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

USA2 759 Technologies & Applications9 302...

📈 Analytical overview of Telegram channel DevOps & SRE notes

Channel DevOps & SRE notes (@devops_sre_notes) in the English language segment is an active participant. Currently, the community unites 13 271 subscribers, ranking 9 302 in the Technologies & Applications category and 2 759 in the USA region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 13 271 subscribers.

According to the latest data from 26 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 248 over the last 30 days and by 5 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 17.01%. Within the first 24 hours after publication, content typically collects 4.41% reactions from the total number of subscribers.
Post reach: On average, each post receives 2 256 views. Within the first day, a publication typically gains 585 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
Thematic interests: Content is focused on key topics such as kubernete, cluster, author, engineering, monitoring.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“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”

Thanks to the high frequency of updates (latest data received on 27 August, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

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13 271

Subscribers

+524 hours

+237 days

+24830 days

2 256

Post views

~ 58524 hours

~ 72948 hours

17.01%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

13 271

The new DNSTracking feature in the Red Hat network observability operator 1.11, which now captures DNS query names directly via eBPF without additional configuration. https://developers.redhat.com/articles/2026/04/09/how-dns-name-tracking-enhances-network-observability#

13 271

When you have a special math to calculate your uptime, you always have 100%.

13 271

Repost from N/a

kagent runs your agents where your workloads already live — on Kubernetes. Deploy, observe, and govern AI agents with the tools your platform team already trusts. Open source. Production grade. Built by the founders of Istio. https://github.com/kagent-dev/kagent

13 271

I found a good example of why autoscaling based only on CPU utilization can cause an outage. About a week ago, Twingate had an incident that affected us as a client. They've published a postmortem, and it's a good example of why CPU isn't a good metric to rely on when autoscaling your services.

The incident was triggered by elevated network latency affecting communication paths used by the Authorization service. As requests took longer to complete, individual service instances were able to process fewer requests than normal.

This reduction in throughput exposed a limitation in our auto-scaling configuration, which primarily relied on CPU utilization to determine service capacity requirements.

So, from the CPU utilization perspective, everything was OK, but the number of processed requests decreased. https://status.twingate.com/incidents/49qvqk7swjpq

13 271

Networking within container orchestration can often seem like a black box to developers. This explanation aims to demystify Kubernetes CNI providers and how they manage connectivity. https://medium.com/@csinclair11/demystifying-kubernetes-cni-providers-5ed79569c797

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The article details how to implement production-grade distributed tracing for complex multi-agent AI workflows using OpenTelemetry. https://developers.redhat.com/articles/2026/04/06/distributed-tracing-agentic-workflows-opentelemetry#

13 271

Many organizations are looking for more efficient logging solutions than the traditional stack. This comparison highlights a modern alternative to ELK that aims to reduce complexity and resource usage. https://osuite.io/articles/modern-alternative-to-elk

13 271

kro | Kube Resource Orchestrator https://github.com/kubernetes-sigs/kro

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This informative post details a clever method for securing Grafana dashboards when using Google Cloud Identity-Aware Proxy. You will learn how to seamlessly integrate these two powerful technologies for enhanced access control. https://www.vidbregar.com/blog/grafana-gcp-iap

13 271

Managing expenses in the cloud requires a strategic approach beyond just looking at bills. A senior engineer shares valuable insight into optimizing costs effectively in this detailed read. https://medium.com/@razkevich8/cloud-cost-optimization-a-senior-engineers-guide-d49ed4606de1

13 271

A popular & widely deployed Open Source Container Native Storage platform for Stateful Persistent Applications on Kubernetes. https://github.com/openebs/openebs

13 271

The observability market is shifting from volume-based data ingestion to a value-driven model due to the unsustainable costs of scaling cloud-native and AI workloads. Driven by innovations like Chronosphere’s "Logs 2.0" and its subsequent acquisition by Palo Alto Networks, the industry is prioritizing "signal discipline"—retaining only actionable telemetry—and integrating observability directly into broader AI and security platforms. https://siliconangle.com/2026/02/05/observability-cost-ai-scale-chronosphere-opensourcesummit/

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Claude Code gave me three "tickets" for a free week. You can grab them using this link: https://claude.ai/referral/NXtyf-cgbQ

13 271

Uber engineered an automated approach to migrate its massive Java monorepo (over 600,000 tests, 15 million lines of code) from the deprecated JUnit 4 to JUnit 5. Facing challenges like the lack of native JUnit 5 support in their Bazel build system and custom test configurations, they successfully migrated over 75,000 test classes and 1.25 million lines of code in just four months without disrupting developer workflows. https://www.uber.com/us/en/blog/junit-migration/

13 271

The article explains that while Kubernetes excels at scheduling and isolating workloads, it lacks the context to secure Large Language Models (LLMs), which process untrusted natural language inputs. Highlighting four key risks from the OWASP Top 10 for LLMs, the author argues that security controls shouldn't live within the model runtime (like Ollama). Instead, organizations need a dedicated, LLM-aware policy layer (such as LiteLLM, Kong AI Gateway, or Portkey) in front of the model to enforce validation, filtering, and authorization. https://www.cncf.io/blog/2026/03/30/llms-on-kubernetes-part-1-understanding-the-threat-model/

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https://github.com/V4bel/dirtyfrag

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Bulk port forwarding Kubernetes services for local development. https://github.com/txn2/kubefwd

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The article features an interview with Landon Clipp, who built a multi-tenant GPU-based CaaS platform. - Bypassing the NVIDIA GPU Operator - Why gVisor Fails for GPUs - VM Boot Delays - Firmware and Memory Security - Ideal Workload https://kube.fm/gpu-containers-as-a-service-landon