top bandwidth source IPs at SD-WAN Branch X over last 3 hours," Copilot leverages its underlying machine learning models and integrated data lake to aggregate telemetry across the entire fabric. It instantly identifies the specific source IPs responsible for the highest throughput and correlates that data with application visibility. Instead of providing a static report or redirecting the user to other tools, Copilot presents an interactive, summarized view directly within the interface. This view highlights the top-consuming users and breaks down their consumption by application, such as YouTube, Netflix, or business-critical SaaS tools.
This capability significantly reduces the Mean Time to Resolution (MTTR) for performance issues. By bypassing the need for manual data correlation, Copilot provides immediate "Day 2" operational insights. It effectively acts as a virtual assistant that understands the context of the network topology, site names, and time ranges, allowing the administrator to quickly determine if a branch's slow performance is due to an individual user's behavior or a broader infrastructure issue.
NEW QUESTION # 55
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