I thought data caps for home internet were a thing of the past…
I’ve somewhat recently moved back to a very rural area of the Midwest. Small town. No stop lights. Biggest businesses other than the bars are Casey’s, Subway, and Dollar General.
And we have one ISP (not counting DSL) — Mediacom. When we first signed up, I had to go with the second service tier. But not because of speeds, but so I could have a reasonable 1 TB/mo data cap.
Lucky me, they increased the cap to 1.5 TB. 🙄
I hope that in my lifetime I can see ISPs regulated as a public utility.
I’ve used to temporarily live with 100mbps internet (~95mbps up/down). What really helped me:
CAKE queue (QoS stuff) - every device gets fair share of internet.
Since I was lucky to have static speeds - bufferbloat was also eliminated.
QoS - my seedbox had only a spare internet. Which means if everyone/me uses internet at max, then seedbox would have literaly 0 bits per second throughput, and would get it once there is spare throughput available.
Local DNS-based adblocker. I prefer blocky, but others prefer Pi-Hole. Blocky has a feature to pre-cache commonly used domains, so additional internet performance. :)
Local DNS-based adblocker. I prefer blocky, but others prefer Pi-Hole. Blocky has a feature to pre-cache commonly used domains, so additional internet performance. :)
Blocky is written in Go, which I understand is an interpreted language program, versus a compiled language program. Please correct me on this if I’m wrong.
If I’m right, then what kind of performance issues if any do you see using Blocky? I asked this assuming that an interpreted program will run slower than a compiled one.
Blocky is written in Go, which I understand is an interpreted language program, versus a compiled language program. Please correct me on this if I’m wrong.
Yup, you are completelly wrong.
If I’m right, then what kind of performance issues if any do you see using Blocky? I asked this assuming that an interpreted program will run slower than a compiled one.
N/A
Go is awesome. My favorite programming language. <3
Blocky has the same functionality, but it also detects which domains are frequently requested, therefore puts them into “always keep up to date in cache”.
Basically let’s say that many devices keep requesting for “google.com”, blocky detects it as frequently reqiested domain, and as soon as it expires, instead of removing from cache, blocky simply refreshes it’s value and keeps in cache. Expires again? Refresh and keep in cache again. And does this idefinitely.
Let’s say “google.com” TTL time is 10 minutes. Once 10 minutes passes - blocky should remove it from cache, but because precatching is enabled - it will refresh it instead of removal.
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I’ve used to temporarily live with 100mbps internet (~95mbps up/down). What really helped me:
Blocky is written in Go, which I understand is an interpreted language program, versus a compiled language program. Please correct me on this if I’m wrong.
If I’m right, then what kind of performance issues if any do you see using Blocky? I asked this assuming that an interpreted program will run slower than a compiled one.
Yup, you are completelly wrong.
N/A
Go is awesome. My favorite programming language. <3
To confirm, Go is a compiled language?
Yes, just like rust. It compiles into a single binary.
Thanks.
https://0xerr0r.github.io/blocky/v0.21/ This? I’ll have to give it a try later. Pihole has a cache also though, does this do something different?
Yes, this one.
The cache you are referring to is basically:
Blocky has the same functionality, but it also detects which domains are frequently requested, therefore puts them into “always keep up to date in cache”.
Basically let’s say that many devices keep requesting for “google.com”, blocky detects it as frequently reqiested domain, and as soon as it expires, instead of removing from cache, blocky simply refreshes it’s value and keeps in cache. Expires again? Refresh and keep in cache again. And does this idefinitely.
Let’s say “google.com” TTL time is 10 minutes. Once 10 minutes passes - blocky should remove it from cache, but because precatching is enabled - it will refresh it instead of removal.
Check documentation for details. ✌️
Very cool thank you!