Grafana fundamentals

Grafana Labs Team
By Grafana Labs Team

Last update on October 7, 2022

Beginner

Introduction

In this tutorial, you’ll learn how to use Grafana to set up a monitoring solution for your application.

In this tutorial, you’ll:

  • Explore metrics and logs
  • Build dashboards
  • Annotate dashboards
  • Set up alerts

Prerequisites

Set up the sample application

This tutorial uses a sample application to demonstrate some of the features in Grafana. To complete the exercises in this tutorial, you need to download the files to your local machine.

In this step, you’ll set up the sample application, as well as supporting services, such as Prometheus and Loki.

  1. Clone the github.com/grafana/tutorial-environment repository.

    git clone https://github.com/grafana/tutorial-environment.git
    
  2. Change to the directory where you cloned this repository:

    cd tutorial-environment
    
  3. Make sure Docker is running:

    docker ps
    

    No errors means it is running. If you get an error, then start Docker and then run the command again.

  4. Start the sample application:

    docker-compose up -d
    

    The first time you run docker-compose up -d, Docker downloads all the necessary resources for the tutorial. This might take a few minutes, depending on your internet connection.

    Note: If you already have Grafana, Loki, or Prometheus running on your system, then you might see errors because the Docker image is trying to use ports that your local installations are already using. Stop the services, then run the command again.

  5. Ensure all services are up-and-running:

    docker-compose ps
    

    In the State column, it should say Up for all services.

  6. Browse to the sample application on localhost:8081.

Grafana News

The sample application, Grafana News, lets you post links and vote for the ones you like.

To add a link:

  1. In Title, enter Example.

  2. In URL, enter https://example.com.

  3. Click Submit to add the link.

    The link appears in the list under the Grafana News heading.

To vote for a link, click the triangle icon next to the name of the link.

Log in to Grafana

Grafana is an open-source platform for monitoring and observability that lets you visualize and explore the state of your systems.

  1. Open a new tab.

  2. Browse to localhost:3000.

  3. In email or username, enter admin.

  4. In password, enter admin.

  5. Click Log In.

    The first time you log in, you’re asked to change your password:

  6. In New password, enter your new password.

  7. In Confirm new password, enter the same password.

  8. Click Save.

The first thing you see is the Home dashboard, which helps you get started.

To the far left you can see the sidebar, a set of quick access icons for navigating Grafana.

Add a metrics data source

The sample application exposes metrics which are stored in Prometheus, a popular time series database (TSDB).

To be able to visualize the metrics from Prometheus, you first need to add it as a data source in Grafana.

  1. In the sidebar, hover your cursor over the Configuration (gear) icon, and then click Data sources.

  2. Click Add data source.

  3. In the list of data sources, click Prometheus.

  4. In the URL box, enter http://prometheus:9090.

  5. Click Save & test.

    Prometheus is now available as a data source in Grafana.

Explore your metrics

Grafana Explore is a workflow for troubleshooting and data exploration. In this step, you’ll be using Explore to create ad-hoc queries to understand the metrics exposed by the sample application.

Ad-hoc queries are queries that are made interactively, with the purpose of exploring data. An ad-hoc query is commonly followed by another, more specific query.

  1. In the sidebar, click the Explore (compass) icon.

  2. In the Query editor, where it says Enter a PromQL query…, enter tns_request_duration_seconds_count and then press Shift + Enter. A graph appears.

  3. In the top right corner, click the dropdown arrow on the Run Query button, and then select 5s. Grafana runs your query and updates the graph every 5 seconds.

    You just made your first PromQL query! PromQL is a powerful query language that lets you select and aggregate time series data stored in Prometheus.

    tns_request_duration_seconds_count is a counter, a type of metric whose value only ever increases. Rather than visualizing the actual value, you can use counters to calculate the rate of change, i.e. how fast the value increases.

  4. Add the rate function to your query to visualize the rate of requests per second. Enter the following in the Query editor and then press Shift + Enter.

    rate(tns_request_duration_seconds_count[5m])
    

    Immediately below the graph there’s an area where each time series is listed with a colored icon next to it. This area is called the legend.

    PromQL lets you group the time series by their labels, using the sum aggregation operator.

  5. Add the sum aggregation operator to your query to group time series by route:

    sum(rate(tns_request_duration_seconds_count[5m])) by(route)
    
  6. Go back to the sample application and generate some traffic by adding new links, voting, or just refresh the browser.

  7. In the upper-right corner, click the time picker, and select Last 5 minutes. By zooming in on the last few minutes, it’s easier to see when you receive new data.

