Best practices for handling rate limits when using the REST API for frequent polling

[AayuAmor]

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Hi everyone,

I'm working on an integration that uses GitHub's REST API to poll for updates on issues and pull requests every few minutes.

I understand that there are rate limits in place, and I'm looking for best practices or recommended strategies to stay within those limits while still keeping data relatively fresh.

Some specific questions I had:

Is there a preferred way to reduce API calls, like using conditional requests (ETags)?

Would webhooks be more efficient for this use case?

Are there known patterns or tools that help manage GitHub API rate limits effectively?

I’d love to hear how others have approached this, or if GitHub recommends a specific method for frequent syncs.

Thanks in advance!

[MaNoLiN-CRV]

I think webhooks will be the best option.
You will reduce the network traffic notoriously, save system resources and decrease system logic complexity.

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[jcodes101]

Hi @AayuAmor 👋 Great questions — you're thinking in exactly the right direction.

Polling GitHub’s REST API can work, but to keep things efficient and stay within rate limits, here are some best practices and answers to your specific points:

✅ 1. Yes — Use Conditional Requests (ETags)
GitHub REST API supports ETags and the If-None-Match header, which lets you ask:

"Has this resource changed since I last saw it?"

If nothing changed, GitHub returns 304 Not Modified — which doesn’t count against your rate limit.

✅ Recommended: Store ETags from responses and reuse them in future requests.

Docs: https://docs.github.com/en/rest/overview/resources-in-the-rest-api#conditional-requests

✅ 2. Yes — Webhooks Are More Efficient (When Available)
If you're polling for changes like:

New issues / PRs

Status updates

Comments or label changes

➡️ GitHub webhooks are the preferred approach. They're real-time, lightweight, and don't count against rate limits.

Downside: You’ll need a public server or service (like ngrok or a cloud function) to receive the POST requests.

Docs: https://docs.github.com/en/webhooks

✅ 3. Known Patterns & Tools
Backoff + Throttling: Always check the X-RateLimit-Remaining and X-RateLimit-Reset headers, and back off when close.

Efficient Polling: If polling is your only option (e.g. rate-limited orgs, legacy infra), space out requests using a priority queue and differentiated polling intervals (e.g., active PRs every 5 min, stale ones every 30).

Caching Layer: Use a lightweight cache or state store so your app only calls GitHub when data is actually stale.

Libraries: If you're using Node, Python, etc., some GitHub API clients already support ETag handling and rate limit backoff (e.g. octokit for JS).

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[Tanishq-S-Dev05]

Hi @AayuAmor 👋

Great question — you’re right that polling every few minutes can hit GitHub’s REST API rate limits pretty quickly. A few strategies that usually help:

==Use conditional requests (ETags / If-None-Match headers):
This way, GitHub will only send a full response if something has changed. If not, you’ll get a lightweight 304 Not Modified response, which doesn’t count as heavily against your rate limit.

==Prefer webhooks where possible:
Instead of polling, webhooks push updates to you in real time. For issues, pull requests, and most repository events, webhooks are much more efficient and scale better.

==Combine REST with GraphQL if needed:
GraphQL lets you batch related queries into a single call, reducing the number of requests.

==Use caching and backoff strategies:
Cache responses where possible and increase your polling interval if you’re nearing the rate limit. Some people also implement exponential backoff to avoid bursts.

==Tools & patterns:
Many integrations rely on webhooks for event-driven updates and fall back to periodic REST polling (with conditional requests) only as a safety net.

If your integration requires “near real time” updates, the best practice is usually webhooks first + occasional syncs via conditional requests to catch anything that might have been missed.

Hope this helps you design a reliable sync strategy 🚀

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