Grafana Alerting is a powerful feature that enables users to monitor metrics and receive notifications when predefined conditions are met. Whether you're overseeing infrastructure, applications, or performance metrics, alerting helps you stay proactive by signaling when something needs attention.

This guide will provide a comprehensive walkthrough of Grafana's alerting system, covering everything from creating alerts to more advanced capabilities like using variables and configuring notifications.

With the rise of real-time monitoring, the importance of setting up reliable alerting mechanisms cannot be overstated. Grafana Alerting integrates seamlessly with different data sources, including Prometheus, and provides flexibility in configuring alert rules, notification policies, and message templates.

By the end of this guide, you’ll have a deep understanding of how to create, configure, and fine-tune alerting workflows within Grafana to ensure timely responses to critical issues.

Setting Up Alert Message Templates

Grafana uses Go templating for alert message customization, which allows for flexible and dynamic content in notifications. You can insert dynamic variables, use conditional logic, and format the message based on the alert details.

This diagram demonstrates the complete templating workflow, from querying labels and formatting the alert summary and notification to producing the final alert message.

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1. Basic Template Structure

The alert message typically consists of the following:

• Title: The subject or headline of the alert notification.
• Body: Detailed information about the alert, including metrics, conditions, and any important context.
• Labels & Annotations: Dynamic variables that provide context, such as server names, data sources, and alert severity.

2. Using Variables in Templates

Grafana offers a variety of dynamic variables that can be included in templates:

• Common Labels: These represent alert-level labels like alertname, severity, or instance.
• Annotations: Custom metadata, such as descriptions or summaries, are added to alerts.
• Status Variables: These indicate the status of the alert, e.g., firing or resolved.
• Group Labels: Useful for grouping multiple alerts in a single notification.

3. Formatting Alert Messages

Grafana allows for rich formatting using markdown in alert messages. You can add bullet points, links, code blocks, and more to make the alert easier to read and action.

4. Conditional Logic in Templates

Templating in Grafana allows conditional logic to be applied to message formatting.

For instance, you can create different messages based on the severity or status of the alert.

Here’s a sample notification template consolidating all active and resolved alerts within a notification group.

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The notification sent to the contact point would appear as follows:

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Best Practices for Grafana Alert Message Formatting

• Keep Messages Clear and Concise: Avoid overloading alert messages with too much information. Provide enough context for the recipient to understand and act on the alert without being overwhelmed.
• Use Dynamic Variables: Leverage dynamic variables to include key information such as the affected instance, the triggered metric, and the status of the alert.
• Incorporate Links to Dashboards: Include links back to Grafana dashboards or relevant documentation to give recipients a direct path to investigate further.
• Use Severity Levels for Prioritization: Ensure that the alert message clearly states the severity of the issue so that the appropriate level of attention is given.

By mastering alert message templates and formatting in Grafana, you can significantly improve how you communicate critical issues, making your alerting system more effective and actionable for your team.

Learn more about Grafana Alert Message Templates here.

Understanding Grafana Alert Conditions & Metrics

In Grafana, alert conditions and metrics form the foundation of the alerting system. These conditions define when an alert should be triggered based on specific metrics, allowing you to monitor and respond to any deviations from expected performance.

Understanding how to configure alert conditions is key to creating effective, meaningful, and actionable alerts.

What Are Alert Conditions?

Alert conditions are the set of logical expressions that determine when an alert is triggered. These conditions evaluate the metrics retrieved from your data sources and check whether the data meets certain thresholds or criteria over a specified period of time. When a condition is met (for example, CPU usage exceeding 80% for more than 5 minutes), Grafana will change the alert state and notify the relevant parties.

Components of Alert Conditions:

• Metric Query: This is the first step in defining an alert condition. You need to specify which metrics Grafana should query. For instance, you might query CPU utilization, memory usage, or response times.
• Reducers: Once the metric query retrieves the data, a reducer function is applied to transform the data series into a single value. Common reducers include average, max, min, and last.
• Evaluators: The evaluator compares the reduced value against a threshold you define. For instance, you may set an evaluator to trigger an alert if the average CPU usage is greater than 80%.
• Condition Time Frame: You can define how long a metric must remain in a certain state before triggering the alert (e.g., CPU usage > 80% for 5 minutes).

