396 lines
14 KiB
Markdown
396 lines
14 KiB
Markdown
---
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title: How to Setup Prometheus, Grafana and Loki on NixOS
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date: 2020-11-20
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tags:
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- nixos
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- prometheus
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- grafana
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- loki
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- promtail
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---
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# How to Setup Prometheus, Grafana and Loki on NixOS
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When setting up services on your home network, sometimes you have questions
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along the lines of "how do I know that things are working?". In this blogpost we
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will go over a few tools that you can use to monitor and visualize your machine
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state so you can answer that. Specifically we are going to use the following
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tools to do this:
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- [Grafana](https://grafana.com/) for creating pretty graphs and managing
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alerts
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- [Prometheus](https://prometheus.io/) for storing metrics and as a common
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metrics format
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- [Prometheus node_exporter](https://github.com/prometheus/node_exporter) for
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deriving metrics from system state
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- [Loki](https://grafana.com/oss/loki/) as a central log storage point
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- [promtail](https://grafana.com/docs/loki/latest/clients/promtail/) to push
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logs to Loki
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Let's get going!
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[Something to note: in here you might see domains using the `.pele` top-level
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domain. This domain will likely not be available on your home network. See <a
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href="/blog/series/site-to-site-wireguard">this series</a> on how to set up
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something similar for your home network. If you don't have such a setup, replace
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anything that ends in `.pele` with whatever you normally use for
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this.](conversation://Mara/hacker)
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## Grafana
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Grafana is a service that handles graphing and alerting. It also has some nice
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tools to create dashboards. Here we will be using it for a few main purposes:
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- Exploring what metrics are available
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- Reading system logs
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- Making graphs and dashboards
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- Creating alerts over metrics or lack of metrics
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Let's configure Grafana on a machine. Open that machine's `configuration.nix` in
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an editor and add the following to it:
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```nix
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# hosts/chrysalis/configuration.nix
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{ config, pkgs, ... }: {
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# grafana configuration
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services.grafana = {
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enable = true;
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domain = "grafana.pele";
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port = 2342;
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addr = "127.0.0.1";
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};
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# nginx reverse proxy
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services.nginx.virtualHosts.${services.grafana.domain} = {
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locations."/" = {
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proxyPass = "http://127.0.0.1:${toString config.services.grafana.port}";
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proxyWebsockets = true;
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};
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};
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}
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```
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[If you have a <a href="/blog/site-to-site-wireguard-part-3-2019-04-11">custom
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TLS Certificate Authority</a>, you can set up HTTPS for this deployment. See <a
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href="https://github.com/Xe/nixos-configs/blob/master/common/sites/grafana.akua.nix">here</a>
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for an example of doing this. If this server is exposed to the internet, you can
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use a certificate from <a
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href="https://nixos.wiki/wiki/Nginx#TLS_reverse_proxy">Let's Encrypt</a> instead
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of your own Certificate Authority.](conversation://Mara/hacker)
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Then you will need to deploy it to your cluster with `nixops deploy`:
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```console
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$ nixops deploy -d home
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```
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Now open the Grafana server in your browser at http://grafana.pele and login
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with the super secure default credentials of admin/admin. Grafana will ask you
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to change your password. Please change it to something other than admin.
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This is all of the setup we will do with Grafana for now. We will come back to
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it later.
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## Prometheus
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> Prometheus was punished by the gods by giving the gift of knowledge to man. He
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> was cast into the bowels of the earth and pecked by birds.
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Oracle Turret, Portal 2
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Prometheus is a service that reads metrics from other services, stores them and
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allows you to search and aggregate them. Let's add it to our `configuration.nix`
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file:
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```nix
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# hosts/chrysalis/configuration.nix
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services.prometheus = {
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enable = true;
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port = 9001;
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};
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```
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Now let's deploy this config to the cluster with `nixops deploy`:
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```console
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$ nixops deploy -d home
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```
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And let's configure Grafana to read from Prometheus. Open Grafana and click on
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the gear to the left side of the page. The `Data Sources` tab should be active.
