It batches and paces API calls and staggers large operations across time to respect provider rate limits is the correct option.

The service uses batching and pacing to control request volume and to spread heavy work across time so that provider rate limits are honored. This approach reduces the chance of triggering throttling and makes retries and backoff more effective when transient limits are encountered.

By grouping operations and limiting concurrency the product can maintain consistent data collection without overwhelming provider APIs. It also observes provider responses and adapts call frequency so that ongoing scans remain reliable and efficient.

It streams updates through Cloud Pub/Sub to avoid polling APIs is incorrect because Pub Sub is a Google Cloud specific messaging service and cannot generally replace direct API interactions across multiple third party cloud providers. Streaming alone does not solve provider enforced rate limits for management and inventory calls.

It ignores rate limits and continues sending requests at maximum speed until requests are throttled is incorrect because that behavior would produce excessive failures and incomplete data. Respecting limits prevents repeated throttling and reduces wasted retries.

It attempts to gather all necessary data with one consolidated API call is incorrect because most cloud providers do not offer a single call for all needed data and responses can be too large or incomplete. Practical solutions instead break work into paced batches and use targeted calls while managing rate limits.

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