What JN0-335 Questions and Answers feature?

The session table is a limited resource for SRX Series devices. If the session table is full, any new sessions will be rejected by the device. The aggressive session-aging mechanism accelerates the session timeout process when the number of sessions in the session table exceeds the specified high-watermark threshold. This mechanism minimizes the likelihood that the SRX Series devices will reject new sessions when the session table becomes full1. To perform aggressive session aging, you need to configure the following parameters1:

• early-ageout –During aggressive session aging, the sessions with an age-out time lower than the early-ageout threshold are marked as invalid. The early-ageout configuration specifies the timeout value, in seconds, that will be applied once the high-watermark value is met. For example, if you set the early-ageout to 30 seconds, any session that has been inactive for at least 30 seconds will be aged out when the high-watermark is reached2.
• high-watermark –The device performs aggressive session aging when the number of sessions in the session table exceeds the high-watermark threshold. The high-watermark configuration specifies the percentage of how much of the session table can be allocated before applying a more aggressive age-out timer. For example, if you set the high-watermark to 90 percent, the device will start aging out sessions more aggressively when the session table reaches 90 percent of its capacity3.

Therefore, the correct statements are B and D.

References: Understanding Aggressive Session Aging high-watermark early-ageout

Based on the information from the exhibit, node0 is the primary node for both redundancy group 0 (RG0) and redundancy group 1 (RG1). RG0 is responsible for the control plane, which includes the Routing Engine and the management interface. RG1 is responsible for the data plane, which includes the interfaces and services. Therefore, node0 is the active node for the data plane, and node1 is the active node for the control plane34 References:

• Chassis Cluster Redundancy Groups | Junos OS | Juniper Networks
• Troubleshooting a Redundancy Group that Does Not Fail Over in an SRX Chassis Cluster | Junos OS | Juniper Networks
• Understanding Chassis Cluster Redundancy Group 0: Routing Engines | Junos OS | Juniper Networks
• Understanding Chassis Cluster Redundancy Groups 1 Through 128 | Junos OS | Juniper Networks

Statistical sampling is a technique that reduces the amount of flow data that is sent to JSA by sampling a subset of packets from the network device. Statistical sampling can help reduce network bandwidth and storage requirements, but it also increases processor utilization on the network device and decreases event correlation accuracy on JSA. Statistical sampling can also affect the accuracy of reports and searches that are based on flow data. Therefore, it is recommended to use statistical sampling only when necessary and with caution12.

BGP FlowSpec is not used to collect traffic flows from Junos OS devices, but to distribute firewall filter rules to routers that participate in BGP. BGP FlowSpec can help mitigate distributed denial-of-service (DDoS) attacks by filtering unwanted traffic based on flow attributes such as source and destination IP addresses, ports, and protocols3.

Superflows are not a method of collecting network traffic flows, but a way of grouping individual flows that match certain criteria into a single record. Superflows can help detect common attack vectors and reduce the number of flows that are stored on JSA. Superflows do not reduce traffic licensing requirements, but they can help optimize the performance and storage of JSA4. References:

• 1: Flow Sources | JSA 7.5.0 | Juniper Networks
• 2: JSA Events and Flows | JSA 7.5.0 | Juniper Networks
• 3: Understanding BGP FlowSpec
• 4: Superflows | JSA 7.5.0 | Juniper Networks