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DevOps & SRE notes

DevOps & SRE notes

رفتن به کانال در Telegram

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

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📈 تحلیل کانال تلگرام DevOps & SRE notes

کانال DevOps & SRE notes (@devops_sre_notes) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 12 657 مشترک است و جایگاه 10 040 را در دسته فناوری و برنامه‌ها و رتبه 2 978 را در منطقه الولايات المتحدة الأمريكية دارد.

📊 شاخص‌های مخاطب و پویایی

از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 12 657 مشترک جذب کرده است.

بر اساس آخرین داده‌ها در تاریخ 11 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 228 و در ۲۴ ساعت گذشته برابر 17 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.

  • وضعیت تأیید: تأیید نشده
  • نرخ تعامل (ER): میانگین تعامل مخاطب 17.75% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 4.84% واکنش نسبت به کل مشترکان کسب می‌کند.
  • دسترسی پست‌ها: هر پست به طور میانگین 2 247 بازدید دریافت می‌کند. در اولین روز معمولاً 612 بازدید جمع‌آوری می‌شود.
  • واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 3 است.
  • علایق موضوعی: محتوا بر موضوعات کلیدی مانند kubernete, cluster, author, engineering, monitoring تمرکز دارد.

📝 توضیح و سیاست محتوایی

نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
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

به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 12 ژوئن, 2026)، کانال همواره به‌روز و دارای دسترسی بالاست. تحلیل‌ها نشان می‌دهد مخاطبان به‌طور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامه‌ها تبدیل کرده‌اند.

12 657
مشترکین
+1724 ساعت
+677 روز
+22830 روز
آرشیو پست ها
Richard Artoul explores the distinctions between "shared nothing" and "shared storage" architectures, particularly within data streaming contexts. He highlights how shared storage systems, by decoupling data from metadata, offer enhanced flexibility and scalability compared to traditional shared-nothing models. citeturn0search0 https://www.warpstream.com/blog/the-case-for-shared-storage

In his article "TTR: the out-of-control metric," Lorin Hochstein critiques the application of the Time-to-Resolve (TTR) metric in incident management. He argues that since incidents represent periods when systems are out of control, applying statistical analyses to TTR is ineffective and does not lead to meaningful improvements. https://surfingcomplexity.blog/2024/11/23/ttr-the-out-of-control-metric/

OpenTofu / Terraform / Terragrunt and Atmos version manager https://github.com/tofuutils/tenv

An operator to manage ephemeral Kubernetes resources 🐝 https://github.com/NCCloud/mayfly

The blogpost highlights potential security risks associated with automating Terraform lifecycle management. It discusses how malicious actors can exploit vulnerabilities in Terraform automation platforms, such as Hashicorp Cloud and Atlantis, by creating custom providers or using data sources to execute malicious code during the terraform plan phase. This can lead to unauthorized access to sensitive cloud credentials, compromising entire cloud environments. The article emphasizes the need for secure defaults and validation mechanisms in these platforms to mitigate such risks https://snyk.io/blog/gitflops-dangers-of-terraform-automation-platforms/

The article "Autoscaling with Keda and Prometheus Using Custom Metrics in Go" on *Medium* provides a detailed guide on how to implement autoscaling in Kubernetes using Keda and Prometheus. It demonstrates creating custom Prometheus metrics in a Go application, deploying it on Kubernetes, and configuring Prometheus to scrape these metrics. The article then shows how to integrate Keda with Prometheus to scale pods based on custom metrics, such as the number of HTTP requests or product orders, ensuring dynamic resource allocation during varying traffic conditions. https://medium.com/vakifbank-teknoloji/autoscaling-with-keda-and-prometheus-using-custom-metrics-in-go-558a64668fc4

Repost from N/a
🚀 Golang Notes 🐹 Looking for a place to level up your Go skills? Join Golang Notes and stay ahead in the world of Golang! ✨
🚀 Golang Notes 🐹 Looking for a place to level up your Go skills? Join Golang Notes and stay ahead in the world of Golang! ✨ What you'll find: 🔹 Best practices and coding tips 🔹 Latest updates from the Go ecosystem 🔹 Useful tools, snippets, and guides 🔹 Community discussions and expert insights 👨‍💻 Whether you're a beginner or an experienced developer, this channel has something for you! 🔗 Join now

Kuzco reviews your Terraform and OpenTofu resources, compares them to the provider schema to detect unused parameters, and uses AI to suggest improvements and fixes https://github.com/RoseSecurity/Kuzco

Retry a command with exponential backoff and jitter (+ Starlark expressions) https://github.com/dbohdan/recur

