Got a warning for my blog going over 100GB in bandwidth this month... which sounded incredibly unusual. My blog is text and a couple images and I haven't posted anything to it in ages... like how would that even be possible?
Turns out it's possible when you have crawlers going apeshit on your server. Am I even reading this right? 12,181 with 181 zeros at the end for 'Unknown robot'? This is actually bonkers.
Edit: As Thunraz points out below, there's a footnote that reads "Numbers after + are successful hits on 'robots.txt' files" and not scientific notation.
Edit 2: After doing more digging, the culprit is a post where I shared a few wallpapers for download. The bots have been downloading these wallpapers over and over, using 100GB of bandwidth usage in the first 12 days of November. That's when my account was suspended for exceeding bandwidth (it's an artificial limit I put on there awhile back and forgot about...) that's also why the 'last visit' for all the bots is November 12th.
What is that log analysis tool you are using in the picture? Looks pretty neat.
It's a mix, I put two screenshots together. On the left is my monthly bandwidth usage from CPanel on the right is Awstats (though I hid some sections so the Robots/Spiders section was closer to the top).
I thought I recognized it. Hell of a blast from the past, haven't seen it in fifteen years at least.
I think they're winding down the project unfortunately, so I might have to get with the times...
I mean, I thought it was long dead. It's twenty-five years old, and the web has changed quite a bit in that time. No one uses Perl anymore, for starters. I used Open Web Analytics, Webalizer, or somesuch by 2008 or so. I remember Webalizer being snappy as heck.
I tinkered with log analysis myself back then, peeping into the source of AWStats and others. Learned that a humongous regexp with like two hundred alternative matches for the user-agent string was way faster than trying to match them individually — which of course makes sense seeing as regexps work as state-machines in a sort of a very specialized VM. My first attempts, in comparison, were laughably naive and slow. Ah, what a time.
Sure enough, working on a high-traffic site taught me that it's way more efficient to prepare data for reading at the moment of change instead of when it's being read — which translates to analyzing visits on the fly and writing to an optimized database like ElasticSearch.