Docs housekeeping (#13179)
* Change the title of the /docs/configure/machine-learning doc * fix some outdated links * Clarify some details in the postgres collector
Tasos Katsoulas committed
Jul 14, 2022 at 20:21 UTC
02996dab660563efbda48f02e32b7b850a0c5b0f
4 files changed
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aclk/README.md
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@@ -11,15 +11,25 @@ The Agent-Cloud link (ACLK) is the mechanism responsible for securely connecting
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through Netdata Cloud. The ACLK establishes an outgoing secure WebSocket (WSS) connection to Netdata Cloud on port
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`443`. The ACLK is encrypted, safe, and _is only established if you connect your node_.
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-The Cloud App lives at app.netdata.cloud which currently resolves to 35.196.244.138. However, this IP or range of
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-IPs can change without notice. Watch this page for updates.
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+The Cloud App lives at app.netdata.cloud which currently resolves to the following list of IPs:
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+
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+- 54.198.178.11
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+- 44.207.131.212
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+- 44.196.50.41
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+
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+:::caution
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+
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+This list of IPs can change without notice, we strongly advise you to whitelist the domain `app.netdata.cloud`, if
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+this is not an option in your case always verify the current domain resolution (e.g via the `host` command).
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+
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+:::
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For a guide to connecting a node using the ACLK, plus additional troubleshooting and reference information, read our [get
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started with Cloud](https://learn.netdata.cloud/docs/cloud/get-started) guide or the full [connect to Cloud
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documentation](/claim/README.md).
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## Data privacy
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-[Data privacy](https://netdata.cloud/data-privacy/) is very important to us. We firmly believe that your data belongs to
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+[Data privacy](https://netdata.cloud/privacy/) is very important to us. We firmly believe that your data belongs to
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you. This is why **we don't store any metric data in Netdata Cloud**.
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All the data that you see in the web browser when using Netdata Cloud, is actually streamed directly from the Netdata Agent to the Netdata Cloud dashboard.
collectors/python.d.plugin/postgres/README.md
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@@ -97,7 +97,8 @@ cd /etc/netdata # Replace this path with your Netdata config directory, if dif
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sudo ./edit-config python.d/postgres.conf
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```
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-When no configuration file is found, the module tries to connect to TCP/IP socket: `localhost:5432`.
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+When no configuration file is found, the module tries to connect to TCP/IP socket: `localhost:5432` with the
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+following collection jobs.
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```yaml
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socket:
@@ -113,6 +114,29 @@ tcp:
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port : 5432
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```
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+**Note**: Every job collection must have a unique identifier. In cases that you monitor multiple DBs, every
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+job must have it's own name. Use a mnemonic of your preference (e.g us_east_db, us_east_tcp)
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+
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+## Troubleshooting
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+
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+To troubleshoot issues with the `postgres` collector, run the `python.d.plugin` with the debug option enabled. The output
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+should give you clues as to why the collector isn't working.
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+
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+First, navigate to your plugins directory, usually at `/usr/libexec/netdata/plugins.d/`. If that's not the case on your
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+system, open `netdata.conf` and look for the setting `plugins directory`. Once you're in the plugin's directory, switch
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+to the `netdata` user.
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+
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+```bash
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+cd /usr/libexec/netdata/plugins.d/
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+sudo su -s /bin/bash netdata
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+```
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+
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+You can now run the `python.d.plugin` to debug the collector:
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+
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+```bash
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+./python.d.plugin postgres debug trace
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+```
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+
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---
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docs/anonymous-statistics.md
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@@ -10,7 +10,7 @@ custom_edit_url: https://github.com/netdata/netdata/edit/master/docs/anonymous-s
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By default, Netdata collects anonymous usage information from the open-source monitoring agent using the open-source
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product analytics platform [PostHog](https://github.com/PostHog/posthog). We use their [cloud enterprise platform](https://posthog.com/product).
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-We are strongly committed to your [data privacy](https://netdata.cloud/data-privacy/).
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+We are strongly committed to your [data privacy](https://netdata.cloud/privacy/).
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We use the statistics gathered from this information for two purposes:
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ml/README.md
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@@ -1,5 +1,5 @@
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<!--
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-title: Machine learning (ML) powered anomaly detection
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+title: Configure machine learning (ML) powered anomaly detection
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custom_edit_url: https://github.com/netdata/netdata/edit/master/ml/README.md
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description: This is an in-depth look at how Netdata uses ML to detect anomalies.
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keywords: [machine learning, anomaly detection, Netdata ML]