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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
Show moreπ 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 12 743 subscribers, ranking 9 995 in the Technologies & Applications category and 2 933 in the USA region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 12 743 subscribers.
According to the latest data from 23 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 209 over the last 30 days and by 7 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 14.26%. Within the first 24 hours after publication, content typically collects 3.58% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 812 views. Within the first day, a publication typically gains 455 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 7.
- Thematic interests: Content is focused on key topics such as kubernete, cluster, author, engineering, monitoring.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βHelpful 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-02-19β
Thanks to the high frequency of updates (latest data received on 25 June, 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.
12 743
Subscribers
+724 hours
+217 days
+20930 days
Data loading in progress...
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Tags Cloud
Incoming and Outgoing Mentions
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| Date | Subscriber Growth | Mentions | Channels | |
| 24 June | +27 | |||
| 23 June | +9 | |||
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| 02 June | +15 | |||
| 01 June | +6 |
Channel Posts
Shopify discovered that deeply nested, high-cardinality GraphQL queries were bottlenecking not on I/O, but on CPU-bound field resolver execution driven by GraphQLβs standard depth-first traversal model. To solve this, Shopify built "GraphQL Cardinal," a breadth-first execution engine that resolves each field once across all objects rather than recursively per object, vastly reducing platform overhead and resolving N+1 issues more efficiently.
https://shopify.engineering/faster-breadth-first-graphql-execution
| 2 | A utility for fetching Kubernetes Manifest documents from a running cluster. This utility can be run inside or outside a Kubernetes cluster, and utilizes a config file to determine what kind of objects to detect. Manifests files are stored in an output directory in the format:Β <outputDir>/<kind>/<namespace>/<name>.yaml
https://github.com/grafana/k8s-manifest-tail | 798 |
| 3 | Airbnb migrated its high-volume metrics infrastructure to adopt the OpenTelemetry Protocol (OTLP) and Prometheus. To do so without massive disruption, they implemented a dual-emit strategy in their shared metrics libraries. They encountered and solved specific performance bottlenecks regarding high-cardinality data and replaced their legacy Veneur aggregator with a custom-sharded vmagent setup. Crucially, they developed a "zero injection" technique to solve systemic undercounting issues when translating StatsD-style counters into Prometheus cumulative counters.
https://medium.com/airbnb-engineering/building-a-high-volume-metrics-pipeline-with-opentelemetry-and-vmagent-c714d6910b45 | 1 256 |
| 4 | The article explores the newly introduced CloudWatch Logs delivery feature for Amazon EKS Auto Mode.
https://shinyaz.com/en/blog/2026/03/19/eks-auto-mode-enhanced-logging | 1 057 |
| 5 | The primary bottleneck in software delivery is no longer writing code (thanks to AI-assisted development) but rather post-commit infrastructure operations, which are traditionally built for human interaction rather than machine autonomy. It positions Crossplane and Kubernetes-native control planes as the necessary solution, advocating for "API-first infrastructure."
https://www.cncf.io/blog/2026/03/20/crossplane-and-ai-the-case-for-api-first-infrastructure/ | 1 363 |
| 6 | ING tackled developer portal sprawl (60+ disparate tools) by adopting Backstage.io as their unified front-end standard. The talk outlines their specific architectural choices and governance models to scale Backstage without it becoming a monolithic bottleneck or crashing due to community plugins.
- To prevent a single bad plugin from crashing the portal, ING separates core services (like the software catalog, which handles hundreds of thousands of entities and has dedicated DB tuning) from community/external plugins, running them on separate instances.
- To avoid costly rewrites of legacy services, internal teams can use a backend proxy plugin to connect existing backend tools into the Backstage UI.
- Built a custom plugin to solve ownership issues in complex, cross-domain workflows.
- Because anyone can contribute, ING enforces a "Contribution Plugin" workflow
- They drove adoption by focusing heavily on Developer Experience (local setups, playgrounds) while simultaneously having their Technology Standards Board mandate Backstage for all new internal UI initiatives.
https://tldrecap.tech/posts/2026/backstagecon-europe/ing-backstage-scaling-developer-platform/ | 1 688 |
| 7 | CLI tool for linting and testing Helm charts
https://github.com/helm/chart-testing | 1 715 |
| 8 | 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# | 1 950 |
| 9 |  When you have a special math to calculate your uptime, you always have 100%. | 1 900 |
| 10 | kagent runs your agents where your workloads already live β 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 | 2 019 |
| 11 | 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 | 2 061 |
| 12 | 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 | 1 973 |
| 13 | 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# | 2 243 |
| 14 | 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 | 2 734 |
| 15 | kro | Kube Resource Orchestrator
https://github.com/kubernetes-sigs/kro | 2 781 |
| 16 | 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 | 3 086 |
| 17 | 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 | 2 772 |
| 18 | A popular & widely deployed Open Source Container Native Storage platform for Stateful Persistent Applications on Kubernetes.
https://github.com/openebs/openebs | 2 738 |
| 19 | 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 Chronosphereβs "Logs 2.0" and its subsequent acquisition by Palo Alto Networks, the industry is prioritizing "signal discipline"βretaining only actionable telemetryβand integrating observability directly into broader AI and security platforms.
https://siliconangle.com/2026/02/05/observability-cost-ai-scale-chronosphere-opensourcesummit/ | 2 967 |
| 20 |  One left | 0 |