Setting Up Alert Conditions

1. Define the Metric Query:

First, you specify the data source and the metric you want to monitor. For example, you might want to monitor a server's CPU usage, so you would query the relevant metric from your data source.

1. Apply the Reducer Function:

Next, apply a reducer function to condense your metric data.

For example, if you’re monitoring CPU usage across multiple servers, you might use the max() function to track the highest CPU usage among all servers.

1. Set the Evaluation Criteria:

Define the criteria that will determine whether an alert should be triggered. For instance, you may set an evaluator to trigger an alert if the max CPU usage exceeds 80% for more than 5 minutes.

1. Time Window for Evaluation:

Grafana allows you to configure the time window during which the alert condition is evaluated. You can set alerts to be evaluated at specific intervals, such as every minute or every 5 minutes, depending on how critical the metric is.

Types of Metrics and Conditions

Grafana supports a wide range of metrics from various data sources, including Prometheus, InfluxDB, Graphite, and others. Some common metrics used for alert conditions include:

• System Performance Metrics: CPU usage, memory usage, disk I/O, network latency.
• Application Metrics: Response times, error rates, request counts.
• Database Metrics: Query performance, connection times, failed queries.
• Custom Business Metrics: Metrics relevant to business-specific processes, such as transactions per minute, sales conversions, or customer support response times.

Example of Alert Conditions

• High CPU Usage Alert:
  • Query: CPU usage
  • Reducer: max
  • Evaluator: greater than 80%
  • Time frame: 5 minutes
  • Action: Trigger alert if CPU usage exceeds 80% for more than 5 minutes.

Best Practices for Configuring Alert Conditions

• Choose Metrics Wisely: Focus on metrics that directly impact your operations or systems. Avoid unnecessary alerts from trivial metrics.
• Set Appropriate Thresholds: Define thresholds that are meaningful for your environment. For example, a CPU usage of 80% might be fine for one application but concerning for another.
• Consider Alert Frequency: Ensure that alert conditions are configured to avoid alert fatigue. Too many false positives can overwhelm your team and reduce the effectiveness of alerts.
• Combine Multiple Conditions: Grafana allows you to combine multiple conditions to create more sophisticated alerts. For example, you could create an alert that only triggers if both CPU and memory usage are above 80% for a prolonged period.

By understanding how to configure alert conditions and select the right metrics, you can build a robust monitoring system that notifies your team of critical issues before they become major problems.

Learn more about configuring alert conditions in Grafana here

How to Create Prometheus Alerts within Grafana

Prometheus is a powerful monitoring and alerting system that works seamlessly with Grafana to visualize and manage metrics. Prometheus alerts are triggered based on rules that monitor time series data.

By integrating Prometheus with Grafana, you can configure and visualize alerts directly from your Grafana dashboards, allowing for efficient monitoring and actionable insights. Below is a guide on how to create Prometheus alerts within Grafana.

1. Set Up Prometheus Data Source in Grafana

Before creating alerts, you must first set up Prometheus as a data source in Grafana:

• Navigate to Configuration > Data Sources in the Grafana UI.
• Click Add Data Source and select Prometheus.

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• Enter the URL of your Prometheus server ( if you’re running it locally).
• Configure any authentication or additional settings as required.
• Click Save & Test to ensure Grafana can connect successfully to your Prometheus instance.

2. Create a Prometheus Query

To create an alert, start by defining a query in Grafana that pulls the desired metrics from Prometheus. This query will serve as the basis for your alert condition:

• Open your Grafana dashboard and add a new panel.
• Select Prometheus as the data source.
• Write a Prometheus query in the Query tab. For example, to monitor CPU usage across all servers, you might use:

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• Visualize the query results to ensure the data looks correct.

3. Create and Configure Alert Rules

With your query defined, you can now set up the alert rules:

• In the panel editor, switch to the Alert tab and click Create Alert.
• Configure the Alert Rule by defining:
  • Conditions: For example, you might want to trigger an alert when the average CPU usage exceeds 80% over a 5-minute window:

• Evaluation Interval: Set how frequently Grafana should evaluate this condition (e.g., every minute).
• Alert State Handling: Define actions for when the alert transitions between different states, such as "OK," "Pending," or "Alerting".

4. Configure NotificationsOnce your alert rule is configured, you need to specify where and how you want to be notified:

• In the Alert tab, click on Notification Policies.
• Choose the appropriate contact point (e.g., email, Slack, PagerDuty).
• Set up a notification channel to define who should be notified when the alert is triggered.
• Optionally, configure notification policies like grouping, silencing, and escalation.

