What is the recommended approach to ensuring adequate capacity in an Orion Polling Engine deployment?

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Multiple Choice

What is the recommended approach to ensuring adequate capacity in an Orion Polling Engine deployment?

Explanation:
Distributing pollers across multiple servers is the recommended approach because the polling engine’s capacity is tied to hardware resources and how many polls it can handle concurrently. Spreading the workload across several servers lets you scale horizontally, increases total polling throughput, and keeps CPU, memory, and network usage from becoming bottlenecks. It also provides redundancy so if one polling engine fails, others continue collecting data, preserving monitoring coverage. Consolidating polling on a single server would quickly hit its capacity ceiling and create a single point of failure. Disabling caching would likely reduce performance, not increase capacity, since caching helps reduce repeated data retrieval. Disabling polling for critical devices would degrade visibility and isn’t a valid way to improve capacity.

Distributing pollers across multiple servers is the recommended approach because the polling engine’s capacity is tied to hardware resources and how many polls it can handle concurrently. Spreading the workload across several servers lets you scale horizontally, increases total polling throughput, and keeps CPU, memory, and network usage from becoming bottlenecks. It also provides redundancy so if one polling engine fails, others continue collecting data, preserving monitoring coverage. Consolidating polling on a single server would quickly hit its capacity ceiling and create a single point of failure.

Disabling caching would likely reduce performance, not increase capacity, since caching helps reduce repeated data retrieval. Disabling polling for critical devices would degrade visibility and isn’t a valid way to improve capacity.

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