From d079b656b4719739b2247dcd9d46e9bec793095a Mon Sep 17 00:00:00 2001 From: Daniel Baumann Date: Mon, 6 Feb 2023 17:11:34 +0100 Subject: Merging upstream version 1.38.0. Signed-off-by: Daniel Baumann --- .../monitor/raspberry-pi-anomaly-detection.md | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) (limited to 'docs/guides/monitor/raspberry-pi-anomaly-detection.md') diff --git a/docs/guides/monitor/raspberry-pi-anomaly-detection.md b/docs/guides/monitor/raspberry-pi-anomaly-detection.md index 73f57cd04..00b652bf2 100644 --- a/docs/guides/monitor/raspberry-pi-anomaly-detection.md +++ b/docs/guides/monitor/raspberry-pi-anomaly-detection.md @@ -12,7 +12,7 @@ We love IoT and edge at Netdata, we also love machine learning. Even better if w of monitoring increasingly complex systems. We recently explored what might be involved in enabling our Python-based [anomalies -collector](/collectors/python.d.plugin/anomalies/README.md) on a Raspberry Pi. To our delight, it's actually quite +collector](https://github.com/netdata/netdata/blob/master/collectors/python.d.plugin/anomalies/README.md) on a Raspberry Pi. To our delight, it's actually quite straightforward! Read on to learn all the steps and enable unsupervised anomaly detection on your on Raspberry Pi(s). @@ -23,14 +23,14 @@ Read on to learn all the steps and enable unsupervised anomaly detection on your - A Raspberry Pi running Raspbian, which we'll call a _node_. - The [open-source Netdata](https://github.com/netdata/netdata) monitoring agent. If you don't have it installed on your - node yet, [get started now](/docs/get-started.mdx). + node yet, [get started now](https://github.com/netdata/netdata/blob/master/docs/get-started.mdx). ## Install dependencies First make sure Netdata is using Python 3 when it runs Python-based data collectors. -Next, open `netdata.conf` using [`edit-config`](/docs/configure/nodes.md#use-edit-config-to-edit-configuration-files) -from within the [Netdata config directory](/docs/configure/nodes.md#the-netdata-config-directory). Scroll down to the +Next, open `netdata.conf` using [`edit-config`](https://github.com/netdata/netdata/blob/master/docs/configure/nodes.md#use-edit-config-to-edit-configuration-files) +from within the [Netdata config directory](https://github.com/netdata/netdata/blob/master/docs/configure/nodes.md#the-netdata-config-directory). Scroll down to the `[plugin:python.d]` section to pass in the `-ppython3` command option. ```conf @@ -59,7 +59,7 @@ LLVM_CONFIG=llvm-config-9 pip3 install --user llvmlite numpy==1.20.1 netdata-pan ## Enable the anomalies collector -Now you're ready to enable the collector and [restart Netdata](/docs/configure/start-stop-restart.md). +Now you're ready to enable the collector and [restart Netdata](https://github.com/netdata/netdata/blob/master/docs/configure/start-stop-restart.md). ```bash sudo ./edit-config python.d.conf @@ -82,7 +82,7 @@ centralized cloud somewhere) is the resource utilization impact of running a mon With the default configuration, the anomalies collector uses about 6.5% of CPU at each run. During the retraining step, CPU utilization jumps to between 20-30% for a few seconds, but you can [configure -retraining](/collectors/python.d.plugin/anomalies/README.md#configuration) to happen less often if you wish. +retraining](https://github.com/netdata/netdata/blob/master/collectors/python.d.plugin/anomalies/README.md#configuration) to happen less often if you wish. ![CPU utilization of anomaly detection on the Raspberry Pi](https://user-images.githubusercontent.com/1153921/110149718-9d749c00-7d9b-11eb-9af8-46e2032cd1d0.png) @@ -108,18 +108,18 @@ looks like a potentially useful addition to enable unsupervised anomaly detectio See our two-part guide series for a more complete picture of configuring the anomalies collector, plus some best practices on using the charts it automatically generates: -- [_Detect anomalies in systems and applications_](/docs/guides/monitor/anomaly-detection-python.md) -- [_Monitor and visualize anomalies with Netdata_](/docs/guides/monitor/visualize-monitor-anomalies.md) +- [_Detect anomalies in systems and applications_](https://github.com/netdata/netdata/blob/master/docs/guides/monitor/anomaly-detection-python.md) +- [_Monitor and visualize anomalies with Netdata_](https://github.com/netdata/netdata/blob/master/docs/guides/monitor/visualize-monitor-anomalies.md) If you're using your Raspberry Pi for other purposes, like blocking ads/trackers with Pi-hole, check out our companions -Pi guide: [_Monitor Pi-hole (and a Raspberry Pi) with Netdata_](/docs/guides/monitor/pi-hole-raspberry-pi.md). +Pi guide: [_Monitor Pi-hole (and a Raspberry Pi) with Netdata_](https://github.com/netdata/netdata/blob/master/docs/guides/monitor/pi-hole-raspberry-pi.md). Once you've had a chance to give unsupervised anomaly detection a go, share your use cases and let us know of any feedback on our [community forum](https://community.netdata.cloud/t/anomalies-collector-feedback-megathread/767). ### Related reference documentation -- [Netdata Agent · Get Netdata](/docs/get-started.mdx) -- [Netdata Agent · Anomalies collector](/collectors/python.d.plugin/anomalies/README.md) +- [Netdata Agent · Get Netdata](https://github.com/netdata/netdata/blob/master/docs/get-started.mdx) +- [Netdata Agent · Anomalies collector](https://github.com/netdata/netdata/blob/master/collectors/python.d.plugin/anomalies/README.md) -- cgit v1.2.3