2 measurements taken within a single day. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 186–188 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Oct 2026, 09:59
187
no change
13 Oct 2026, 18:22
187
first reading
Engagement
20 posts held, back to 25 December 2024 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
ERR · 30 days
10.5%
avg views ÷ 187 subscribers
Avg views / post
19.7
6 posts measured
Reaction rate
17.8%
reactions ÷ views · ER floor
Posts in window
7
of 20 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 13 October 2026
Posts held
20 (25 December 2024 – 13 October 2026)
Views total
118
Reactions total
21
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Oct 2026, 18:22 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Video runtime
7m 51s
Average length
1m 19s
Measured directly from 6 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
25 reactions across 7 posts, in 3 distinct kinds. The most used accounts for 40.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
10
40.0%
❤
9
36.0%
🔥
6
24.0%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 7 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 25 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 25 December 2024 to 13 October 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
🖋 امنیت را نمیتوان خرید
⬅️ مریم مطلبی کارشناس IT در یادداشتی که در سایت پیوست منتشر شده است به موضوع امنیت پرداخته است.
⬅️مطلبی در این یادداشت نوشته است: در بسیاری از شرکتها و سازمانها هنوز این تصور وجود دارد که امنیت سایبری با خرید تجهیزات گرانقیمت تامین میشود. کافی است یک فایروال چندصد میلیون تومانی خریداری و در رک سرور نصب شود تا مدیران احساس کنند شبکه سازمان در برابر تهدیدهای سایبری ایمن شده است. اما امنی…
🔐 وقتی هوش مصنوعی به یک ریسک امنیتی تبدیل میشود!
🎬 در این ویدئو، نگاهی کوتاه داریم به یکی از چالشهای مهم امنیت اطلاعات در عصر هوش مصنوعی.
📌 از هوش مصنوعی، هوشمندانه استفاده کنیم.
#افراتک #هوش_مصنوعی #امنیت_اطلاعات #امنیت_سایبری
🔐 تازههای فناوری اطلاعات | هوش مصنوعی؛ مسیر ناخواسته نشت اطلاعات؟
کارکنان ممکن است برای خلاصهکردن قراردادها، تحلیل فایلها یا نوشتن کد، اطلاعات محرمانه شرکت را وارد ابزارهای هوش مصنوعی کنند؛ اقدامی که بدون سیاستگذاری مناسب میتواند ریسک نشت داده را افزایش دهد.
🔹 چه اطلاعاتی در خطرند؟
اطلاعات مشتریان، اسناد مالی، قراردادها و کدهای اختصاصی.
🔹 راهکار چیست؟
▪️ تعیین ابزارهای هوش مصنوعی مجاز
▪️ آموزش کارکنان درباره …
تازههای فناوری اطلاعات | نسل جدید ابزارهای عیبیابی شبکه 🔍
عیبیابی شبکه دیگر به پینگهای دستی یا بوقزدن تسترهای ساده کابل محدود نمیشود؛ امروز ترکیب تجهیزات سختافزاری نسل جدید و پلتفرمهای نرمافزاری هوشمند این فرایند را متحول کرده است:
🔹 در لایه نرمافزار و ترافیک (Network Discovery):
اسکنرهای مدرن و مانیتورینگهای مبتنی بر پروتکلهای استاندارد (مانند LLDP و SNMP)، نقشه توپولوژی و دستگاههای فعال را خودکار و …
تازههای فناوری اطلاعات | ۳ ترند داغ IT که همین الان دنیای ما را تغییر میدهند ⚡️
اگر پیگیر دنیای تکنولوژی هستید، این سه تغییر را زیر نظر داشته باشید:
🔹 ۱. نسل جدید سوئیچها و پورتهای پرسرعت:
با انفجار حجم دادهها و ویدیوهای باکیفیت، کابلکشیها و کارتهای شبکه ۱۰ گیگابیتی (10GbE) که قبلاً مخصوص دیتاسنترهای عظیم بودند، حالا به شبکههای محلی شرکتهای متوسط هم رسیدهاند.
🔹 ۲. حافظههای ذخیرهسازی سرد بدون برق (DNA…
سلام به همراهان همیشگی افراتک؛ دلتنگتان بودیم! 👋
در این سکوت طولانی کانال، چراغ اتاق سرورهای ما هیچوقت خاموش نشد! 💻⚙️
در این مدت تمام تمرکزمان را روی اجرای پروژههای زیرساختی پیچیدهتر، ارتقای پروتکلهای امنیت شبکه و تجهیز به فناوریهای نسل جدید گذاشتیم تا حالا بتوانیم دست پر و با تیمی منسجمتر در کنارتان باشیم.
کانال افراتک از این لحظه دوباره روشن شد! قرار است اینجا:
🔹 داغترین و کاربردیترین تحولات دنیای شبک…
روز مهندس بر مهندسان امنیت شبکه مبارک باد.
به عنوان کسانی که با دانش و تخصص خود، به دنیای دیجیتال امنیت میبخشید و هر روز با چالشهای جدید در این حوزه روبهرو هستید، از زحمات و تلاشهای شما بهخوبی آگاهیم.
نقش شما در حفاظت از اطلاعات و حفظ امنیت شبکهها بینهایت ارزشمند است و بدون شک، دنیای ما بدون شما به شدت آسیبپذیر خواهد بود.
روز مهندس را به شما تبریک میگوییم و امیدواریم که همیشه به تحقق اهداف خویش دست یابید و در راستا…
🕵️♂️ هکرها رو با رنگ کلاههاشون بشناسید! هر کلاه نشونه یک نوع از هکرها و هدفشونه. از کلاه سیاه که هدفش تخریب و سرقت اطلاعاته، تا کلاه سفید که برای حفاظت از سیستمها میجنگه. و البته کلاه خاکستری که مرز بین قانون و تخلف رو داره! ◻️◼️
👨💻 کلاهها رنگهای دیگهای هم دارن! مثل آبی ، قرمز و سبز . هر رنگ بازهم هدف هکرهای دیگه رو بازگو میکنه.
🎥 ویدیو رو ببینید و جواب سوالی که تو ویدیو ازتون پرسیده شد رو توی کامنت به ما …
🎁تا ۲۹ دی ماه به مناسبت روز پدر از ۱۵% تخفیف بر روی کلیه خدمات افراتک هوشمند بهره مند بشید🎁
📣فقط کافیه با ما در تماس باشید و کد تخفیف بالا رو به کارشناسان ما ارائه بدید📣
🎉روز پدر مبارک🎉
امن بمانید ... ✅
شرکت نوآوران افراتک هوشمند
---------------------------------------------------------
🤝 با ما در تماس باشید
🪪Instagram(business): @afratec.ir
🌐Website: WWW.afratec.ir
📞Phone: 021-86765000 / 0936-6115511
🚀Tele…
Signed Mohammad Amin
Showing the 12 most recent of 20 posts we hold for @Afratechoshmand. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Handles this channel named that no longer answer
Dead references
2
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
2
vacant every time we have ever looked
@Afratechoshmand named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@afratec named in 6 posts, 14 October 2026 – 14 October 2026
@afratecmedia named in 1 post, 14 October 2026 – 14 October 2026
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 14 October 2026 — this
entry's latest reading, not the date you are reading this.
“AfratecCo” (@Afratechoshmand), 187 subscribers as measured 14 October 2026. Telegram Register, tgregister.com/channel/Afratechoshmand.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.