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DevOps & SRE notes

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

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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
This comprehensive guide of LocalStack and Terraform for efficient local development of AWS-based applications. It demonstrates how to set up a local environment that emulates AWS services, enabling developers to work on Spring Boot and React applications without relying on actual AWS resources during initial stages https://www.srvrlss.io/blog/localstack-terraform/

Node feature discovery for Kubernetes https://github.com/kubernetes-sigs/node-feature-discovery

🏗 Build container images for your Java applications. https://github.com/GoogleContainerTools/jib

This comprehensive article delves into five distinct solutions for cross-cluster communication in Kubernetes multi-cluster environments, comparing their principles, advantages, and limitations. It covers underlay networks, overlay CNIs, Submariner, Skupper, and KubeSlice, providing insights into their unique approaches to addressing the challenges of inter-cluster connectivity and communication https://oilbeater.com/en/2024/05/24/five-kubernetes-multicluster-network/

This exploration delves into managing AWS Systems Manager (SSM) Parameters using Terraform while accommodating external updates. It presents a solution to the challenge of maintaining SSM Parameters that are modified by other processes, ensuring that Terraform-managed infrastructure remains tracked and in sync with real-world changes https://www.proactiveops.io/archive/managing-aws-ssm-parameters-with-terraform-with/

Kube Startup CPU Boost is a controller that increases CPU resource requests and limits during Kubernetes workload startup time https://github.com/google/kube-startup-cpu-boost

Monitor DNS queries by host processes using eBPF! https://github.com/furkanonder/DnsTrace

This thought-provoking piece challenges the common "safety first" slogan in tech companies, arguing that true prioritization of safety is incompatible with organizational realities. It proposes a hypothetical definition of "safety first" where engineers can extend deadlines without consequences, highlighting the inherent tension between safety and production pressure in software development https://surfingcomplexity.blog/2024/08/31/safety-first/

This exploration delves into the reasons behind the adoption of Infrastructure as Code (IaC) in cloud and Kubernetes environments, comparing it with traditional Graphical User Interfaces (GUIs) and Command-Line Interfaces (CLIs). It highlights the advantages and challenges of IaC, discussing its ability to address limitations found in GUIs and CLIs while acknowledging the learning curve and complexity associated with its implementation https://itnext.io/what-drives-users-to-infrastructure-as-code-848e8640a506

Terraform plan analyzer using Amazon Bedrock https://github.com/aws-ia/terraform-aws-runtask-tf-plan-analyzer

A single binary kubernetes dashboard to manage your multiple clusters. https://github.com/kubewall/kubewall/

The article explores the challenges of creating code that is not only functional for computers but also intuitive for human developers to use and understand. He emphasizes the importance of user-friendly design in frameworks, libraries, and APIs, highlighting the need for easy onboarding, learning through examples, and avoiding conceptual overload. https://erikbern.com/2024/09/27/its-hard-to-write-code-for-humans.html

The author shares their experience with OpenTelemetry, highlighting its potential as a unified observability framework for logs, metrics, and traces. They discuss the benefits of OpenTelemetry's vendor-agnostic approach and its ability to simplify data collection from various sources, while also addressing challenges such as complexity and documentation gaps. https://medium.com/@magstherdev/opentelemetry-journey-87efbfa261db

Making it easy to write shell-like scripts in Go https://github.com/bitfield/script

csi storage for container orchestration systems https://github.com/democratic-csi/democratic-csi

Repost from N/a
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AWS explores strategies for optimizing costs associated with generative AI implementations in enterprise environments. The blog post likely provides insights into efficient resource allocation and cost-effective approaches for leveraging generative AI technologies on the AWS platform. https://aws.amazon.com/blogs/enterprise-strategy/generative-ai-cost-optimization-strategies

OpenSauced shares their experience in significantly reducing costs by implementing open-source AI technologies on a large scale using Kubernetes. Their approach demonstrates how organizations can leverage cost-effective solutions for AI deployment without compromising on performance or capabilities. https://dev.to/opensauced/how-we-saved-10s-of-thousands-of-dollars-deploying-low-cost-open-source-ai-technologies-at-scale-with-kubernetes-57j8

The Modern Application Platform. https://github.com/kubevela/kubevela

Customizable Linux Persistence Tool for Security Research and Detection Engineering. https://github.com/Aegrah/PANIX