Your monitoring team reports performance issues with a web application hosted in Azure.

According to theFortiOS 7.6 Azure Administration Guideand theFortinet 7.4 Public Cloud Securitydocumentation regarding monitoring and troubleshooting in Microsoft Azure, administrators must utilize native diagnostic tools to gain visibility into network traffic patterns:

NSG Flow Logs (Option D):Network Security Group (NSG) flow logs are a feature of Azure Network Watcher that allows you to record information about IP traffic flowing through an NSG. These logs capture critical 5-tuple information (source/destination IP, port, and protocol) and whether the traffic was allowed or denied by specific security rules.

Traffic Pattern Analysis with Azure Monitor:To effectively analyze the "pattern" of a traffic spike, these logs are typically sent to aLog Analytics workspacewithinAzure Monitor. By usingTraffic Analytics, the raw flow data is processed into rich visualizations and searchable datasets. This allows administrators to run Kusto Query Language (KQL) queries to identify "top talkers," visualize traffic spikes over time, and correlate the timing of these spikes with application performance degradation.

Identifying Bottlenecks:This method is preferred for identifying bottlenecks because it provides a granular view of every packet entering or leaving the subnets where the FortiGate-VM or application servers are hosted, revealing the exact nature of the inbound volume.

Why other options are incorrect:

Option A:While Azure Firewall provides logging, it is an additional security layer that may not be deployed in all environments. NSG Flow Logs are the primary and more ubiquitous method for monitoring all subnet-level traffic regardless of firewall placement.

Option B:DDoS Protection is apreventativemeasure; it does not provide the historical "identification and analysis" of traffic patterns required to diagnose a past performance bottleneck.

Option C:Azure Traffic Manager is a DNS-based load balancer. While it provides high-level metrics, it does not have visibility into the actual flow-level traffic data needed for a detailed pattern analysis of application bottlenecks.