DevOps&SRE Library
Библиотека статей по теме DevOps и SRE. Реклама: @ostinostin Контент: @mxssl РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3
Show more📈 Analytical overview of Telegram channel DevOps&SRE Library
Channel DevOps&SRE Library (@devopslibrary) in the English language segment is an active participant. Currently, the community unites 19 870 subscribers, ranking 6 592 in the Technologies & Applications category and 33 022 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 19 870 subscribers.
According to the latest data from 08 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -26 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 12.80%. Within the first 24 hours after publication, content typically collects 6.49% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 544 views. Within the first day, a publication typically gains 1 289 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
- Thematic interests: Content is focused on key topics such as kubernete, cluster, infrastructure, storage, configuration.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Библиотека статей по теме DevOps и SRE.
Реклама: @ostinostin
Контент: @mxssl
РКН: https://www.gosuslugi.ru/snet/67704b536aa9672b963777b3”
Thanks to the high frequency of updates (latest data received on 09 November, 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.
GitOps doesn’t solve all deployment problems or even cover the entire deployment process, but it’s a solid foundational building block.https://medium.com/@briankgrant/is-gitops-actually-useful-a1c851ba99d8
There are multiple layers where the performance of Loki can be improved and fine-tuned. From optimising the query, channeling it efficiently for processing, to allocating the right computational resources, we will cover the following parameters that make a significant improvement to the performance.https://dev.to/siddharthjain1715/grafana-loki-optimising-log-based-metrics-5edb
Реклама. ООО «Отус онлайн-образование», ОГРН 1177746618576, erid: 2Vtzqvaus2NSPQR is a production-ready system for horizontal scaling of PostgreSQL via sharding. We appreciate any kind of feedback and contribution to the project.https://github.com/pg-sharding/spqr
Know enough to be dangerous in 10 minuteshttps://metoro.io/blog/distributed-tracing-whistle-stop-tour
While working on SLOs, SLAs and SLIs I have found that there are only so many ways to aggregate service metrics. I have not yet found somewhere that attempts to review the different aggregation methods and what their relative strengths and weaknesses are.https://hross.substack.com/p/different-ways-to-aggregate-nines
Everyone experiences stress at work—thankfully, it’s a topic folks aren’t shying away from anymore. But for on-call engineers, alert fatigue is a phenomenon closer to home. Unfortunately, like stress, it can be just as insidious and drastically impact those it affects. First discussed in the context of hospital settings, this phrase later entered engineering circles. Alert fatigue is when an excessive number of alerts overwhelms the individuals responsible for answering them, often over a prolonged period, resulting in missed or delayed responses, or them being ignored altogether The impact of this fatigue can have an effect beyond the individual and can create significant risks for your organization. But, if you approach on-call the right way, you can mitigate the impacts of alert fatigue or, better yet, avoid it altogether. Here, we'll dive into the tactics teams can implement to address alert fatigue and its underlying causes.https://incident.io/hubs/on-call/dealing-with-alert-fatigue-head-on
Introduction to the SLA in relation to SLI and SLOhttps://blog.alexewerlof.com/p/sla
Core principles of documentation-as-code tools - Treating documentation with the same rigor as code - Storing documentation in version control - Automation of documentation generation and deployment - Peer review processes for documentation updateshttps://www.tabnine.com/blog/documentation-as-code-principles-workflow-and-challenges
A key challenge of monitoring your CI/CD system is understanding how to optimize your workflows and create best practices that help you minimize pipeline slowdowns and better respond to CI issues. In addition to monitoring CI pipelines and their underlying infrastructure, your organization also needs to cultivate effective relationships between platform and development teams. Fostering collaboration between these two teams is a critical and equally valuable aspect of improving the reliability and performance of your CI. In this post, we’ll explore how platform teams can help developers visualize trends in CI test performance and notify them of new flaky tests, test failures, and performance regressions with dashboards and monitors. We’ll also detail best practices that can help developers identify, investigate, and remediate flaky tests.https://www.datadoghq.com/blog/best-practices-for-monitoring-software-testing
Kubernetes has been a great orchestrator of Jobs and CronJobs for over half a decade now, but if you had a need for running proxy containers or other secondary containers alongside the job, running things properly took a bit of work and decision-making to handle gracefully. This article introduces the easiest way to run Jobs with sidecars using the latest Kubernetes features, and has a complementary repository with complete example manifests you can try in your own cluster. The repository contains all the examples for earlier versions of K8s as well, so make sure to focus on the cronjob.sidecar.*.yaml examples.https://medium.com/teamsnap-engineering/properly-running-kubernetes-jobs-with-sidecars-in-2024-k8s-1-28-ad9b51d17d50
Garnet is a remote cache-store from Microsoft Research that offers strong performance (throughput and latency), scalability, storage, recovery, cluster sharding, key migration, and replication features. Garnet can work with existing Redis clients.https://github.com/microsoft/garnet
