Channel
@sberhealthIT
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
1,315subscribers
+3 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002324790749 |
|---|---|
| Type | Channel |
| Username | @sberhealthIT |
| Created | Between 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 17 August 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 17 August 2026 |
| On Telegram | t.me/sberhealthIT |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Aug 2026, 13:09 | 1,315 | +1 |
| 14 Aug 2026, 05:16 | 1,314 | +3 |
| 11 Aug 2026, 04:24 | 1,311 | -2 |
| 7 Aug 2026, 21:07 | 1,313 | +1 |
| 6 Aug 2026, 23:01 | 1,312 | first reading |
7 posts held, back to 18 June 2026 — 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 pageof Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 3 August 2026 |
|---|---|
| Posts held | 7 (18 June 2026 – 3 August 2026) |
| Views total | 1,892 |
| Reactions total | 59 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 23:01 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.
96 reactions across 7 posts, in 8 distinct kinds. The most used accounts for 56.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 54 | 56.3% | |
| 👍 | 16 | 16.7% | |
| ❤ | 15 | 15.6% | |
| 😁 | 4 | 4.17% | |
| 🥰 | 4 | 4.17% | |
| custom 5334996220886656404 | 1 | 1.04% | |
| 👏 | 1 | 1.04% | |
| 🤩 | 1 | 1.04% |
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.
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 7 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 96reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 7 most recent posts we hold, published 18 June 2026 to 3 August 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.
Конец спринта. Все задачи горят. Самое время… готовить демо?🔥 Уже 2 года команды стрима Записи находят на это время — каждые две недели! Что заставляет разработчиков, аналитиков и тестировщиков раз за разом выходить и рассказывать о своей работе — делится Оля Курбан, человек, который держит этот формат на плаву с самого начала 📕
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Мониторинг здоровья Kubernetes через безопасность Как понять, что Kubernetes действительно здоров? Недостаточно следить за ресурсами и доступностью сервисов — важно знать, насколько кластер защищён от ошибок конфигурации, подозрительной активности и атак✔️ Безопасность сложно измерить одной метрикой. Но её можно превратить в систему проверок, покрытий и сигналов, которая позволяет объективно оценивать состояние Kub…
🔥8❤3👍3
Спорт — это и есть здоровье (простите, не удержались) На прошлой неделе, с 13 по 17 июля, сотрудники СберЗдоровья приняли участие в Летних играх Сбера в Нижнем Новгороде. И название компании в этот раз сыграло дословно 😂 Заявились сразу в нескольких дисциплинах: 🟣 киберспорт 🟢 баскетбол 🟡 пляжный волейбол 🔵 настольный теннис Коллеги успевали совмещать рабочие задачи, тренировки и соревнования. Кажется, отличный пр…
🔥8❤7😁3🤩1
Можно ли доверить LLM mission-critical процессы? Многие считают, что нет: нейросети слишком непредсказуемы. Но действительно ли проблема в самой модели? На конференции PyCon 2026 Руслан Черкас, ведущий архитектор, расскажет, откуда на самом деле берётся «недетерминированность» LLM, почему зачастую это следствие инженерных решений, а не фундаментальное свойство моделей, и что можно сделать, чтобы их работа была стаб…
🔥9❤2👍2
Можно ли доверять ответу нейросети? Получить ответ от нейросети — только половина задачи. Не менее важно понять, насколько этому ответу можно доверять. В новой статье Руслан Черкас, старший архитектор, делится своим взглядом на существующие методы верификации⭐️ В статье: классификация подходов, их ограничения и рекомендации, какие методы стоит использовать, а каких лучше избегать. ⏩Читать на Хабре #СберЗдоровье_…
🔥6👍2❤1
Как превратить LLM из обычного чат-бота в рабочий инструмент разработки? Об этом 23 июня на Saint Highload++ расскажет Максим Божко, ведущий backend-разработчик СберЗдоровья. На воркшопе: 🔘 мультиагентный подход 🔘 Spec-Driven Development 🔘 практический разбор работы с LLM на разных этапах создания продукта 📌 14:50, Зал "Синий", Saint Highload++ 📎 Подробнее в программе
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А вы знали, что... в PHP можно оптимизировать импорт с ключевым словом use? Это называется группировкой и выглядит так: use Sberhealth\Entity\{Book,Box as BoxEntity}; Лев Лейман, ведущий бэкенд-разработчик, рассказал подробнее про этот способ. Передаём ему слово 👇 «Эта возможность появилась в версии 7.0.0, а началось всё с RFC в далеком 2015 году. На первый взгляд кажется, что это не самая нужная фича, но в её по…
👍7🔥4😁1custom 53349962208866564041
Showing the 7 most recent of 7 posts we hold for @sberhealthIT. 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.
Citation-graph rank — 395,661 of 1,549,376entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
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 17 August 2026 — this entry's latest reading, not the date you are reading this.
“SberHealth ИТ” (@sberhealthIT), 1,315 subscribers as measured 17 August 2026. Telegram Register, tgregister.com/channel/sberhealthIT.
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.