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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 - February 2026 Amazon EC2 security: How misconfigured and public AMIs expand your cloud attack surface Enable end-to-end visibility into your Java apps with a single command Measure and improve mobile app startup performance with Datadog RUM Evaluating our AI Guard application to improve quality and control cost Identify untested code across every level of your codebase Make use of guardrail metrics and stop babysitting your releases Monitor Versa Networks SD-WAN performance in Datadog Improve performance and reliability with APM Recommendations Remediate transitive vulnerabilities faster with Datadog Software Composition Analysis Generate audit-ready vulnerability and compliance reports with Datadog Sheets Monitor Fortinet FortiManager performance in Datadog Improve test coverage across codebases with Datadog Code Coverage Move fast, don’t break things: Consistent testing standards at scale Enrich logs with ServiceNow CMDB context before routing to any SIEM or logging tool Monitor Lustre with Datadog Make faster, better product decisions with Datadog Product Analytics Surface and remediate runtime posture issues with Workload Protection Findings Protect agentic AI applications with Datadog AI Guard How to optimize JavaScript code with CSS Trace Google Pub/Sub workloads in Cloud Run with Datadog Detect human names in logs with ML in Sensitive Data Scanner How we cut our NLQ agent debugging time from hours to minutes with LLM Observability Debug PostgreSQL query latency faster with EXPLAIN ANALYZE in Datadog Database Monitoring Datadog acquires Propolis Unify and correlate frontend and backend data with retention filters Scale compliance across global frameworks with Datadog Cloud Security Monitor Arista VeloCloud SD-WAN performance with Datadog Building reliable dashboard agents with Datadog LLM Observability Simplify log collection and aggregation for MSSPs with Datadog Observability Pipelines Mitigation for Node.js denial-of-service vulnerability affecting Datadog APM Automate flaky test fixes with the Bits AI Dev Agent and Test Optimization How we built an AI SRE agent that investigates like a team of engineers Datadog integrations 2025 recap: Observability for AI, security, and hybrid cloud Design effective executive dashboards with Datadog Implement dbt data quality checks with dbt-expectations Bring faster visibility into AWS Lambda functions with remote instrumentation Troubleshoot faster with the GitLab Source Code integration in Datadog How Cambia Health Solutions saved $30,000 monthly with Cloud Cost Management and the Datadog Resource Catalog Normalize any logs for Cloud SIEM with Datadog's OCSF processor Optimizing Datadog at scale: Cost-efficient observability at Zendesk Detect, diagnose, and resolve network issues easily with CNM Network Health Connect engineering errors to user impact in early-stage products Cilium configuration for Kubernetes operations at scale Designing feedback loops for progressive delivery Ship features faster and safer with Datadog Feature Flags Choosing the right OpenTelemetry Collector distribution Route your monitor alerts with Datadog monitor notification rules Automate Cloud SIEM investigations with Bits AI Security Analyst Cloud threat detection: How to identify risky activity across control and data planes Collecting Kafka performance metrics Monitoring Kafka with Datadog Monitoring Kafka performance metrics
Centralize observability management with Datadog Governance Console | Datadog
David Iparraguirre · 2026-04-17 · via Datadog | The Monitor blog

As organizations grow, they face increasing difficulty in managing their observability efforts. More teams mean more dashboards, monitors, API keys, pipelines, and custom configurations. Without a centralized view, administrators spend hours chasing down untagged resources, investigating surprise bills, and revoking dormant credentials. Governance becomes a reactive effort to reduce waste and address issues, falling short of its potential to proactively create standards and optimize observability.

Datadog Governance Console helps solve this challenge by providing a centralized interface for managing observability usage, configuration, and hygiene. Governance Console transforms your organization’s configuration and usage activity into actionable insights and automates enforcement of best practices through built-in controls. Instead of managing governance through spreadsheets and ad hoc audits, you can monitor adoption of Datadog products and features, apply guardrails, and improve accountability from a single place.

