Palo Alto Networks (PANW) System Engineer (PSE) Practice Exam

Which Kubernetes auto scaling method is suitable for dynamically adjusting the CN-Series firewall deployment?

1. Horizontal pod auto scaling

2. Vertical cluster auto scaling

3. Cluster auto scaling

4. Namespace auto scaling

The correct answer is: Horizontal pod auto scaling

Horizontal pod auto scaling is the appropriate method for dynamically adjusting the CN-Series firewall deployment within a Kubernetes environment. This method allows for the automatic adjustment of the number of pod replicas based on observed CPU utilization or other select metrics. In the case of the CN-Series firewall, which may experience variable load conditions, horizontal pod auto scaling ensures that the number of active firewall instances can increase or decrease in response to actual traffic demands, maintaining optimal performance and resource utilization. This scaling method is particularly beneficial for applications that need to handle fluctuating workloads, as it enables the deployment to adapt in real-time, ensuring that sufficient resources are available during peak periods and conserving resources when the load decreases. By maintaining the appropriate scalability of the CN-Series firewall through horizontal scaling, organizations can enhance their cybersecurity posture while efficiently managing costs associated with cloud resources. The other choices do not specifically address the dynamic scaling needs of the individual firewall pods. Vertical cluster auto scaling, for instance, adjusts the resources allocated to existing nodes rather than increasing the number of pods. Cluster auto scaling modifies the number of nodes in the cluster instead of scaling the individual pods. Namespace auto scaling is not a recognized Kubernetes feature and does not apply to the context of firewall deployments. Thus, horizontal pod auto scaling stands out