DevOps & SRE notes

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Helpful articles and tools for DevOps&SRE WhatsApp: https://whatsapp.com/channel/0029Vb79nmmHVvTUnc4tfp2F For paid consultation (RU/EN), contact: @tutunak All ways to support https://telegra.ph/How-support-the-channel-02-19

EEUU2 966 Tecnologías y Aplicaciones10 048...

📈 Análisis del canal de Telegram DevOps & SRE notes

El canal DevOps & SRE notes (@devops_sre_notes) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 12 681 suscriptores, ocupando la posición 10 048 en la categoría Tecnologías y Aplicaciones y el puesto 2 966 en la región EEUU.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 12 681 suscriptores.

Según los últimos datos del 14 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 228, y en las últimas 24 horas de 6, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 15.90%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 4.81% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 2 016 visualizaciones. En el primer día suele acumular 610 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 5.
Intereses temáticos: El contenido se centra en temas clave como kubernete, cluster, author, engineering, monitoring.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Helpful articles and tools for DevOps&SRE WhatsApp: https://whatsapp.com/channel/0029Vb79nmmHVvTUnc4tfp2F For paid consultation (RU/EN), contact: @tutunak All ways to support https://telegra.ph/How-support-the-channel-02-19”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 15 junio, 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.

12 681

Suscriptores

+624 horas

+517 días

+22830 días

2 016

Visitas de la publicación

~ 61024 horas

~ 76448 horas

15.90%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

beta

Archivo de publicaciones

12 682

If you like this channel, you can support it. If you don't have an account in DO and what to have a simple cloud platform for development and running your project, you can register here by my referral link, https://m.do.co/c/0f8bec835d26 . By this link, you get $200 in credit over 60 days.

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The blog post elaborates on scaling Elasticsearch by optimizing the Cluster State, which isn't about the amount of data stored but the metadata's size and rate of change. The post suggests minimizing cluster state size by practices such as avoiding field overuse, distributing data across multiple clusters, and preferring fewer, larger nodes. These adjustments, alongside others like strict mappings and efficient alias usage, contribute to a more manageable and scalable Elasticsearch environment https://sematext.com/blog/elasticsearch-scaling-cluster-state/

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AWS Reference Platform for Kubernetes + Data Services for use as a starting point in upbound.io to build, run, and operate your own internal cloud platform and offer a self-service console and API to your internal teams. https://github.com/upbound/platform-ref-aws

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A better kubectl explain with the fuzzy finder https://github.com/keisku/kubectl-explore

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The Startup CTO's Handbook, a book covering leadership, management and technical topics for leaders of software engineering teams https://github.com/ZachGoldberg/Startup-CTO-Handbook

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Optimized and Maintenance-free Kubernetes on Hetzner Cloud in one command! https://github.com/kube-hetzner/terraform-hcloud-kube-hetzner

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Explain complex systems using visuals and simple terms. Help you prepare for system design interviews. https://github.com/ByteByteGoHq/system-design-101

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The article on Depot highlights the introduction of on-demand Dockerfile linting to identify common linting issues, aiming to adhere to best practices for efficient Docker image creation. It lists the top 10 prevalent linting issues observed in Depot, elaborating on each problem and providing solutions to amend them, thus serving as a resource for improving Dockerfile writing practices https://depot.dev/blog/dockerfile-linting-issues

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A set of modern Grafana dashboards for Kubernetes. https://github.com/dotdc/grafana-dashboards-kubernetes

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Local Volume CSI Provisioner for K8S https://github.com/Protryon/lvp

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The blog post elucidates the author's journey with Argo Workflows, highlighting its effectiveness for infrastructure automation and its advantage over Jenkins. Through personal experiences, the author shares mistakes made, lessons learned, and certain developed patterns to assist readers in avoiding similar pitfalls. The blog's objective is to impart the acquired knowledge and patterns which are conducive to a more efficient utilization of Argo Workflows https://hodgkins.io/argo-workflow-proven-patterns-from-production

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Mutating Webhook to dynamically add tolerations based on detected image architectures https://github.com/PeterGrace/tolerable

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The blog post recounts a real-world scenario where a Kubernetes API was overwhelmed by numerous requests, detailing the troubleshooting process and the implemented solution to stabilize the system. Through creating and deploying FlowSchema and PriorityLevelConfiguration manifests, the authors were able to manage request flows efficiently, thereby restoring and optimizing the Kubernetes cluster's performance https://blog.palark.com/kubernetes-api-flow-control-management/

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Self-hosted AI coding assistant https://github.com/TabbyML/tabby

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The blog post discusses the application of chaos engineering to intentionally induce failures in distributed systems, aiding in assessing their resilience and improving the observability stack at Coroot. Through simulated network failures, the post explores how such disruptions can be detected in a distributed environment, providing insights into ensuring accurate identification of different failure scenarios https://coroot.com/blog/chaos-driven-observability-spotting-network-failures

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A security layer for Git repositories https://github.com/gittuf/gittuf

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KrakenD Community Edition: High-performance, stateless, declarative, API Gateway written in Go. https://github.com/krakend/krakend-ce

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The article delves into how chaos engineering helps in proactively identifying potential system failures in modern cloud applications, thereby averting costly outages. It further elaborates on the application of chaos engineering in security testing, dubbed Security Chaos Engineering (SCE), to ensure systems respond appropriately to common threats by conducting controlled experiments that inject failures into various components like servers and database https://www.datadoghq.com/blog/chaos-engineering-for-security/

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underlay network and rdma solution of cloud native, for bare metal, VM and public cloud environment https://github.com/spidernet-io/spiderpool