Alerting is at the heart of proactive system monitoring, especially when managing dynamic environments that involve complex infrastructure. Datadog, a leading monitoring and observability tool, provides engineers and IT teams with the flexibility to set up detailed alert systems through its monitor feature.

Whether you're tracking resource usage, application performance, or specific events within your ecosystem, Datadog monitors help ensure you stay ahead of potential issues.

In this guide, we'll explore how to create monitors in Datadog, manage "no data" alerts, handle events, and monitor logs. We’ll also dive into setting up composite monitors, dynamic alerts, and practical examples of alert setups.

Finally, we’ll address a common challenge: alert fatigue and how to handle it effectively using Datadog alongside Doctor Droid.

In Datadog, alerts are managed through a feature called monitors, which function like alert rules in other monitoring systems. Monitors allow you to track and respond to changes in your infrastructure, application, or services based on specific conditions.

They help ensure that you’re notified when a system metric or performance crosses a predefined threshold.

Here’s how you can create a monitor (alert) in Datadog:

1. Log in to Datadog: Access your Datadog account using your credentials.

2. Navigate to Monitors: Click on "Monitors" in the left-hand sidebar.

3. Create a New Monitor:

• Click on the "New Monitor" button.
• Select "Metric" as the detection method.

4. Configure the Monitor:

• Detection Method:

When you set up a metric monitor, the system automatically defaults to the Threshold Alert method—this type of alert checks metric values against predetermined thresholds. Since the objective is to trigger alerts based on a fixed threshold, no further adjustments are needed for this monitor configuration.

• Define the metrics:

To receive an alert for low disk space, utilize the system.disk.in_use metric from the Disk integration, and calculate the average value across both the host and device.

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• Alert Condition:

As outlined in the Disk integration documentation, the system.disk.in_use metric represents the percentage of disk space currently being used, expressed as a fraction of the total available space. For instance, if this metric shows a value of 0.7, it indicates that 70% of the disk is occupied.

To monitor low disk space, the alert should activate when this metric exceeds a specific threshold, which can be customized based on your requirements. Typically, values between 0 and 1 are used for this metric.

Set the following threshold:

For this example, leave the other settings in this section on the defaults. For more details, see the Metric Monitors documentation.

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• Notification Options:

Configure how you want to be notified when an alert is triggered. You can choose email, SMS, or other notification methods.

• Automation:

Set up automated actions to take when an alert is triggered, such as running a script or sending a webhook.

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5. Permissions

To restrict who can edit your monitor, click Edit Access and limit access to specific individuals such as the monitor's creator, teams, users, groups, or specific roles within your organization. Additionally, you can choose the Notify option to receive alerts when any modifications are made to the monitor.

6. Save and Enable the Monitor:

• Click "Save" to create the monitor.
• Toggle the "Enabled" switch to activate the monitor.

7. Test the Alert:

To ensure the alert is functioning correctly, simulate a condition that should trigger it and verify that you receive the expected notification.

By following these steps, you can effectively create custom alerts in Datadog to monitor your systems and applications for potential issues.

For more detailed steps on creating monitors in Datadog, refer to Datadog Monitors Documentation.

Datadog's No Data Alerts is a useful tool for getting notified when an  Integration/application stops sending metrics to Datadog.

Two Monitor configuration options can be adjusted to evaluate these types of metrics properly:

• Delay Evaluation: This option allows the monitor to wait for a specified period (e.g., 900 seconds) before evaluating the metric. This can be helpful for backfilled metrics, such as those coming from AWS, which may not be immediately available in Datadog.

• Require a Full Window of Data:

This option determines whether the monitor requires a complete set of data for the evaluation window. Enabling this is typically recommended for metrics reported by the Datadog Agent and those with current timestamps.However, for sparse metrics or metrics that don't report at consistent frequencies, keeping the default option "Do Not Require a Full Window of Data" is advised.

‍Here are some additional points to consider:

• Cloud metric delays can vary depending on the cloud provider.
• To receive metrics with minimal delay, installing the Datadog Agent on your cloud hosts is recommended whenever possible.

