Refer to the exhibit. How does the architecture respond to a usage spike?

This describes a standard autoscaling mechanism: monitoring detects high load, triggering the orchestrator (e.g., Kubernetes) to provision more container instances (horizontal scaling). The load balancer is then automatically configured to distribute incoming traffic across both existing and newly created containers, effectively handling the usage spike.

Database query prioritization is an internal database optimization technique and not the primary architectural response for scaling an application tier in a containerized environment to handle usage spikes.

Increasing resources assigned to *existing* containers is vertical scaling, which is less common and often less effective for handling sudden usage spikes in a distributed, containerized architecture compared to horizontal scaling by adding more instances.

While a load balancer optimizes traffic distribution, it typically doesn't directly interact with the orchestrator to *increase* resources; its role is to direct traffic to *available* resources, which the orchestrator manages based on monitoring signals.