RPC Rate Limits Causing Unreliable Transactions on Polygon

Developers
1

Hello

I’ve been running a high-frequency transaction script on Polygon & I’m facing intermittent failures due to RPC rate limits. Sometimes; transactions fail to broadcast or get stuck in a pending state for an unusually long time, even when gas fees are appropriate. :upside_down_face: Other times; I receive 429 Too Many Requests errors, despite spacing out requests within the advertised limits.

This issue is especially problematic when interacting with smart contracts requiring multiple sequential calls; as one failed request can disrupt the entire process.
I’ve tested multiple RPC providers; including public and private nodes, but the issue persists, particularly during high network congestion. :innocent:

I suspect that Polygon’s public RPCs may have hidden rate limits beyond what’s officially documented. Another concern is whether fallback RPCs can be configured dynamically to avoid disruptions when one provider enforces stricter limits. :innocent: Checked https://docs.polygon.technology/pos/reference/rpc-endpoints/selenium training online guide related to this and found it quite informative.

Has anyone else encountered unreliable transaction handling due to RPC rate limits? :thinking: Are there any best practices for managing high-frequency interactions with Polygon’s network? :thinking: I’d appreciate insights from other developers on how to ensure smooth transaction execution.

Thank you!! :slightly_smiling_face:

3

You should always use private, paid RPC endpoints for high frequency calls - Tenderly can serve your needs quite well. In addition to paying for RPC endpoint reliability, I also recommend you use Bundlers (like Bundler3) to execute batch calls at once in an atomic fashion (will undo all TXs if one fails) and to reduce the number of RPC calls you need to make. This will also make it cheap and easy to do retries if you run into 429 or gas issues (which sadly do still occur, but are being worked on).

4

A 429 can come from the provider’s per-IP or per-method limits and not only from the headline request rate, so spacing calls evenly may not be enough. It usually helps to batch read calls into one JSON-RPC batch request, cache anything that does not change between blocks, and back off with a short random delay after each 429. For broadcasting, a client-side list of two or three RPC endpoints that you rotate on failure works well, as long as you keep a single nonce counter in your own code so a retry on another node does not reuse or skip a nonce. Stuck pending transactions are often a nonce or gas-price issue as well, so it is worth logging both for every send.