In this post, we’ll explore how Governance Console helps you:

  • Understand how observability is implemented across your organization

  • Improve Datadog product configuration and adoption

  • Prevent configuration drift before it creates risk

Understand how observability is implemented across your organization

Governance Console gives you a consolidated view of Total Org Usage, enabling you to understand how Datadog is used across teams, services, and products. From the Summary page, you can monitor trends in active users, dashboards, monitors, and time spent in the product.

Governance Console summary view showing organization-wide usage metrics such as active users, dashboards, and monitors.

The Total Org Usage summary helps answer strategic questions that matter to VP-level observability leaders and platform engineering managers: Which teams are actively engaging with Datadog? Where is usage increasing? Where are assets accumulating without clear ownership? Rather than relying on anecdotal feedback or periodic reviews, you can reference measurable usage signals across your entire organization.

In addition, you gain a clear understanding of how consistently governance standards are being applied and where gaps remain. You can track governance metrics across areas such as tagging coverage, asset ownership, product utilization, and control adoption. Governance metrics help you prioritize cleanup efforts, focus outreach on specific teams, and allocate time and resources toward areas that will have the largest organizational impact.

Improve Datadog product configuration and adoption

High-level usage metrics provide directional clarity, but effective governance also requires deeper product-level context. Governance Console exposes per-product insights that help administrators understand how key platform features are configured and adopted throughout the organization.

For example, for Datadog Log Management, you can track:

  • The number of archives and custom destinations

  • Disabled or unused pipelines

  • Indexed log volume and quota usage

  • Monitors and dashboards built on log data

Governance Console product view displaying Log Management metrics such as archives, pipelines, indexed logs, and custom destinations.

Per-product insights help you optimize the value of the data that your organization generates. You can spot notable trends or adoption behaviors that need correction, such as large ingestion volumes that receive minimal querying or complex configurations that lack ownership tags. When patterns indicate configuration drift or inefficient usage, you can take action directly by applying controls to enforce standards, reduce waste, and bring configurations back into alignment.

Prevent configuration drift before it creates risk

To maintain standards and prevent configuration drift over time, organizations need automated guardrails that reduce administrative work. Governance Console includes a catalog of controls to detect issues, notify stakeholders, and enforce organizational standards in areas such as security, cost optimization, and data hygiene.

You can configure each control to follow a structured life cycle:

  1. Detection identifies noncompliant assets, such as unused API keys, unqueried metrics, and dashboards without team tags.

  2. Notification alerts accountable owners and administrators.

  3. Enforcement applies automated remediation, such as revoking inactive credentials or dropping unused metrics, for controls where it is available. When enabled, enforcement helps reduce security risk and limit unnecessary expenses by automatically correcting noncompliant configurations.

You can scope controls to specific environments, teams, or resource subsets to help you perform risk-managed rollouts. Platform teams can start with nonproduction environments or pilot groups, review detection results manually, and gradually expand automated enforcement when they’re confident that the control is operating as expected.

A common security use case is the Unused API Keys control, which identifies credentials that have not been used within a configurable threshold of time. Dormant keys increase attack surface and often go unnoticed in fast-growing environments. Governance Console can detect these keys, notify responsible owners, and optionally revoke them automatically after a remediation delay.

Governance Console control panel showing the Unused API Keys control with detection, notification, and enforcement options.

Scale observability governance with confidence

The larger your Datadog footprint grows, the harder it becomes to answer a simple question: Is everything configured the way it should be? Governance Console helps you answer that question proactively, giving your platform team continuous visibility and automated enforcement without manual overhead. Whether you’re preparing for a compliance review, cleaning up after rapid team growth, or trying to prevent drift that results in wasteful expenditures, Governance Console helps make Datadog manageable at scale. To learn more, check out the Governance Console documentation.

If you don’t have a Datadog account, you can sign up for a 14-day free trial to get started with Governance Console.