Tired of fighting with SNMP and confusing network data? 😤
Join our "Nonsense Networking" live stream where we make sense of network #metrics, #logs, and #flows. We'll cover the common pain points and show you better alternatives.

📅 August 28th at 10 am PDT | 6 pm BST | 7 pm CEST

https://bit.ly/45ykGpy

#NetworkMonitoring #SysAdmin #SNMP #Netflow #Prometheus

Currently working on metrics like Accuracy, Precision and Recall for my new ML project.
Any suggestions for simple and clear ways to visualize these? 🤔

#ml #machinelearning #visualization #metrics

Knowing and not knowing at conferences through the lens of Mary Oliver’s poetry, where metrics meet wonder, connection, and the intangible

https://www.conferencesthatwork.com/index.php/event-design/2024/12/knowing

#eventprofs #metrics #wonder #knowing #MaryOliver #EventDesign #poetry #owl

#Development #Analyses
The fastest site in the Tour de France · Which bike brand excelled in both browser and race? https://ilo.im/16600l

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#TourDeFrance #WebPerf #WebPage #Metrics #WebVital #CrRRUX #Browser #DevTools #WebDev #Frontend

Сбор и масштабирование метрик в PHP Symfony highload: 200k RPM, 50+ серверов и zero overhead с Telegraf UDP

«Redis умирает на 200k RPM, Prometheus не успевает скрейпить 50 серверов, а бизнес требует real-time дашборды. Знакомо?» Пятница, 18:00. Дашборд в Grafana показывает timeout'ы при сборе метрик. Redis, который хранит данные для prometheus_client_php, жрёт 8GB памяти и 100% CPU. Prometheus не успевает опросить все 50+ серверов за отведённые 15 секунд. А в понедельник запускается Black Friday... Эта статья — о том, как мы перешли с pull на push модель для мониторинга PHP-приложения в highload, почему выбрали UDP + Telegraf вместо классического подхода, и как теперь собираем метрики PHP с 50+ серверов без единого timeout'а.

https://habr.com/ru/articles/935808/

#метрики #php #symfony #metrics #telegraf #prometheus #grafana #monitoring

TuBoost.io Day 4 reality check.

7 signups sounds small until you realize each person trusted a random AI tool with their content.

23 clips generated means 23 moments where someone thought "this might actually work."

Zero revenue stings, but zero complaints hits different.

Progress isn't always measurable in dollars.

#BuildingInPublic #StartupJourney #SoloFounder #TuBoost #Metrics #IndieHacker

HTML Is Dead, Long Live HTML, by @unconed.bsky.social:

https://acko.net/blog/html-is-dead-long-live-html/

#html #css #dom #standards #metrics

When I created the MONK metrics for Platform Engineering, the N was for NPS (net promoter score) - but any satisfaction measure would do.

I've written up 3 complementary techniques you can mix and match to measure platform satisfaction.

https://octopus.com/devops/metrics/platform-satisfaction/

#PlatformEngineering #Metrics

#KnowledgeSharing post:

Yesterday I talked about #metrics #cardinality and churn, and how they can affect #Prometheus server performance.

Today I want to talk about unbounded cardinality, which is when there is no fixed maximum value for the cardinality of a time series. Unbounded cardinality is not only detrimental to Prometheus server performance, but it also introduces a lot of metrics noise, leading to degraded #observability.

A common example of unbounded cardinality is mapping an HTTP server's request path to a label. At a glance this may seem like a good idea, for example to identify which requests are taking the longest to serve. However, this only works if the received requests represent valid traffic. A client that is scraping the site or a malicious actor performing reconnaissance will throw the dictionary at the server, and a small site serving a dozen or so legitimate pages will produce millions of idle time series from all these requests that were seen only once.

My recommendation for HTTP request metrics is to only produce aggregate metrics. For example, instead of producing metrics for every request path, instead produce metrics for the routes configured on the server. This does not mean that observability granularity needs to be sacrificed: Metrics can be complemented with #traces for each HTTP request, and aggressive sampling can be applied to the traces so that only the "interesting" ones are kept - the exceptions, requests taking too long, with too big of a payload, etc.