What action should a cloud engineer take to optimize compute usage if a host is near maximum CPU and memory capacity?

Optimizing compute usage in a scenario where a host is nearing its maximum CPU and memory capacity involves managing workloads effectively. By migrating resource-intensive applications to different hosts, the cloud engineer can balance the load across multiple servers, ensuring that none are overwhelmed and that performance remains optimal. This approach not only alleviates pressure on the already strained host but also enhances overall resource utilization within the cloud environment.

The action of migrating workloads also allows for a more strategic distribution of resources, which can lead to better efficiency and responsiveness from the cloud infrastructure. This helps in maintaining service levels and can significantly reduce the risk of performance bottlenecks or system failures due to resource exhaustion.

Employing automatic scaling or adding additional hosts can also contribute to resource management; however, these options may not be immediate solutions to the problem of a single host's performance being compromised. While increasing the number of hosts or enabling auto-scaling can enhance overall capacity, addressing the immediate workload distribution through migration is often a more targeted and quicker remedy for high CPU and memory usage on one specific host.