The author provides a comprehensive guide to building a REST API hosted on AWS API Gateway with a backend on AWS Lambda and a database on DynamoDB. The guide includes setting up AWS services using Terraform, creating a Lambda function to perform CRUD operations on DynamoDB, and implementing authentication with Amazon Cognito to secure certain routes https://awstip.com/a-step-by-step-guide-on-deploying-rest-api-using-api-gateway-lambda-cognito-terraform-f277814d048e

The blogpost addresses the challenges engineering managers face in maintaining their technical skills amidst busy schedules. It suggests that instead of trying to dedicate a significant portion of their time to hands-on technical work, managers can leverage their team's diversity and projects to stay updated. This involves guiding team members through experimental projects, learning from their experiences, and teaching junior engineers, which helps maintain a technical edge without compromising work-life balance https://medium.com/engineering-managers-journal/real-ways-to-maintain-your-technical-edge-as-an-engineering-manager-25652fa1495c

Goliat - Dashboard is an open-source tool for managing, visualizing, and optimizing Terraform deployments, with integration to Terraform Cloud and a custom provider. https://github.com/danieljsaldana/goliat-dashboard

Stateless cluster local OCI registry mirror. https://github.com/spegel-org/spegel

The article delves into the intricacies of Kubernetes resource management, specifically focusing on requests and limits. It explains how these settings impact pod scheduling, resource allocation, and performance, highlighting the importance of correctly configuring them to ensure efficient use of cluster resources and prevent overcommitting or underutilization. Understanding these concepts is crucial for optimizing application performance and reliability in Kubernetes environments. https://thenewstack.io/how-kubernetes-requests-and-limits-really-work/

The author discusses strategies for significantly reducing the startup time of AWS EKS Windows nodes. The author achieved this by using Karpenter for dynamic node provisioning, optimizing PowerShell scripts, and pre-caching images with AWS Image Builder. Key optimizations included uninstalling unnecessary PowerShell modules and rewriting the bootstrap script in C# for better performance, resulting in startup times under 90 seconds https://hackernoon.com/how-i-reduced-eks-windows-node-start-time-from-5-min-to-90s

🔥 Critical vulnarabliiity in ingress-nginx controlller 9.8/10 🔥 https://github.com/advisories/GHSA-mgvx-rpfc-9mpv If you're running Kubernetes with the ingress-nginx controller and are affected by the vulnerability described in GHSA-mgvx-rpfc-9mpv (CVE-2025-1974), you face several serious security risks: Critical Security Risks This vulnerability, published on March 25, 2025, is part of a set of critical flaws collectively named "IngressNightmare" with a CVSS score of 9.8[6]. The specific issues include: - Unauthenticated Remote Code Execution (RCE): An attacker with access to the pod network can execute arbitrary code in the context of the ingress-nginx controller without authentication[1][2]. - Cluster-wide Secret Exposure: The vulnerability allows attackers to access and steal all secrets accessible to the controller. In default installations, the controller can access all secrets across all namespaces in the cluster[1][3]. - Complete Cluster Takeover: Due to the elevated privileges of the admission controller, successful exploitation could lead to full compromise of your Kubernetes environment[3][6]. - Public Exposure Risk: Over 6,500 clusters with publicly accessible admission controllers are at immediate risk, including those operated by Fortune 500 companies[8]. How the Vulnerability Works The attack targets the admission controller component of the ingress-nginx controller: 1. The vulnerability allows attackers to inject arbitrary NGINX configuration remotely by sending a malicious ingress object directly to the admission controller[3]. 2. When the controller processes this malicious object during validation, it causes the NGINX validator to execute malicious code[6][8]. 3. The admission controller's elevated privileges and network accessibility create a critical escalation path, allowing an attacker to access sensitive resources across the entire cluster[3]. Required Action To mitigate this issue, you should: - Update immediately to one of the patched versions: 1.12.1, 1.11.5, or 1.10.7[6]. - Ensure your admission webhook endpoint is not exposed externally[6]. - Limit access to the admission controller to only the Kubernetes API Server[6]. - Temporarily disable the admission controller component if it's not needed[6]. This vulnerability affects approximately 43% of cloud environments, making it a widespread and serious threat to Kubernetes deployments[6].

Repost from Golang notes
A PostgreSQL database explorer TUI (Terminal User Interface) application written in Go. https://github.com/ddoemonn/go-dot-dot

The incredible HULL - Helm Uniform Layer Library - is a Helm library chart to improve Helm chart based workflows https://github.com/vidispine/hull

The article focuses on the importance of handling termination signals gracefully in applications deployed in orchestrated environments like Kubernetes. Graceful shutdowns are crucial to prevent data loss and system instability that can occur with abrupt terminations, ensuring that applications can exit cleanly and maintain consistency even when they are stopped or scaled down. https://packagemain.tech/p/graceful-shutdowns-k8s-go

Repost from Python notes
The recursive internet scanner for hackers. 🧡 https://github.com/blacklanternsecurity/bbot