5. Test and Validate Prometheus AlertsBefore deploying alerts to production, it’s a good idea to test your configurations:

• Trigger a test alert by temporarily lowering the threshold to see if the alert fires as expected.
• Check your notifications to ensure that alerts are delivered to the appropriate channels.
• Verify that the alert is resolved when the metrics return to normal levels.

6. Prometheus Alerting with Alertmanager

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For more advanced alert management, consider integrating Prometheus with Alertmanager, which handles silencing, deduplication, and routing of alerts:

• Set up Alertmanager by configuring the alertmanager.yml file.
• Define alert routes, receivers (such as email, Slack, or PagerDuty), and silence rules in the configuration.
• Once Alertmanager is connected to Prometheus, Grafana can visualize alert rules from Alertmanager alongside other Prometheus metrics, giving you a unified view of both alerts and performance data.

Best Practices for Prometheus Alerts

• Avoid Over-Alerting: Set thresholds that are meaningful to avoid false positives and alert fatigue.
• Combine Alerts: Group-related alerts are used to prevent excessive notifications, particularly during large incidents.
• Monitor Critical Metrics: Prioritize alerts for critical metrics that directly impact your infrastructure or applications.
• Test Alerts Regularly: Periodically test your alerts to ensure that they are still relevant and functioning as expected.

By integrating Prometheus alerts into Grafana, you can efficiently monitor your system metrics and respond quickly to issues, all while benefiting from Grafana’s visualization capabilities.

Learn more about setting up Prometheus alerts in Grafana

Setting up alerts directly from Grafana dashboard panels enables real-time monitoring of critical metrics and conditions. Grafana allows you to create alerts based on the visualized data in your dashboard panels, which is essential for detecting and responding to issues quickly.

Here’s a step-by-step guide to setting up alerts from Grafana dashboard panels:

1. Choose a Panel and Enter Edit Mode

To begin, choose the dashboard panel from which you want to trigger an alert:

• Open your Grafana dashboard.
• Click on the panel title you want to create an alert from, then click Edit from the drop-down menu.

2. Configure Your Query

In the panel editor, configure the metric query that will serve as the foundation for your alert. The query defines the data you want to monitor:

• Switch to the Query tab.
• Write or adjust the Prometheus or other data source query to retrieve the metric data you want to monitor (e.g., CPU usage, memory utilization, response time).

3. Create an Alert Rule

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Once your query is configured, switch to the Alert tab to create an alert rule:

• Click Create Alert to start setting up the alert.
• Define the conditions that will trigger the alert. This typically involves setting thresholds for your metrics.

4. Set Alert Conditions

Define your alert conditions based on your query. The conditions tell Grafana when to fire an alert:

• Reduce Function: Choose a reduction function like avg() or max() to summarize the data over time.
• Evaluator: Specify the threshold that will trigger the alert. For instance, an evaluator can be set to trigger when CPU usage exceeds 80%.
• Time Frame: Define how long the condition must be met before triggering the alert (e.g., CPU usage > 80% for 5 minutes).

5. Set the Evaluation Interval

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The evaluation interval controls how often Grafana checks whether the conditions for the alert are met:

• Define how frequently the alert rule should be evaluated (e.g., every 1 minute).

This helps ensure that alerts are triggered promptly based on the latest data.

6. Configure Notification Channels

After defining your alert rules and conditions, configure where and how you want to be notified:

• Go to the Notification tab to specify the notification channels. Grafana supports multiple notification methods, including email, Slack, PagerDuty, and custom webhooks.
• Select or configure a Notification Channel where the alert will be sent.

Example:

• If you're using Slack, configure your Slack webhook URL to receive alert notifications in a designated Slack channel.

7. Test the Alert

Before deploying the alert in production, it's important to test it to ensure it behaves as expected:

• Use the Test Rule button to simulate the alert conditions and verify that the notification is sent correctly.
• Adjust the alert thresholds or conditions if necessary based on your test results.

8. Save and Apply the Alert

Once you’re satisfied with the alert setup, save your changes:

• Click Save & Apply to activate the alert rule.
• Grafana will now monitor the specified metric and trigger an alert when the conditions are met.

