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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - 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Tiered alerts: Urgency-aware alerting
2016-01-14 · via Datadog | The Monitor blog

Datadog alerts are commonly used to identify dips, spikes, or unhealthy trends in your metrics. For instance, you might alert on memory rapidly running out, or a dramatic drop in requested work. Alerts are built to automatically notify individuals or teams via the communication tools you already use, such as PagerDuty or Slack.

But alerts are only effective when they reach the right people. With Datadog’s new tiered alerts, you can trigger alerts that go to different people, or via different channels, depending on the alert severity. Now you can set a single alert to send email or chat notifications for relatively low-urgency issues, and to page the engineer on call if the situation gets worse.

This new feature works with any integration that supports regular metric alerts. The screenshot below shows a tiered alert configured for the haproxy.frontend.denied.req_rate metric.

Defining tiered alerts

The monitor has two threshold values set: an alert threshold (50), and a warning threshold (25). In this example, if the average metric value rises above either threshold, a specific alert action is triggered.

The right alerts, to the right people

With tiered alerts, you do not need to create multiple monitors for the same metric. You simply configure different severity levels so that no one will be awakened in the middle of the night over a minor issue, and so that major issues will not be missed. With the right people getting the alerts over the right channels, you can reduce alert fatigue significantly!

Try it

To set up your own tiered alert, navigate to the monitors page and choose Metric as your monitor type.

New metric monitor

Choose the metric you want to alert on, and define threshold values that are appropriate for your setup.

Set alert conditions

Next, you need to notify the right people. For alerts, wrap your notification message and recipient list in {{#is_alert}} and {{/is_alert}} tags; for warnings use {{#is_warning}} and {{/is_warning}}. See the screenshot below for an example.

Alert the right people

In the above screenshot, you can see the ops channel in Slack will be notified when the metric value exceeds the warning threshold, and Evan will be notified by email when the metric value is greater than the alert threshold.

Already a Datadog customer? You can now set up tiered alerts on any of your integrations, or on your own custom metrics. Otherwise, try it out today by signing up for a free trial of Datadog.