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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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Understand, explore, and collaborate with Dashboard Details
2019-07-24 · via Datadog | The Monitor blog

Dashboards provide critical visibility into the performance and health of your environment. But if your organization uses hundreds or thousands of dashboards, or if you’ve recently transitioned to a new company or different team, it’s not always easy to understand the full significance of the data shown on every single dashboard.

To provide instant context around every dashboard—and to help you understand how they’re being used in your organization—we released the Dashboard Details feature. You can start exploring this new functionality by clicking the caret next to any dashboard title.

The Dashboard Details panel consists of three parts:

  • a Dashboard Description that explains the intended purpose of a particular dashboard.
  • a Suggested Dashboards section with an auto-generated list of recommended dashboards based on the usage patterns of your organization.
  • a Most Active Users section, which auto-populates a list of people who spend the most time viewing this dashboard, so that you can easily identify subject matter experts.

We hope these features help you get more out of your dashboards by simplifying cross-team collaboration and making it easier to get helpful context for troubleshooting.

Get instant context around every dashboard

Whether you’re viewing a custom dashboard or an out-of-the-box dashboard for a specific technology like NGINX, the Dashboard Description instantly provides rich context around the data shown. When you’re creating a dashboard, you can customize the description to explain what type of information is shown, to help ensure that your colleagues can extrapolate important information at a glance. You can even include links to resources, such as runbooks or wikis that can help users troubleshoot issues with that particular service.

In the screenshot below, you can see that this dashboard is designed to help users diagnose and repair any performance issues in the web app. It also explains how to use the dashboard’s template variables to isolate specific services for more targeted troubleshooting.

The Dashboard Description tab summarizes and explains your dashboard.

Dashboard Descriptions include support for Markdown, so you can add bulleted lists, code snippets, and links. You can edit descriptions directly in the Datadog UI or programmatically through Terraform. Whether you provide a brief blurb or a more detailed overview of the data shown, a well-crafted description can help other members of your organization immediately understand the purpose of that particular dashboard.

After you’ve familiarized yourself with the contents of your dashboard by reading the Descriptions, you can pivot to the Suggested Dashboards tab for additional insights. This feature uses machine learning to analyze usage patterns, discovering related dashboards to help you get more comprehensive insights into your systems.

For instance, in the Application Diagnostic View dashboard below, the Suggested Dashboards section recommends dashboards for various components of this web application, including HAProxy, NGINX, Redis, Apache, and Akamai Edge. By viewing these relevant dashboards, you can build a more detailed understanding of your web application, and effectively troubleshoot issues by drilling down to view important metrics like slow queries and dropped connections from specific components of your stack.

In order to get a different perspective, use this tab to find and use other, similar dashboards.

The Suggested Dashboards section can help you discover related dashboards and add them to relevant dashboard lists, either for specific teams (such as InfoSec or SRE) or important tasks (like troubleshooting your Kubernetes clusters).

Identify subject matter experts

If you’re working with a dashboard or technology that is outside your normal area of responsibility—or if you just have questions about a particular dashboard—you might wish to reach out to a power user for more information.

Use the Most Active Users tab to find power users who can answer your questions about specific dashboards.

The Most Active Users section makes it easy to identify subject matter experts for each dashboard. This section is algorithmically generated based on usage patterns in your organization, so you can immediately identify the most relevant colleagues to contact if you have a question about the data shown in a specific dashboard.

Dive into Dashboard Details for yourself

If you are currently a Datadog customer, you can try out the new Dashboard Details panel by clicking the dropdown menu next to any dashboard title. To see how this new dashboard feature can help you monitor your dynamic infrastructure and applications, start a free 14-day trial.