From 4887fecfdb916198539f1e957db572691a530354 Mon Sep 17 00:00:00 2001 From: dtinth on MBP M1 Date: Wed, 18 Sep 2024 04:00:06 +0700 Subject: [PATCH] more docs --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 54e5759..7eab32d 100644 --- a/README.md +++ b/README.md @@ -3,11 +3,11 @@ > [!CAUTION] > This action is a work in progress. -This action sets up [netdata](https://github.com/netdata/netdata) to send metrics to a [Prometheus server](https://github.com/prometheus/prometheus) via the [Prometheus remote write API](https://learn.netdata.cloud/docs/exporting-metrics/prometheus-remote-write) while GitHub Actions is running. This gives you detailed visibility into the performance of your GitHub Actions workflows, which can be helpful optimizing your workflow performance. +**Your CI workflow can be slow because of many reasons.** Maybe we ran out of CPU power, or maybe the CPU is underutilized due to incorrect config, or maybe it’s idle waiting for IO. Maybe there is a lot of page faults, or maybe the network or disk I/O is the bottleneck. This action sets up [netdata](https://github.com/netdata/netdata) to send detailed system performance metrics to a [Prometheus server](https://github.com/prometheus/prometheus) via the [Prometheus remote write API](https://learn.netdata.cloud/docs/exporting-metrics/prometheus-remote-write) while GitHub Actions is running. This gives you detailed visibility into the performance of your GitHub Actions workflows, which can be helpful optimizing your workflow performance. ![image](https://github.com/user-attachments/assets/14dd94f1-8c12-41ff-8ce2-f3e8d7d7a32f) -In this example, the application server consumes only 2 CPUs out of 4. Further digging shows that our E2E test setup only runs 2 instance of the application server. We can increase the number of instances to 4 to better utilize the available resources and make tests run faster. +In this example, the application server consumes only 2 CPUs out of 4. Total CPU utilization is around 75%. Further digging shows that our E2E test setup only runs 2 instance of the application server. We can increase the number of instances to 4 to better utilize the available resources and make tests run faster. We can also slightly increase the number of workers in Playwright to get CPU utilization closer to 90%. Without any configuration, Netdata automatically tracks hundreds of metrics about your system's performance. Here are some metrics we find useful: