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I'm using this library in a database that timestamps data entries. When inserting data asynchronously, this means many OTS requests happen at once. One of the problems with this is an explosion of DNS requests, which slows things down and also puts load on the DNS server. In my case I actually hit my Pi-Hole rate limit.
Here are some screenshots from my DNS server (Pi-hole) showing the issue:
I will be rate-limiting my code to reduce load on the calendar servers too, but I just wanted to flag that if there's a way to do DNS caching that would be helpful.
Notably many of the requests were for AAAA ots.btc.catallaxy.com, which (1) doesn't exist and (2) isn't relevant because I am on an IPv4-only network.
The text was updated successfully, but these errors were encountered:
Hi @makew0rld , do you use the library on your local npm project or in a web page?
You could reduce the number of requests by passing to the stamp() function the list of calendars you want to use; with a list of calendars you could avoid to use ots.btc.catallaxy.com (if you don't need it) and avoid too make 3/4 requests with 3 proofs for each stamp.
I'm using this library in a database that timestamps data entries. When inserting data asynchronously, this means many OTS requests happen at once. One of the problems with this is an explosion of DNS requests, which slows things down and also puts load on the DNS server. In my case I actually hit my Pi-Hole rate limit.
Here are some screenshots from my DNS server (Pi-hole) showing the issue:
I will be rate-limiting my code to reduce load on the calendar servers too, but I just wanted to flag that if there's a way to do DNS caching that would be helpful.
Notably many of the requests were for
AAAA ots.btc.catallaxy.com
, which (1) doesn't exist and (2) isn't relevant because I am on an IPv4-only network.The text was updated successfully, but these errors were encountered: