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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
Monitor Cloudflare Zero Trust with Datadog Cloud SIEM
Nimisha Saxena, Dayspring Johnson · 2023-07-27 · via Datadog | The Monitor blog

Cloudflare’s SASE is a zero trust network-as-a-service platform that dynamically connects users to enterprise resources, with identity-based security controls delivered close to users, wherever they are. Cloudflare spans more than 300 cities in over 100 countries, resulting in latencies under 50 milliseconds for 95 percent of the internet-connected population globally.

Today, we’re excited to announce that we’ve expanded our existing Cloudflare integration with out-of-the-box threat detection rules in Datadog Cloud SIEM that help you identify suspicious activity in your Cloudflare Zero Trust logs, an updated dashboard, and new Workflow Automation blueprints to assist with security monitoring, triage, and remediation. By using Cloudflare Zero Trust alongside Cloud SIEM, security teams can access a centralized solution that correlates network and security insights to address the complex risks posed by modern applications and cloud computing.

In this post, we’ll show you how to:

  • Send your Zero Trust logs to Datadog using Cloudflare Logpush

  • Analyze and correlate Cloudflare logs with Datadog Cloud SIEM’s out-of-the-box detections

  • Triage and respond to Cloudflare incidents using Datadog Workflow Automation and Case Management

  • Visualize security insights using Datadog’s updated Cloudflare dashboard

Send your Zero Trust logs to Datadog using Cloudflare Logpush

Cloudflare Zero Trust provides enhanced security for users, devices, and data across an organization by securing access to the corporate network, SaaS applications, email, and other resources. Enforcing access controls across all of these forms of traffic generates a high volume of logs, containing information such as accessed websites, application sign-ins, and shared data across systems. The ability to access and understand these logs helps teams achieve a holistic understanding of who is performing what activities within the environment, and when and where they are taking place.

To take advantage of this deepened integration, you can follow the two steps below to send logs using Logpush, Cloudflare’s tool for uploading logs to a cloud storage provider or monitoring service:

  1. Enable Logpush to Datadog: Cloudflare supports pushing logs directly to Datadog through the Cloudflare dashboard or using the API.

  2. Install the Cloudflare tile: Locate and install the Cloudflare Tile within the Datadog Integration catalog.

After the steps above, Datadog’s out-of-the-box log processing pipeline will automatically parse and normalize your Cloudflare Zero Trust logs. Standardizing the format of these logs helps structure them for easier analysis and correlation with your logs from other sources, so that Cloud SIEM can surface signs of related suspicious activity across all of your logs.

Analyze and correlate Cloudflare logs with Datadog Cloud SIEM’s out-of-the-box detections

Datadog Cloud SIEM’s integration with Cloudflare Zero Trust provides several capabilities that help you analyze your Cloudflare logs and correlate them with detection rules, so you can understand what’s happening in your environment and catch attacker behavior more quickly.

Security detections built for CASB

Datadog Cloud SIEM now has an out-of-the-box detection rule developed specifically for Cloudflare’s cloud access security broker (CASB), which will trigger a Security Signal whenever Cloudflare’s CASB finds anomalies that could indicate suspicious activity. Cloud SIEM users can quickly and easily catch Cloudflare CASB findings to immediately identify misconfigurations and other security issues that may pose threats to their SaaS applications.

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Security detections for impossible travel

With this integration, Datadog can also use your Cloudflare Zero Trust logs to detect impossible travel scenarios, which could indicate that user accounts have been hijacked by threat actors. Using the impossible travel detection method, Datadog Cloud SIEM compares the GeoIP data of the last log and the current log to determine if this activity indicates the user has traveled more than 500 km at over 1,000 km/h. If your log data indicates this impossible scenario has occurred, Cloud SIEM will surface a Security Signal so you can investigate whether the affected accounts have been accessed by unauthorized users.

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Security detections for DDoS attacks

Additionally, Datadog’s Cloud SIEM can now surface signals based on Cloudflare’s HTTP DDoS Attack Protection ruleset in order to immediately alert on DDoS attack vectors at layer 7 of the Cloudflare CDN (i.e., the application layer). Cloudflare’s DDoS protection rule set identifies known attack patterns and tools, suspicious patterns, protocol violations, requests causing large amounts of origin errors, excessive traffic hitting the origin or cache, and additional attack vectors at the application layer. The new out-of-the-box rule in Datadog Cloud SIEM will create a Security Signal when your Cloudflare logs contain the l7ddos attribute, so you can quickly catch indicators of a potential DDoS attack.

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Automate triage for Cloudflare incidents with Datadog Workflow Automation and Case Management

Datadog Workflow Automation orchestrates automated series of actions in response to alerts or security signals. You can now use a Datadog workflow to chain together Datadog-specific actions or actions from any of our integrations, including Cloudflare Zero Trust. Datadog now provides two Workflow Blueprints—out-of-the-box automations that you can use immediately or customize for your needs—that include Cloudflare actions: Block IP with Cloudflare and Check IP with GreyNoise and Block Using Cloudflare.

Say you receive a notification for a Security Signal in Datadog Cloud SIEM indicating suspicious activity in your Cloudflare Zero Trust logs. You can use the Block IP with CloudFlare workflow to automatically update the access rule in Cloudflare to remove access from the IP address associated with that activity. Additionally, Workflows integrate with Datadog Case Management, which allows you to create a centralized, easily accessible workspace for investigating your security signals. You can use this feature to add a step to your Workflow that creates a case in Datadog, so that while you’ve denied access to the suspicious user, you can triage and troubleshoot further and determine if you need to take more significant remediation steps, such as permanently blocking the IP address or remediating misconfigured IAM roles.

Visualize security insights in real time with Datadog’s updated Cloudflare dashboard

The revamped Cloudflare dashboard in Datadog now features sections with widgets that highlight various details about activity across the applications, devices, and users in your Cloudflare Zero Trust ecosystem. The new Zero Trust insights sections highlight various metrics and charts showing your Zero Trust sessions, CASB alerts, app usage over time, top devices and identities, rare devices and identities, and other key data points. With these details you can gain a holistic view of activity across your Zero Trust environment, helping you spot and respond to anomalies quickly.

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In addition, the new Cloud SIEM section of the Cloudflare dashboard provides a one-glance, real-time view of Cloudflare-related Security Signals that may indicate threats targeting your environment.

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Deeper insights into your Cloudflare Zero Trust logs

Datadog’s Cloudflare Zero Trust integration provides you with more visibility than ever before to detect and secure your environment against threats. If you’re already a Datadog customer, you can start exploring the new Cloudflare Zero Trust integration now. And if you’re not, get started today with a 14-day free trial.