DevOps&SRE Library
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
Mostrar más📈 Análisis del canal de Telegram DevOps&SRE Library
El canal DevOps&SRE Library (@devopslibrary) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 19 429 suscriptores, ocupando la posición 6 863 en la categoría Tecnologías y Aplicaciones y el puesto 34 483 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 19 429 suscriptores.
Según los últimos datos del 02 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 47, y en las últimas 24 horas de 0, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 13.23%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 7.43% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 571 visualizaciones. En el primer día suele acumular 1 444 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 0.
- Intereses temáticos: El contenido se centra en temas clave como kubernete, cluster, infrastructure, storage, configuration.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 03 julio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
There are a wealth of monitoring solutions available for engineers and developers to choose from, so how do you select which is most appropriate for you?https://medium.com/contino-engineering/how-to-pick-the-best-observability-solution-for-your-organisation-e956f0bffb8e
uptime ⟶ load averages
2. dmesg -T | tail ⟶ kernel errors
3. vmstat 1 ⟶ overall stats by time
4. mpstat -P ALL 1 ⟶ CPU balance
5. pidstat 1 ⟶ process usage
6. iostat -xz 1 ⟶ disk I/O
7. free -m ⟶ memory usage
8. sar -n DEV 1 ⟶ network I/O
9. sar -n TCP,ETCP 1 ⟶ TCP stats
10. top ⟶ check overview
Linux Disk Checklist
1. iostat -xz 1 ⟶ any disk I/O? if not, stop looking
2. vmstat 1 ⟶ is this swapping? or, high sys time?
3. df -h ⟶ are file systems nearly full?
4. ext4slower 10 ⟶ (zfs*, xfs*, etc.) slow file system I/O?
5. bioslower 10 ⟶ if so, check disks
6. ext4dist 1 ⟶ check distribution and rate
7. biolatency 1 ⟶ if interesting, check disks
8. cat /sys/devices/…/ioerr_cnt ⟶ (if available) errors
9. smartctl -l error /dev/sda1 ⟶ (if available) errors
* Another short checklist. Won't solve everything. ext4slower/dist, bioslower/latency, are from bcc/BPF tools.
Linux Network Checklist
1. sar -n DEV,EDEV 1 ⟶ at interface limits? or use nicstat
2. sar -n TCP,ETCP 1 ⟶ active/passive load, retransmit rate
3. cat /etc/resolv.conf ⟶ it's always DNS
4. mpstat -P ALL 1 ⟶ high kernel time? single hot CPU?
5. tcpretrans ⟶ what are the retransmits? state?
6. tcpconnect ⟶ connecting to anything unexpected?
7. tcpaccept ⟶ unexpected workload?
8. netstat -rnv ⟶ any inefficient routes?
9. check firewall config ⟶ anything blocking/throttling?
10. netstat -s ⟶ play 252 metric pickup
* tcp*, are from bcc/BPF tools.
Linux CPU Checklist
1. uptime ⟶ load averages
2. vmstat 1 ⟶ system-wide utilization, run q length
3. mpstat -P ALL 1 ⟶ CPU balance
4. pidstat 1 ⟶ per-process CPU
5. CPU flame graph ⟶ CPU profiling
6. CPU subsecond offset heat map ⟶ look for gaps
7. perf stat -a -- sleep 10 ⟶ IPC, LLC hit ratio
* htop can do 1-4. I'm tempted to add execsnoop for short-lived processes (it's in perf-tools or bcc/BPF tools).
https://www.brendangregg.com/blog/2016-05-04/srecon2016-perf-checklists-for-sres.htmlKubernetes is to Borg what Frankstein is to the Dali Lama When I left Google, I was sold on the whole containerized way of running things. Borg is lightyears ahead of every other cluster orchestration project. Borg doesn't let you do everything. It is designed to run specifically built applications that are containerized. You don't get Docker images with whatever OS stuff you feel like running that day. The OS is always Google's internal OS. You don't get access to whatever binaries you want to install. You don't get go use whatever security you want. Your RPC system is always going to be Stubby (GRPC internal to Google). Your cluster file system is going to be the only one allowed. Period. Those limits are freeing. You simply need to have resources to run your jobs and deploy them. Your binaries are packaged up and you just need to say what is going to get run. So naturally, I've used Kubernetes after I left. Everything about Borg I liked is gone in Kubernentes. It is trying to solve everyone's problem and solves no one's problem. It is easy to kill your jobs. Its hard to do things like update a single instance. Service meshes???? Really???? Helm? Great, I can kill all my cluster MySQL databases at the flick of my heml config. Security, what security? Oh, right, the bring my own model that is just crazy hard. Need it to work with special cloud sidecars (like special identity services)? Well, that's going to be a fun thing. Upgrades that change the config language so that your jobs won't run anymore. Perfect..... And btw, love YAML over the Borg config language, NOT!http://www.gophersre.com/2021/02/21/my-dev-lessons-from-2020
Ortelius simplifies the implementation of microservices. By providing a central catalog of services with their deployment specs, application teams can easily consume and deploy services across cluster. Ortelius tracks application versions based on service updates and maps their service dependencies eliminating confusion and guess work.https://github.com/ortelius/ortelius
A Kubernetes operator for declarative database schema management (gitops for database schemas)https://github.com/schemahero/schemahero
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