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If it is not active, click on `Data Sources`. Then click "add data source" and
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choose Prometheus. Set the URL to `http://127.0.0.1:9001` (or with whatever port
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you configured above) and leave everything set to the default values. Click
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"Save & Test". If there is an error, be sure to check the port number.
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Now let's start getting some data into Prometheus with the node exporter.
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### Node Exporter Setup
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The Prometheus node exporter exposes a lot of information about systems ranging
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from memory, disk usage and even systemd service information. There are also
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some [other
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collectors](https://search.nixos.org/options?channel=20.09&query=prometheus.exporters+enable)
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you can set up based on your individual setup, however we are going to enable
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only the node collector here.
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In your `configuration.nix`, add an exporters block and configure the node
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exporter under `services.prometheus`:
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```nix
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# hosts/chrysalis/configuration.nix
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services.prometheus = {
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exporters = {
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node = {
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enable = true;
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enabledCollectors = [ "systemd" ];
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port = 9001;
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};
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};
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}
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```
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Now we need to configure Prometheus to read metrics from this exporter. In your
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`configuration.nix`, add a `scrapeConfigs` block under `services.prometheus`
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that points to the node exporter we configured just now:
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```nix
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# hosts/chrysalis/configuration.nix
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services.prometheus = {
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# ...
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scrapeConfigs = [
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{
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job_name = "chrysalis";
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static_configs = [
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targets = [ "127.0.0.1:${toString config.services.prometheus.exporters.node.port}" ];
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];
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}
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];
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# ...
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}
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# ...
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```
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[The complicated expression in the target above allows you to change the port of
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the node exporter and ensure that Prometheus will always be pointing at the
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right port!](conversation://Mara/hacker)
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Now we can deploy this to your cluster with nixops:
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```console
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$ nixops deploy -d home
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```
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Open the Explore tab in Grafana and type in the following expression:
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```
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node_memory_MemFree_bytes
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```
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and hit shift-enter (or click the "Run Query" button in the upper left side of
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the screen). You should see a graph showing you the amount of ram that is free
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on the host, something like this:
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If you want to query other fields, you can type in `node_` into the searchbox
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and autocomplete will show what is available. For a full list of what is
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available, open the node exporter metrics route in your browser and look through
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it.
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## Grafana Dashboards
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Now that we have all of this information about our machine, let's create a
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little dashboard for it and set up a few alerts.
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Click on the plus icon on the left side of the Grafana UI to create a new
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dashboard. It will look something like this:
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In Grafana terminology, everything you see in a dashboard is inside a panel.
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Let's create a new panel to keep track of memory usage for our server. Click
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"Add New Panel" and you will get a screen that looks like this:
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Let's make this keep track of free memory. Write "Memory Free" in the panel
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title field on the right. Write the following query in the textbox next to the
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dropdown labeled "Metrics":
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```
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node_memory_MemFree_bytes
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```
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and set the legend to `{{job}}`. You should get a graph that looks something
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like this:
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This will show you how much memory is free on each machine you are monitoring
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with Prometheus' node exporter. Now let's configure an alert for the amount of
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free memory being low (where "low" means less than 64 megabytes of ram free).
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Hit save in the upper right corner of the Grafana UI and give your dashboard a
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name, such as "Home Cluster Status". Now open the "Memory Free" panel for
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editing (click on the name and then click "Edit"), click the "Alert" tab, and
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click the "Create Alert" button. Let's configure it to do the following:
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- Check if free memory gets below 64 megabytes (64000000 bytes)
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- Send the message "Running out of memory!" when the alert fires
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You can do that with a configuration like this:
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Save the changes to apply this config.
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[Wait a minute. Where will this alert go to?](conversation://Mara/hmm)
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It will only show up on the alerts page:
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But we can add a notification channel to customize this. Click on the
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Notification Channels tab and then click "New Channel". It should look something
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like this:
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You can send notifications to many services, but let's send one to Discord this
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time. Acquire a Discord webhook link from somewhere and paste it in the Webhook
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URL field. Name it something like "Discord". It may also be a good idea to make
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this the default notification channel using the "Default" checkbox under the
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Notification Settings, so that our existing alert will show up in Discord when
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the system runs out of memory.
