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There is no universal polling interval or request quota for health monitoring APIs. Follow the specific API’s quota and freshness rules, honor Retry-After, and use bounded backoff with jitter for eligible transient failures. Stop when the retry budget expires, and automatically repeat only requests that are safe to repeat.
How often should you poll a health monitoring API?
Use the API’s documented quota, quota scope, reset behavior, and data-freshness constraints to choose an interval. HTTP defines no general polling frequency, and a 429 response does not establish one: the server decides how it identifies callers and counts requests. Limits may apply per user, project, key, endpoint, resource, or another grouping. See RFC 6585.
- Check the endpoint documentation for request limits and any remaining-quota or reset headers.
- Do not request updates more often than the product’s data freshness warrants.
- Spread scheduled polls across the allowed window instead of synchronizing clients at the same moment.
- If multiple workers share a quota, coordinate their request rate with a shared client-side limiter.
- Where the endpoint supports them, consider conditional requests, pagination, rollups, or batch operations to reduce calls.
Provider figures are service-specific, not generic health API limits. For example, Google Health’s documentation lists defaults of 86.4 million requests per day per project, 120,000 requests per minute per project, and 300 requests per minute per user. Those published figures are subject to change; check the Google Health API limits before relying on them.
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What should your client do when it receives an error?
429 Too Many Requests
Pause requests in the quota scope affected by the provider’s policy. If the response includes Retry-After, schedule the next attempt no earlier than the indicated time. If it does not, follow the API’s documented policy or use bounded backoff; do not retry immediately. RFC 6585 defines 429 as too many requests in a given period and permits the server to include Retry-After, but does not prescribe a universal counting method.
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503 and other documented transient failures
Use provider instructions and bounded backoff for failures the API documents as transient. RFC 9110 describes 503 as temporary inability to handle a request, such as during overload or maintenance, and allows a server to send Retry-After. See RFC 9110.
Authentication, permission, validation, and not-found errors
Repeating an identical request usually will not fix a bad credential, missing permission, invalid argument, or absent resource. Check the API’s error contract, correct the underlying issue, or surface the error instead of retrying blindly. Google Cloud Monitoring distinguishes these classes from quota and transient backend errors in its Monitoring API troubleshooting guidance.
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Sustained overload or an exhausted volume quota
More retries may add load without restoring capacity. Reduce polling frequency or concurrency, queue work, or batch requests if the endpoint supports it. Google Cloud’s guidance notes that retrying is not useful for some exhausted volume quotas; a time-based limit may recover after a wait, but an exhausted volume allowance may not.
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For retryable failures without a more specific server wait, increase the delay exponentially, add random jitter, cap the delay, and enforce both an attempt limit and an overall deadline. Jitter helps prevent clients that failed together from retrying together.
- Classify the response against the API’s documented retry policy.
- If a valid
Retry-Afteris present, parse it as either an HTTP date or a delay in seconds, as specified by RFC 9110, and schedule no earlier than that time. - Otherwise, choose an exponential delay with independent random jitter and a maximum cap suitable for the application’s latency and quota requirements.
- Before scheduling, check the remaining attempt budget and total retry deadline. If the server’s requested wait exceeds that deadline, defer the work or report a bounded failure rather than retrying early.
- On exhaustion, surface the failure or hand it to a controlled queue; do not loop indefinitely.
A sequence such as 1, 2, 4, then 8 seconds plus a small random component illustrates exponential growth, not a universal policy. Google Cloud Monitoring gives a 1-to-32-second example for specified transient errors. Google Cloud Healthcare documentation gives 32 or 64 seconds as typical maximum-backoff examples. Use those figures only when the relevant service guidance applies: Google Cloud Monitoring and Google Cloud Healthcare API best practices.
For retries that must survive process restarts or span multiple workers, persist retry state in a durable queue. Google Cloud Healthcare recommends persistent retry queues for longer-term or multi-process handling.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which requests are safe to retry?
Polling typically uses GET to read a current representation, so repeating that read is generally appropriate. Do not assume the same for state-changing requests. A repeated write can create duplicate records or effects if the first request succeeded but its response was lost.
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When should you stop retrying and escalate?
Set a maximum number of attempts and a total elapsed-time deadline that fit the user experience or background job. On exhaustion, record enough context to diagnose the failure and either report it or route it to a controlled queue.
- Endpoint and response status
- Request correlation ID, if supplied
- Quota or rate-limit headers
- Attempt count and total elapsed time
- Backoff duration and retry queue depth and age, where applicable
Google Cloud Monitoring recommends stopping after a configured attempt count or reasonable elapsed time. NHS England Digital likewise advises against retrying indefinitely and says retry counts should follow API-specific guidance or the needs of the use case: RESTful API guidance for developers. Google Cloud Healthcare specifically recommends monitoring retries, queue size, and queue age in its data-throughput best practices.
Quick Recap
What to verify in an API contract
- Quota: its scope, counting rules, reset behavior, and any headers exposing remaining capacity.
- Retry guidance: whether
Retry-Afteris returned and how the provider classifies transient errors. - Freshness: the expected update cadence or sampling constraints for the data.
- Safety: which operations are idempotent and whether writes support deduplication.
- Efficiency: support for batching, rollups, pagination, or conditional reads.
- Operations: whether retries need durable queues and what telemetry is available.
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