Channel
@opennet
On this record: Growth · Engagement · Reactions · Posts · Cite this entry
328subscribers
+0 since we began measuring on 5 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003016202330 |
|---|---|
| Type | Channel |
| Username | @opennet |
| Created | 3 September 2025 — measured — dated from the channel’s first post |
| First recorded | 6 August 2026 |
| Last confirmed live | 30 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 2 times, most recently 30 August 2026 |
| On Telegram | t.me/opennet |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 22 Aug 2026, 15:22 | 328 | +1 |
| 14 Aug 2026, 07:37 | 327 | -1 |
| 6 Aug 2026, 21:47 | 328 | no change |
| 5 Aug 2026, 22:05 | 328 | first reading |
8 posts held, back to 3 September 2025 — 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 8 posts for this entry, the most recent from 30 April 2026. An engagement rate over an empty window would be a number about nothing.
2 reactions across 1 post, in 2 distinct kinds. The most used accounts for 50.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👀 | 1 | 50.0% | |
| 🔥 | 1 | 50.0% |
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 1 of the 8 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 2reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 8 most recent posts we hold, published 3 September 2025 to 30 April 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.
PSI (Pressure Stall Information): ранние алерты на деградацию CPU/Memory/IO 🧠 Проблема Метрики уровня CPU%/memory usage запаздывают: под уже “плохой”, когда вы видите пик. OOM и latency-спайки возникают раньше — в момент stall’ов (когда процессы ждут ресурсы). Нужен сигнал, который ловит деградацию до аварии. Решение Использовать PSI (Linux ≥4.20, в проде обычно ≥5.x): метрики давления по CPU/Memory/IO (/proc/press…
GitLab Runner autoscaling: устранение задержек старта job (VM executor) Проблема При autoscaling раннеров (OpenStack/VM) наблюдается лаг 3–10 минут между стартом job и фактическим выполнением. Узкие места: долгое создание ВМ, установка Docker на лету, ожидание SSH, “холодные” образы и консервативные тайминги раннера. Решение Сместить максимум работы в golden image, сократить provisioning до нуля и агрессивно настро…
Nexus OSS при 500k+ артефактов: тюнинг JVM и blob store Проблема После ~300–500k артефактов Nexus OSS (3.x) начинает “задыхаться”: GC-паузы, рост latency UI/API, долгие cleanup tasks. Типовые причины — неподходящий heap/GC и неоптимальный blob store (файловая система, layout, GC). Решение Фиксируем heap и GC под профиль нагрузки + выносим blob store на быстрый диск с корректными параметрами FS и включаем регулярный…
Golden images для OpenStack: Packer + cloud-init без “снежинок” ⚙️ Проблема Долгая и нестабильная инициализация ВМ: конфиги через user-data разрастаются, время старта плавает, воспроизводимость падает. Ручные “снежинки” усложняют отладку и масштабирование. Решение Собираем golden image через Packer (builder: openstack) и оставляем динамику на cloud-init. База (пакеты, агенты, hardening) — в образе; переменные окруж…
Тюнинг sysctl для high-load ingress (10k+ RPS) Проблема На ingress-узлах при 10k+ RPS типичные симптомы — рост SYN backlog, TIME_WAIT-шторм, дропы в netstat -s, скачки latency. Дефолтные значения ядра ограничивают очереди, портовый диапазон и поведение TCP, что приводит к ретрансмитам и нестабильным p99. Решение Поднять лимиты очередей и файловых дескрипторов, расширить ephemeral ports, ускорить обработку TIME_WAIT…
OOMKilled в Kubernetes: контроль памяти через cgroup v2 и requests/limits Проблема OOMKilled — частая причина флапающих подов и нестабильных rollout’ов. В k8s (≥1.25) с cgroup v2 поведение меняется: ядро умеет мягко ограничивать память (memory.high) до убийства (memory.max). Без настройки контейнеры упираются в hard limit и попадают под OOM killer. Решение Задать осмысленные requests/limits и включить использование…
Ускорение image pull в Kubernetes через registry mirror + containerd ⚙️ Проблема В кластерах с активным CI/CD и autoscaling основная задержка — image pull. Cold start, rate limits Docker Hub, сетевые RTT до внешних registry → медленные rollout’ы и “залипающий” HPA. Решение Ставим локальный registry mirror (proxy cache) и настраиваем containerd (≥1.7) через hosts.toml. Узлы тянут образы из LAN-кеша, а он — из upstre…
👀1🔥1
Channel created
Showing the 8 most recent of 8 posts we hold for @opennet. 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.
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 22 August 2026 — this entry's latest reading, not the date you are reading this.
“SRE | DevOps” (@opennet), 328 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/opennet.
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.