For a detailed guide on No Data alerts, visit Datadog No Data Alerts Guide.

Event monitors in Datadog enable you to track and alert on specific system or application-level events such as service restarts, crashes, or critical logs. These monitors are useful when you want to be notified of significant occurrences that may impact the performance or availability of your infrastructure.

Steps to Create Event-Based Alerts in Datadog:

1. Access Event Monitor Setup: To create an event monitor, navigate to the Monitors section in the Datadog dashboard and select Event Monitor as the monitor type. Event monitors allow you to set up alerts based on specific event logs or custom events in your infrastructure.
2. Choose Event Sources: Select the source of the event data you want to monitor. Datadog can ingest event data from various sources:
   • System logs
   • Application logs
   • Custom events sent via Datadog APIs or integrations (e.g., Slack, AWS CloudWatch)
3. Define Search Criteria: Specify the search criteria to identify the events you want to trigger an alert on. You can use keywords, tags, or metadata from logs to filter for the relevant events.
4. Set Alert Conditions: Determine the conditions under which the alert will trigger. You can configure the monitor to alert you based on the frequency of the event or its severity.
5. Configure Notifications: Once the event-based alert is defined, set up notifications through your preferred channels, such as email, Slack, or PagerDuty. You can also configure escalation policies to handle critical events.
6. Test and Deploy: Before deploying the monitor, you can preview the alert to ensure that the conditions are met and the monitor works as expected. Once deployed, Datadog will continuously evaluate incoming events and trigger alerts accordingly.

For more detailed guidance, refer to Datadog's Event Monitors Documentation.

Logs monitors in Datadog allow you to set up alerts based on patterns or specific content found within your application or system logs. These alerts help capture issues like error spikes, performance bottlenecks, or security vulnerabilities, ensuring that your team is immediately notified when something unusual occurs in your logs.

Steps to Create and Monitor Log Alerts:

1. Access Log Monitor Setup: In the Datadog dashboard, navigate to the Monitors section and select Log Monitor. This type of monitor allows you to define conditions based on logs ingested into Datadog from your applications and systems.
2. Define Log Query: Set up a query to filter the logs based on specific criteria. For example, you can create a query to search for log entries containing keywords like "error" or "critical." Datadog allows you to apply advanced filters and aggregate logs based on tags, hosts, or services.
3. Set Alert Conditions: Define the conditions for triggering an alert. You can specify thresholds for the number of log events over a certain time period. For example, trigger an alert if an error message appears more than 10 times within 5 minutes.
4. Configure Notification Channels: Once the log alert conditions are defined, set up notifications to be sent via your preferred channels (e.g., email, Slack, or PagerDuty). This ensures that your team is notified promptly when logs indicate an issue.
5. Monitor and Analyze Logs: After setting up the log alert, Datadog will continuously monitor your logs for the specified patterns or conditions. You can view real-time logs, analyze past data, and use dashboards to track issues as they develop. This helps identify and resolve problems before they escalate.
6. Testing and Tuning: Before deploying the monitor, you can test it by simulating log entries that match your alert conditions. Tuning your log queries and thresholds helps reduce false positives and ensures that only critical issues are flagged.

For more details on creating and monitoring log alerts, visit Datadog's Logs Monitor Documentation.

Composite Metric Monitors in Datadog allow you to combine multiple monitors into a single one. This is useful when you want to trigger an alert only if certain conditions from multiple monitors are met simultaneously.

This helps reduce alert noise and ensures that alerts are only triggered for significant events that meet several criteria at once, thus providing more meaningful alerts for complex environments.

How to Create a Composite Monitor:

1. Access Monitor Setup: Navigate to the Monitors section in Datadog and select Composite Monitor.
2. Choose Monitors: Select the monitors you wish to combine.
3. Define Conditions: Specify the conditions that must be met for the composite monitor to trigger an alert. You can use logical operators (AND/OR) to define how the selected monitors interact.
4. Set Notification Channels: Configure where alerts should be sent (e.g., Slack, email, or PagerDuty).
5. Test and Deploy: Preview and test your composite monitor setup before deploying it to ensure it works as expected.