Depending on your use case, you might want to group on other labels. Try grouping by other labels, such as status_code, by changing the by(route) part of the query.

Add a logging data source

Grafana supports log data sources, like Loki. Just like for metrics, you first need to add your data source to Grafana.

  1. In the sidebar, hover your cursor over the Configuration (gear) icon, and then click Data Sources.
  2. Click Add data source.
  3. In the list of data sources, click Loki.
  4. In the URL box, enter http://loki:3100.
  5. Click Save & Test to save your changes.

Loki is now available as a data source in Grafana.

Explore your logs

Grafana Explore not only lets you make ad-hoc queries for metrics, but lets you explore your logs as well.

  1. In the sidebar, click the Explore (compass) icon.

  2. In the data source list at the top, select the Loki data source.

  3. In the Query editor, enter:

    {filename="/var/log/tns-app.log"}
    
  4. Grafana displays all logs within the log file of the sample application. The height of each bar in the graph encodes the number of logs that were generated at that time.

  5. Click and drag across the bars in the graph to filter logs based on time.

Not only does Loki let you filter logs based on labels, but on specific occurrences.

Let’s generate an error, and analyze it with Explore.

  1. In the sample application, post a new link without a URL to generate an error in your browser that says empty url.

  2. Go back to Grafana and enter the following query to filter log lines based on a substring:

    {filename="/var/log/tns-app.log"} |= "error"
    
  3. Click on the log line that says level=error msg="empty url" to see more information about the error.

    Note: If you’re in Live mode, clicking logs will not show more information about the error. Instead, stop and exit the live stream, then click the log line there.

Logs are helpful for understanding what went wrong. Later in this tutorial, you’ll see how you can correlate logs with metrics from Prometheus to better understand the context of the error.

Build a dashboard

A dashboard gives you an at-a-glance view of your data and lets you track metrics through different visualizations.

Dashboards consist of panels, each representing a part of the story you want your dashboard to tell.

Every panel consists of a query and a visualization. The query defines what data you want to display, whereas the visualization defines how the data is displayed.

  1. In the sidebar, hover your cursor over the Create (plus sign) icon and then click Dashboard.

  2. Click Add a new panel.

  3. In the Query editor below the graph, enter the query from earlier and then press Shift + Enter:

    sum(rate(tns_request_duration_seconds_count[5m])) by(route)
    
  4. In the Legend field, enter {{route}} to rename the time series in the legend. The graph legend updates when you click outside the field.

  5. In the Panel editor on the right, under Settings, change the panel title to “Traffic”.

  6. Click Apply in the top-right corner to save the panel and go back to the dashboard view.

  7. Click the Save dashboard (disk) icon at the top of the dashboard to save your dashboard.

  8. Enter a name in the Dashboard name field and then click Save.

Annotate events

When things go bad, it often helps if you understand the context in which the failure occurred. Time of last deploy, system changes, or database migration can offer insight into what might have caused an outage. Annotations allow you to represent such events directly on your graphs.

In the next part of the tutorial, we will simulate some common use cases that someone would add annotations for.

  1. To manually add an annotation, click anywhere in your graph, then click Add annotation.

  2. In Description, enter Migrated user database.

  3. Click Save.

    Grafana adds your annotation to the graph. Hover your mouse over the base of the annotation to read the text.

Grafana also lets you annotate a time interval, with region annotations.

Add a region annotation:

  1. Press Ctrl (or Cmd on macOS), then click and drag across the graph to select an area.
  2. In Description, enter Performed load tests.
  3. In Tags, enter testing.

Manually annotating your dashboard is fine for those single events. For regularly occurring events, such as deploying a new release, Grafana supports querying annotations from one of your data sources. Let’s create an annotation using the Loki data source we added earlier.

  1. At the top of the dashboard, click the Dashboard settings (gear) icon.

  2. Go to Annotations and click Add annotation query.

  3. In Name, enter Errors.

  4. In Data source, select Loki.

  5. In Query, enter the following query:

    {filename="/var/log/tns-app.log"} |= "error"
    
  1. Click Add. Grafana displays the Annotations list, with your new annotation.
  2. Click the Go back arrow to return to your dashboard.
  3. At the top of your dashboard, there is now a toggle to display the results of the newly created annotation query. Press it so that it’s enabled.

The log lines returned by your query are now displayed as annotations in the graph.

Being able to combine data from multiple data sources in one graph allows you to correlate information from both Prometheus and Loki.

Annotations also work very well alongside alerts. In the next and final section, we will set up an alert for our app grafana.news and then we will trigger it. This will provide a quick intro to our new Alerting platform.