9. Monitor Active Alerts

To monitor your active alerts across all panels and dashboards:

• Add an Alert List panel to your dashboard, which will display the status of all active and resolved alerts in real-time.
• The Alert List panel helps you quickly assess the state of your infrastructure and the effectiveness of your alerting system.

By following these steps, you can successfully set up and manage alerts from Grafana dashboard panels, ensuring you’re immediately informed when key metrics cross critical thresholds. This setup allows you to respond to incidents quickly and efficiently, keeping your systems healthy and operational.

If you have any doubts, feel free to check out this video for more clarity.

In Grafana, handling "No Data" alerts is crucial to ensure you are aware of potential gaps in data collection or system outages. When monitoring critical systems, a lack of data could indicate underlying issues, such as misconfigurations, service downtime, or failures in data pipelines.

Properly managing "No Data" conditions prevents false negatives, ensuring that your alerting system remains reliable and actionable.

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What Are "No Data" Alerts?

A "No Data" alert is triggered when Grafana cannot retrieve data for a particular metric or query during the alert rule evaluation. This can occur due to various reasons, such as:

• The data source is temporarily unavailable.
• An issue in the data pipeline.
• Incorrect query configuration.
• The monitored system is offline.

These "No Data" scenarios can be problematic, as they might signal more serious underlying issues, such as system failures or miscommunication between Grafana and the data source.

Configuring "No Data" Alerts

Grafana provides options to handle "No Data" situations within the alert rule configuration. When creating an alert, you can specify how Grafana should behave if it encounters a "No Data" condition during evaluation.

1. Alert State Options for "No Data":
2. When setting up an alert rule, you can define the alert state that Grafana should enter if no data is returned by the query. The available options include:
3. • OK: Treats the absence of data as a normal condition.
   • No Data: Flags the lack of data as an issue and changes the alert state to "No Data."
   • Alerting: Treats the absence of data as an alert-triggering condition and sends a notification.
4. Configuring the appropriate response depends on your use case. For example, if the absence of data could signal a critical issue, you might want to set the alert state to "Alerting."
5. Fallback Options for "No Data":
6. Grafana allows you to set fallback actions for when no data is available:
7. • Treat "No Data" as Alerting: This option triggers an alert if no data is returned, signaling that something may be wrong with the data collection or source availability.
   • Set State to "No Data": This option updates the alert state to "No Data" without triggering an actual alert, helping you distinguish between issues due to data unavailability and actual metric breaches.
8. Handling "No Data" in Notification Policies:
9. In some cases, you may want to handle "No Data" differently depending on the alert context. Grafana's notification policies allow you to customize how and when notifications are sent. You can create policies that escalate or suppress notifications for "No Data" conditions, depending on the severity of the impact.

Best Practices for Handling "No Data" Alerts

• Evaluate Data Source Reliability: If you frequently encounter "No Data" scenarios, investigate the reliability of the data source. Ensure that the data pipeline is consistent and that queries are properly configured.
• Contextualize "No Data" Alerts: Consider the importance of missing data for your specific use case. For some metrics, no data might not be critical, whereas for others, it could indicate a serious problem (e.g., monitoring heartbeats or service uptime).
• Use Separate Alert States: Instead of treating all "No Data" conditions as alert-worthy, leverage Grafana’s flexibility to configure different alert states like "No Data" or "Alerting," depending on the situation.
• Testing and Fine-Tuning: Regularly test your alert rules to ensure that "No Data" conditions are handled appropriately. Fine-tune your settings to avoid unnecessary alerts while ensuring that critical situations are captured.

In addition to metric-based alerts, Grafana also supports alerting on log data, allowing you to monitor for specific patterns, anomalies, or errors directly within your logs. This capability is particularly useful for identifying issues such as system errors, application failures, or security incidents that might not be captured through traditional metric monitoring.

Here’s a step-by-step guide to creating alerts on log data in Grafana:

1. Ensure Log Data is Available

Before setting up alerts on log data, ensure that Grafana has access to your logs. Grafana can ingest logs from various sources, including Loki, ElasticSearch, Grafana Cloud Logs, and more. The log data should be properly ingested and indexed in the connected data source.

• Configure your data source by navigating to Configuration > Data Sources, selecting Loki or your preferred log data source, and ensuring the logs are available in Grafana.
• Test the connection to ensure log data is being correctly pulled into Grafana.

2. Create a Log Query

To create alerts on log data, start by building a log query that isolates the specific patterns or errors you want to monitor.