For more details, visit Datadog’s Composite Monitor Documentation.

Dynamic alerts in Datadog allow you to create flexible, adaptive alerts that adjust based on real-time data and environmental variables. By leveraging template variables, tag-based grouping, and intelligent alert routing, you can configure alerts that adapt to the changing landscape of your infrastructure and services.

Steps to Create Dynamic Alerts:

1. Use Template Variables for Alerts

Template variables allow you to create alerts that can dynamically adjust based on certain parameters. For example, you can create a monitor with variables for different hosts or services, ensuring that the alert conditions automatically adjust based on the service being monitored. This helps prevent the need to create multiple monitors for each host or service.

2. Tag-Based Alerts for Flexibility

You can configure alerts to be triggered based on tags. This allows you to monitor specific subsets of your infrastructure or services dynamically.

Watch this video to learn more about Tag-based alerts.

3. Dynamic Routing with Alert Policies

Datadog allows for intelligent dynamic alert routing through notification policies. You can set up policies to ensure that alerts are routed to the right teams based on the severity, source, or tag of the event.

For example, critical alerts from production servers can be routed to a different team compared to non-critical alerts from development environments.

4. Automate the Creation of Dynamic Monitors

You can automate the creation of dynamic monitors using scripts and configuration management tools. This ensures that as new services, hosts, or instances are deployed, new alerts are automatically created and customized based on predefined variables and templates.

For more detailed automation techniques, see this guide on creating monitors dynamically.

In this section, we’ll explore a few sample alert setups, including Kubernetes monitoring, Java application metrics monitoring, and disk space usage monitoring. These examples demonstrate how Datadog helps businesses stay proactive in managing the performance and health of their infrastructure and applications.

1. Creating and Monitoring Kubernetes Alerts with Datadog

Kubernetes is widely used for container orchestration, and monitoring its components is essential to maintaining the health of your clusters. Datadog enables you to monitor critical Kubernetes metrics and trigger alerts when issues arise.

To set up Kubernetes alerts:

• Monitor Kubernetes Metrics: Start by collecting metrics from your Kubernetes clusters, such as pod status, node health, CPU, and memory usage.
• Set up Alerts for Critical Events: Use Datadog’s Kubernetes integration to create alerts for critical conditions like high pod CPU usage, memory saturation, or unhealthy nodes.

Example Use Case:

You can create an alert that notifies you when the CPU usage of a pod exceeds 80% for over 10 minutes, helping you quickly take corrective action.

For more on setting up Kubernetes alerts, check out Datadog’s Kubernetes monitoring guide.

2. Monitoring and Analyzing Java Application Metrics using Datadog

Datadog’s Application Performance Monitoring (APM) provides end-to-end visibility into Java applications, enabling you to track important metrics like request latency, throughput, error rates, and garbage collection performance.

To set up Java application alerts:

• Integrate Java APM: Use Datadog’s Java agent to collect traces and performance metrics from your Java applications.
• Monitor Key Metrics: Set up monitors for critical metrics such as latency, error rates, or slow transactions.

Example Use Case:

Set up an alert that triggers when the average response time of your Java application exceeds a certain threshold, ensuring timely identification of performance bottlenecks.

For more details on Java performance monitoring, refer to Datadog’s Java APM documentation.

3. Monitoring Disk Space Usage with Alerts in Datadog

Monitoring available disk space is essential for ensuring that your servers and applications run smoothly without interruption due to storage limitations.

To monitor disk space usage:

• Enable Disk Integration: Datadog provides a disk integration to collect metrics like disk usage and available storage.
• Create Disk Space Alerts: Set up alerts that trigger when disk usage crosses a predefined threshold (e.g., 90% full).

Example Use Case:

You can configure an alert that notifies you when the disk usage on any server exceeds 85%, giving you time to allocate additional storage or clean up unnecessary files.

For more information on setting up disk space alerts, refer to Datadog’s disk monitoring guide.

By setting up these sample alerts, businesses can prevent potential performance issues and maintain a stable, well-functioning infrastructure.