Create a Grafana Managed Alert

Alerts allow you to identify problems in your system moments after they occur. By quickly identifying unintended changes in your system, you can minimize disruptions to your services.

Grafana’s new alerting platform debuted with Grafana 8. A year later, with Grafana 9, it became the default alerting method. In this step we will create a Grafana Managed Alert. Then we will trigger our new alert and send a test message to a dummy endpoint.

The most basic alert consists of two parts:

  1. A Contact Point - A Contact point defines how Grafana delivers an alert. When the conditions of an alert rule are met, Grafana notifies the contact points, or channels, configured for that alert. Some popular channels include email, webhooks, Slack notifications, and PagerDuty notifications.
  2. An Alert rule - An Alert rule defines one or more conditions that Grafana regularly evaluates. When these evaluations meet the rule’s criteria, the alert is triggered.

To begin, let’s set up a webhook Contact Point. Once we have a usable endpoint, we’ll write an alert rule and trigger a notification.

Create a Contact Point for Grafana Managed Alerts

In this step, we’ll set up a new Contact Point. This contact point will use the webhooks channel. In order to make this work, we also need an endpoint for our webhook channel to receive the alert. We will use requestbin.com to quickly set up that test endpoint. This way we can make sure that our alert is actually sending a notification somewhere.

  1. Browse to requestbin.com.
  2. Under the Create Request Bin button, click the public bin link.

Your request bin is now waiting for the first request.

  1. Copy the endpoint URL.

Next, let’s configure a Contact Point in Grafana’s Alerting UI to send notifications to our Request Bin.

  1. Return to Grafana. In Grafana’s sidebar, hover your cursor over the Alerting (bell) icon and then click Contact points.
  2. Click + New contact point.
  3. In Name, write RequestBin.
  4. In Contact point type, choose Webhook.
  5. In Url, paste the endpoint to your request bin.
  6. Click Test to send a test alert to your request bin.
  7. Navigate back to the request bin you created earlier. On the left side, there’s now a POST / entry. Click it to see what information Grafana sent.
  8. Return to Grafana and click Save contact point.

We have now created a dummy webhook endpoint and created a new Alerting Contact Point in Grafana. Now we can create an alert rule and link it to this new channel.

Add an Alert Rule to Grafana

Now that Grafana knows how to notify us, it’s time to set up an alert rule:

  1. In Grafana’s sidebar, hover the cursor over the Alerting (bell) icon and then click Alert rules.
  2. Click + New alert rule.
  3. For Section 1, name the rule fundamentals-test, and set Rule type to Grafana Managed Alert. For Folder type fundamentals and in the box that appears, press Create: fundamentals.
  4. For Section 2, find the query A box. Choose your Prometheus datasource and enter the same query that we used in our earlier panel: sum(rate(tns_request_duration_seconds_count[5m])) by(route). Press Run queries. You should see some data in the graph.
  5. Now scroll down to the query B box. For Operation choose Classic condition. You can read more about classic and multi-dimensional conditions here. For conditions enter the following: WHEN last() OF A IS ABOVE 0.2
  6. In Section 3, enter 30s for the Evaluate every field. For the purposes of this tutorial, the evaluation interval is intentionally short. This makes it easier to test. In the for field, enter 0m. This setting makes Grafana wait until an alert has fired for a given time before Grafana sends the notification.
  7. In Section 4, you can add some sample text to your summary message. Read more about message templating here.
  8. Click Save and exit at the top of the page.
  9. In Grafana’s sidebar, hover the cursor over the Alerting (bell) icon and then click Notification policies.
  10. Under Root policy, press Edit and change the Default contact point to RequestBin. As a system grows, admins can use the Notification policies setting to organize and match alert rules to specific contact points.

Trigger a Grafana Managed Alert

We have now configured an alert rule and a contact point. Now let’s see if we can trigger a Grafana Managed Alert by generating some traffic on our sample application.

  1. Browse to localhost:8081.
  2. Repeatedly click the vote button or refresh the page to generate a traffic spike.

Once the query sum(rate(tns_request_duration_seconds_count[5m])) by(route) returns a value greater than 0.2 Grafana will trigger our alert. Browse to the Request Bin we created earlier and find the sent Grafana alert notification with details and metadata.

Summary

In this tutorial you learned about fundamental features of Grafana. To do so, we ran several Docker containers on your local machine. When you are ready to clean up this local tutorial environment, run the following command:

docker-compose down -v

Learn more

Check out the links below to continue your learning journey with Grafana’s LGTM stack.