• Open your Grafana dashboard and select the panel where you want to visualize log data.
• In the Query tab, select Loki (or another log data source) as the data source.
• Write a log query to filter and search the logs. For example, to search for all occurrences of the keyword "error":

You can also filter logs based on labels, such as hostnames or log levels, to target specific areas of your infrastructure:

3. Configure the Alert Condition

Once your log query is defined, switch to the Alert tab to configure the alert condition:

• Condition: Define the threshold that will trigger the alert. Log data typically involves monitoring for a specific number of occurrences within a certain time window. For example, trigger an alert if more than 5 "error" logs are detected within 5 minutes.
• Reducer Function: Apply a reducer function to summarize the log query results. For instance, use count() to count the number of logs returned by the query within the specified time frame.
• Evaluator: Define the threshold for the number of log entries that would trigger the alert.

4. Set the Evaluation Interval

Define how frequently Grafana should evaluate the log data for the alert condition:

• Set an appropriate evaluation interval (e.g., every 1 minute) to ensure that log data is continuously monitored.

5. Configure Notifications

After configuring the alert condition, set up the notification channels to receive alerts when the log conditions are met:

• In the Notification tab, choose the channel(s) where alerts should be sent (e.g., email, Slack, or custom webhooks).
• Configure notification policies to group, route, or escalate alerts based on the severity of the log events.

6. Save and Test the Alert

Before finalizing, test the alert rule to ensure that it behaves as expected:

• Use the Test Rule option to simulate the alert by generating test log entries or adjusting the query temporarily to trigger the alert condition.
• Ensure that the notification is received correctly and that the alert resets when the logs return to normal conditions.

7. Fine-Tune Log Alerting

Once the alert is configured, fine-tune the alert conditions and notification settings to prevent false positives or alert fatigue. Consider adjusting thresholds, time frames, or notification rules based on the criticality of the log data.

As you become more familiar with Grafana's alerting system, you can take advantage of its advanced capabilities to refine and customize your alerts further. This includes adding labels to alerts, creating multiple alert rules within a single panel, and using variables to enhance alert configuration.

Adding Labels in Grafana Alerts

Labels are an important aspect of Grafana alerts that help categorize, filter, and identify alerts. Labels allow you to group alerts by specific criteria, making it easier to manage and respond to them effectively.

How to Add Labels:

Labels are key-value pairs that you can attach to your alerts. Grafana uses labels to identify the alert and associate it with relevant metadata, such as severity, instance, or region. To add labels to an alert rule, navigate to the Alert tab in the panel editor and include labels in your configuration.

For instance, one alert may have the label set {alertname="High CPU usage," server="server1"} and another may have {alertname="High CPU usage," server="server2"}. Despite having the same alertname label, they are considered distinct alert instances due to the difference in their server labels.

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Creating Multiple Alert Rules in One Grafana Panel

Grafana allows you to configure multiple alert rules within a single panel. This is useful when you want to monitor different metrics or conditions simultaneously but have them share the same visualization.

• How to Create Multiple Alert Rules:

In a single Grafana panel, you can create multiple alert rules by defining different conditions and thresholds for each metric query. For each query, set up individual alert rules in the Alert tab. Ensure that each alert rule has its own conditions, evaluation intervals, and notification settings. For example, you could create one alert for high CPU usage and another for low memory availability, both within the same panel.

This image illustrates a user creating seven alerts within a single panel, each generated from 7 different queries.

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Using Variables in Grafana Alert Configuration

Variables in Grafana provide dynamic values that can be used in dashboards, queries, and alerts. Using variables in alert configurations allows you to create more flexible and reusable alert rules, which can automatically adjust based on the selected variables.

• How to Use Variables in Alerts:

You can use variables in alert messages and configurations to provide more context to the alerts. For example, you can include the instance name, region, or any other variable dynamically within the alert rule or notification message. Variables can be referenced using the ${variable_name} syntax. This is especially useful when you want to create a single alert that applies to different data sources or regions.

Leveraging these advanced capabilities in Grafana allows you to customize and fine-tune your alerting strategy. Whether it's by adding labels for better categorization, creating multiple alert rules within a single panel, or using variables to make alerts more dynamic and reusable, these features provide greater flexibility and control over your alerting system.

As a result, you can create more targeted, efficient, and actionable alerts that better fit your monitoring needs.