Bot traffic: austinfestivalcalendar.com

all sites · all domains · last 15 days

All sites · All Domains · Visit austinfestivalcalendar.com

Who is really visiting austinfestivalcalendar.com?

Between Oct 23 and Nov 6, austinfestivalcalendar.com received 44,253 requests. About 99.1% came from automated software and about 0.3% look like real people.

That works out to about 68 human visitors, roughly 5 a day, who opened 93 pages between them. 24 of them read more than one page.

The biggest source is scanners hunting for security holes. They try the same list of common weak spots on every site they find.

Bottom line: the hit counts on the All Domains worksheet are almost entirely bots. Use the human visitor figure here to judge this site's real audience.

99.1%of requests from bots
68human visitors (estimate)
93pages opened by people
44,253total requests, 15 days

Where the requests came from

People 0.3%Named bots 11%Disguised bots 9.6%Scanners 78%Unclear 0.6%

Requests per day

PeopleNamed botsDisguised botsScannersUnclear
02,0004,0006,0008,000Oct 23Oct 25Oct 27Oct 29Oct 31Nov 2Nov 4Nov 6

Human visitors per day

Same days, people only, on their own scale so they are visible.

036912Oct 23Oct 25Oct 27Oct 29Oct 31Nov 2Nov 4Nov 6

The breakdown

SourceRequestsΣ 44,253ShareData sentBlockedby the serverWhat this means
Break-in scanners26,22259%31 MB12,541Probing for WordPress logins, password files and other common weak spots.
Scanners posing as browsers8,41619%55 MB64Other requests from an address also caught probing for weak spots.
Disguised scrapers2,7396.2%51 MB1Claims to be a normal browser but only downloads pages, never the images or icons a real browser fetches, reads many pages without ever clicking a link, or runs from a cloud provider.
Other named bots1,7854.0%14 MB14Any other software that identifies itself as a bot.
Search engines1,7143.9%11 MB7Crawlers that say who they are, such as Google, Bing, Apple and Amazon. Usually welcome: this is how people find the site.
AI crawlers1,2082.7%6 MB55AI companies gathering pages or answering a user's question, and saying so.
Scripts and tools1,1822.7%11 MB4Programs such as curl or Python, or anything with an unrecognizable name.
No name given3170.7%2 MB5Requests that give no software name at all.
SEO and marketing tools2660.6%1 MB106Commercial tools that sell data about websites.
Unclear2550.6%<1 MB0Browser name, but fetched only an image or data file and no page. Could be either.
Likely people940.2%2 MB0Opened a page and also fetched its images or icons, at a human pace, from a non-cloud address.
Possibly people530.1%<1 MB0Read 1 to 3 pages, arrived from a search engine or social link, no icons fetched. Referrers can be faked, so treat these as maybe.
Calendar and feed apps20.0%<1 MB0Software fetching a feed for someone who subscribed.

Named bots

Botas it names itselfTypeRequests
PetalBotSearch engines773
QlyzeBotOther named bots610
ClaudeBotAI crawlers352
GooglebotSearch engines323
ElevenlabsCrawlerOther named bots185
Amzn-SearchBotSearch engines179
OAI-SearchBotAI crawlers173
BarkrowlerSEO and marketing tools131
ExaSearchBotOther named bots125
bingbotSearch engines123
SemrushBotSEO and marketing tools96
ApplebotSearch engines84
SeznamBotSearch engines81
ibou-searchOther named bots80
GPTBotAI crawlers79

What people opened

Pages opened by at least two different human visitors.

PageHuman visitors
/41
/about/4
/faq/2
/events/2
/sitemap/2

How people arrived

Referring siteHuman visitors
m.baidu.com20
austinhangout.com4
bastropbeat.com4
www.google.com3
www.bing.com2
duckduckgo.com1
austintweet.com1

Where disguised bots operate from

Address blocks, not individual addresses. A heavily used block with many addresses suggests one operator rotating through them.

Address blockRequestsAddresses used
158.69.0.0/162782
192.42.0.0/1611739
47.82.0.0/16117111
158.173.0.0/16644
148.135.0.0/16522
185.220.0.0/164516
5.102.0.0/16393
64.16.0.0/16388

Day by day

DayHuman visitorsHuman pagesNamed botsrequestsDisguisedrequestsScannersrequestsUnclearrequestsAllrequestsBot share
Oct 23361591514791281996%
Oct 2424252173627101,06699%
Oct 25236581223,672114,46799.7%
Oct 26793372013,761114,32299.5%
Oct 27682092311,370121,83399%
Oct 28662171441,202301,60597%
Oct 299115702144,405105,21399.5%
Oct 30342763264,585125,20999.6%
Oct 31461574311,116101,72299%
Nov 1687171,2345,219217,20299.6%
Nov 2551831621,98472,34399.4%
Nov 3791972002,597493,05998%
Nov 4583732391,136201,78098%
Nov 5232552521,204131,72899.0%
Nov 6234151581,281271,88598%

How this was measured

Every request in the server log was sorted by what it did, not only what it claimed to be. Bots that name themselves are counted as named. Anything claiming to be a browser had to act like one: open a page, fetch its images or icons, move at human speed, and come from outside the big cloud providers. These are estimates. A careful bot can pass the test, and a person with images blocked or a cached icon can fail it, so read the human figures as a good approximation, not an exact count. One person using two devices counts as two visitors. Google Analytics-style tools would show different numbers because most bots never run their script. Logs are kept for 15 days.

Built 2026-11-06 22:42 UTC from 15 log files.