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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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Triggered Alerts in Datadog - providing context to alerts
2013-09-10 · via Datadog | The Monitor blog

Have you ever received an alert on your phone or in your email that left you wondering what exactly what was wrong and how critical the issue was with respect to the rest of the application?

Typical alert with no useful information

In this example the alert mentions that a service is warning but omits to tell you whether the issue is picking up momentum, or if it’s just a slow march to failure.

Without context, it’s difficult to gauge whether the issue is a real problem that you must immediately work on and fix, or simply something that you should acknowledge and investigate later.

Ultimately, when analyzing an issue the following questions must be answered:

  • Is this a new or an old issue?
  • Is the alert indicative of a transient or recurring problem?
  • If the issue is recurring, is the time frame between alerts changing?
  • How intensely “off baseline” are the performance metrics that triggered the alert?

Datadog’s new Triggered Alert screen works to make available important contextual information with one click.

For starters, only alerts for which the alerting criteria are currently engaged are revealed. This allows for any investigation or work done for an alert to have an immediate impact, i.e. the alerting condition will cease.

Clicking on any triggered alert reveals key information in a modal drilldown screen such as:

  1. Scope: Which specific servers are affected
  2. Underlying Metric: Which metric and what its behavior has been
  3. History: How long the alert has been triggered. Has it happened in the past? How often?
Triggered-Alerts---Datadog

Administrators can begin a routine sweep of their environment by first accessing the Triggered Alerts page, and triaging system conditions which are causing problems at that exact minute.

Gaining this real-time insight into existing issues with the Triggered Alerts screen in an IT infrastructure is available with a free signup of Datadog.