惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

V
Visual Studio Blog
C
CERT Recently Published Vulnerability Notes
雷峰网
雷峰网
美团技术团队
L
LangChain Blog
Google DeepMind News
Google DeepMind News
博客园 - 【当耐特】
I
InfoQ
www.infosecurity-magazine.com
www.infosecurity-magazine.com
J
Java Code Geeks
B
Blog
博客园 - 三生石上(FineUI控件)
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
S
Secure Thoughts
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
博客园_首页
博客园 - Franky
Apple Machine Learning Research
Apple Machine Learning Research
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
GbyAI
GbyAI
TaoSecurity Blog
TaoSecurity Blog
N
Netflix TechBlog - Medium
H
Heimdal Security Blog
T
Troy Hunt's Blog
N
News and Events Feed by Topic
V2EX - 技术
V2EX - 技术
腾讯CDC
Forbes - Security
Forbes - Security
P
Privacy & Cybersecurity Law Blog
I
Intezer
Hacker News - Newest:
Hacker News - Newest: "LLM"
Y
Y Combinator Blog
The Register - Security
The Register - Security
Martin Fowler
Martin Fowler
Hugging Face - Blog
Hugging Face - Blog
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Blog — PlanetScale
Blog — PlanetScale
L
Lohrmann on Cybersecurity
Security Latest
Security Latest
AWS News Blog
AWS News Blog
Scott Helme
Scott Helme
Webroot Blog
Webroot Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
MongoDB | Blog
MongoDB | Blog
Vercel News
Vercel News
Engineering at Meta
Engineering at Meta
大猫的无限游戏
大猫的无限游戏
A
Arctic Wolf
S
Security Affairs
P
Privacy International News Feed

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 logs and metrics with Datadog
2021-05-12 · via Datadog | The Monitor blog

Cloudflare is a content delivery network (CDN) that organizations across industries use to secure the reliability of their websites, applications, and APIs. With a wide array of security, networking, and performance-management tools, millions of web applications employ Cloudflare’s DDoS protection, load balancing, and serverless compute-monitoring features to maintain high performance and uptime.

Datadog’s Cloudflare integration already collects key metrics that give you deep insight into your Cloudflare DNS, security and CDN performance. Now, Datadog can ingest HTTP request logs and events directly through Cloudflare’s Logpush service and collect additional metric datasets that let you monitor the health and performance of your Cloudflare Workers and load balancing utilities. This gives you more insight into your content delivery infrastructure so your teams can respond to issues more quickly and reduce service downtime for your customers. Once you’ve enabled the integration and data is flowing into Datadog, you can use our new out-of-the-box Cloudflare dashboard to monitor key Cloudflare metrics and logs from a single pane of glass.

Datadog's out-of-the-box Cloudflare dashboard gives you a full-picture perspective of your Cloudflare activity.

Analyze the full scope of your Cloudflare logs

Datadog can ingest the full volume of logs emitted by your Cloudflare assets in real time, giving you full visibility into the actions and events occurring across your CDN. After enabling the integration you can create a Logpush job on Cloudflare to begin forwarding your Cloudflare logs, including HTTP request logs, Spectrum events, and Firewall events. Datadog automatically enriches your logs and parses out key metadata from them, such as the source of requests, IP addresses, and response status codes. You can use Datadog to analyze and correlate this data with metrics, traces, logs, and other telemetry from more than 1,000 other services and technologies.

If you don’t want to ingest Cloudflare logs, you can still collect the most pertinent information from them by using Datadog Observability Pipelines. Observability Pipelines will extract metrics from your Cloudflare logs before they leave your environment, enabling you to ship logs to your preferred destination, drop them, or retain them in a cost-effective, long-term storage solution, like Flex Logs.

Troubleshoot user problems faster with logs

While Cloudflare metrics provide a big-picture perspective and alert you to issues with the performance of your CDN infrastructure, Cloudflare logs contain key information about any incoming request to your application. This gives you more context around problems and helps speed up your investigation and response. For example, if you receive a user ticket about your website running slow, you can easily filter your Cloudflare logs in the Log Explorer by that user’s IP address to isolate their specific queries and get additional information, such as their user ID in your application. By filtering your application logs with this user ID, you can then examine all the up- and downstream requests for this user. You may end up identifying that this user belongs to a beta-tester group that leverages a new microservice, which is bottlenecking all of their requests.

Cloudflare logs in the Log Explorer filtered based on IP address.

Expand your monitoring reach with new Cloudflare metrics

In addition to DNS and Request metrics, Datadog now collects metrics related to your Cloudflare Workers and load balancers, giving you deeper visibility into the performance of your Cloudflare-powered applications.

Keep your Workers working

Cloudflare Workers is Cloudflare’s serverless computing service that allows you to deploy and automatically scale applications within Cloudflare’s network. This enables you to serve complex content right where your users are without needing to provision your own local infrastructure.

Datadog collects key Workers metrics, such as request count, errors, and response time, and automatically tags them with the relevant script. This makes it easy to identify specific scripts that are experiencing performance issues. For example, you might receive a notification that a Worker script that renames files (from machine-generated to human-readable names) when a user downloads them is experiencing high p75 latency (cloudflare.workers.response_time.75p). The increase could be related to either a new code change to the script, or from increased traffic. By correlating the worker latency with HTTP request metrics, you can track the issue and determine whether increased traffic is the culprit. If not, you can then inspect the relevant logs to see whether the spike is due to a new code push that you should roll back.

Visualize and alert on key metrics across your Workers scripts.
Datadog lets you visualize your Cloudflare Workers metrics, making it easy to spot behavioral anomalies.
Visualize and alert on key metrics across your Workers scripts.

Maintain balance

Load balancing is critical to ensuring your application servers split user traffic as planned. For example, if you are preparing for an upcoming maintenance window for a subset of servers, you need to ensure that all connections to these servers are drained and requests are properly redirected before the servers can be taken offline.

Datadog collects key metrics and tags related to your Cloudflare load balancers so that you can monitor changes in traffic flows across your load balancer. Visualizing load balancer request counts (load_balancer.pool.health.status) for each application pool helps you ensure that Cloudflare is correctly shifting load from one application pool to another. You can also monitor request count by the status of their HTTP response (cloudflare.requests.status) to check that error rates remain steady.

Additionally, monitoring the round-trip time for your load balancers (load_balancer.pool.round_trip_time.average) provides visibility into server-side latency, which helps you determine if a deployment is going smoothly. If you use a CI/CD workflow for your application, you can ensure that new deployments are slowly introduced into your production environment. For instance, you might only apply your new deployment to a small load balancer pool that receives 5 percent of all incoming traffic. This lets the new deployment propagate for a period, during which you can monitor the pool-specific round-trip time and error rates and safely test your changes in a production environment without impacting all of your customer traffic.

Start monitoring your Cloudflare CDN today

Datadog’s Cloudflare integration provides you with more visibility than ever before into your CDN’s activity and gives you more ways to detect and secure your infrastructure against threats and operational failures. And with DNS monitoring and Real User Monitoring, Datadog can help you ensure that users are always able to access your applications. If you’re already a Datadog customer, you can start exploring the new Cloudflare metrics and logs now. And if you’re not, get started today with a 14-day free trial.