Centrifuge - Open HRMP channels to support USDT, Axelar USDC, aUSD

Hey, Community!

The last referenda was activated on block #1,257,060 and succeeded on Centrifuge. However, for the second time the XCM sent to Polkadot to batching hrmp init channel requests with Statemint, Moonbeam, and Acala has failed on block #12,076,308 , this time with a MaxWeightInvalid error.

This error means that the require_weight_at_most that I had specified in the Transact instruction of the XCM message was too low to cover for the weight costs associated with executing the batch described above.

First, I am sincerely sorry for my mistake. I understand this is frustrating and a bad look on me and it’s totally my bad and I apologise for that.

To get us going further as fast and reliably as possible, I have been in touch with the larger XCM community to have a look at the last failed call and ensure that only the require_weight_at_most was wrong and what conservative value we should set to not have this call failing again.

We learned that a single hrmpInitOpenChannel extrinsic has a weight of 677,297,000; Because we are batching 3, we see a total sum that’s just slightly above 3* that, at a total of

2,063,824,000. To play on the safe side, I am setting the require_weight_at_most to 6,000,000,000 (almost the triple). Any surplus will be refunded.

New PreImage

With that, I have submitted a new pre-image with all the values corrected and double checked.

:point_right: pre-image: 0xdc4ebe26e5131c30b214340d4710c119f50155c1ada855c1ff81efab243d7376

  • WithdrawAsset and BuyExecution with 30,000,000,000
  • Transact require_weight_at_most: 6,000,000,000 - covering expected max weight of 2,063,824,000
  • noted on block #1,261,477

My commitment is to 1) automate the creation of these pre-images to avoid further human error and to ensure that every call I submit as a pre-image is first ran and verified in a local environment that mimics the real one to the exact configuration.

I appreciate your patience and understanding :raised_hand:t2:

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