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You can configure other alerts like this so you can monitor any other node
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metrics you want.
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[You can also monitor for the _lack_ of data on particular metrics. If something
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that should always be reported suddenly isn't reported, it may be a good
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indicator that a server went down. You can also add other services to your
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`scrapeConfigs` settings so you can monitor things that expose metrics to
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Prometheus at `/metrics`.](conversation://Mara/hacker)
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Now that we have metrics configured, let's enable Loki for logging.
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## Loki
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Loki is a log aggregator created by the people behind Grafana. Here we will use
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it as a target for all system logs. Unfortunately, the Loki NixOS module is very
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basic at the moment, so we will need to configure it with our own custom yaml
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file. Create a file in your `configuration.nix` folder called `loki.yaml` and
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copy in the config from [this
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gist](https://gist.github.com/Xe/c3c786b41ec2820725ee77a7af551225):
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Then enable Loki with your config in your `configuration.nix` file:
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```nix
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# hosts/chrysalis/configuration.nix
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services.loki = {
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enable = true;
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configFile = ./loki-local-config.yaml;
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};
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```
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Promtail is a tool made by the Loki team that sends logs into Loki. Create a
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file called `promtail.yaml` in the same folder as `configuration.nix` with the
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following contents:
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```yaml
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server:
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http_listen_port: 28183
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grpc_listen_port: 0
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positions:
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filename: /tmp/positions.yaml
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clients:
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- url: http://127.0.0.1:3100/loki/api/v1/push
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scrape_configs:
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- job_name: journal
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journal:
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max_age: 12h
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labels:
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job: systemd-journal
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host: chrysalis
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relabel_configs:
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- source_labels: ['__journal__systemd_unit']
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target_label: 'unit'
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```
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Now we can add promtail to your `configuration.nix` by creating a systemd
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service to run it with this snippet:
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```nix
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# hosts/chrysalis/configuration.nix
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systemd.services.promtail = {
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description = "Promtail service for Loki";
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wantedBy = [ "multi-user.target" ];
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serviceConfig = {
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ExecStart = ''
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${pkgs.grafana-loki}/bin/promtail --config.file ${./promtail.yaml}
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'';
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};
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};
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```
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Now that you have this all set up, you can push this to your cluster with
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nixops:
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```console
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$ nixops deploy -d home
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```
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Once that finishes, open up Grafana and configure a new Loki data source with
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the URL `http://127.0.0.1:3100`:
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Now that you have Loki set up, let's query it! Open the Explore view in Grafana
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again, choose Loki as the source, and enter in the query `{job="systemd-journal"}`:
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[You can also add Loki queries like this to dashboards! Loki also lets you query by
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systemd unit with the `unit` field. If you wanted to search for logs from
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`foo.service`, you would need a query that looks something like
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`{job="systemd-journal", unit="foo.service"}` You can do many more complicated
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things with Loki. Look <a
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href="https://grafana.com/docs/grafana/latest/datasources/loki/#search-expression">here
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</a> for more information on what you can query. As of the time of writing this
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blogpost, you are currently unable to make Grafana alerts based on Loki queries
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as far as I am aware.](conversation://Mara/hacker)
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---
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This barely scrapes the surface of what you can accomplish with a setup like
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this. Using more fancy setups you can alert on the rate of metrics changing. I
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plan to make NixOS modules to make this setup easier in the future. There is
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also a set of options in
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[services.grafana.provision](https://search.nixos.org/options?channel=20.09&from=0&size=30&sort=relevance&query=grafana.provision)
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that can make it easier to automagically set up Grafana with per-host
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dashboards, alerts and all of the data sources that are outlined in this post.
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The setup in this post is quite meager, but it should be enough to get you
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started with whatever you need to monitor. Adding Prometheus metrics to your
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services will go a long way in terms of being able to better monitor things in
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production, do not be afraid to experiment!
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