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

T
The Exploit Database - CXSecurity.com
F
Fortinet All Blogs
U
Unit 42
F
Full Disclosure
雷峰网
雷峰网
博客园 - 司徒正美
云风的 BLOG
云风的 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
T
Tailwind CSS Blog
The Cloudflare Blog
Last Week in AI
Last Week in AI
罗磊的独立博客
D
DataBreaches.Net
C
Check Point Blog
www.infosecurity-magazine.com
www.infosecurity-magazine.com
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
O
OpenAI News
C
CXSECURITY Database RSS Feed - CXSecurity.com
aimingoo的专栏
aimingoo的专栏
S
Security @ Cisco Blogs
大猫的无限游戏
大猫的无限游戏
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
S
SegmentFault 最新的问题
NISL@THU
NISL@THU
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
The Hacker News
The Hacker News
Webroot Blog
Webroot Blog
Security Latest
Security Latest
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
Google DeepMind News
Google DeepMind News
酷 壳 – CoolShell
酷 壳 – CoolShell
N
News | PayPal Newsroom
P
Proofpoint News Feed
B
Blog RSS Feed
MongoDB | Blog
MongoDB | Blog
C
Cybersecurity and Infrastructure Security Agency CISA
N
News and Events Feed by Topic
Google Online Security Blog
Google Online Security Blog
H
Help Net Security
Spread Privacy
Spread Privacy
T
Threat Research - Cisco Blogs
GbyAI
GbyAI
I
Intezer
Application and Cybersecurity Blog
Application and Cybersecurity Blog
M
MIT News - Artificial intelligence
Vercel News
Vercel News
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
IT之家
IT之家
MyScale Blog
MyScale Blog
腾讯CDC

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
Search and analyze unsampled logs in real time with Live Tail
2023-07-19 · via Datadog | The Monitor blog

With thousands of logs generated every minute from your infrastructure, applications, services, and devices, retaining all of this data for active search and analysis can be cost-prohibitive. Because log volumes continue to grow rapidly as operations scale, it’s common for organizations to implement log management strategies and limit the amount that they store in order to minimize costs. Deciding which logs need to be stored and analyzed can be highly complex, and retaining only a subset of logs can make it challenging to troubleshoot effectively.

Stream-based monitoring solutions that allow you to tail your live telemetry, detect security threats, and discover sensitive data are gaining popularity because they can support real-time troubleshooting and eliminate the need to store data that only needs to be used transiently.

To further build upon the versatility of our stream-based products, we’re pleased to announce that we’ve enhanced the capabilities of Live Tail, providing you with the ability to search, correlate, and perform analytics across all ingested logs for 15 minutes. With Live Tail, you’ll gain full access to the data that you need during real-time investigations and time-sensitive analyses.

Live Tail gives you visibility into all of your logs post-processing—completely unsampled—regardless of how you’ve configured your indexes, quotas, or exclusion filters. In this post, we’ll show you how to use Live Tail to:

Verify new deployments and streamline CI/CD troubleshooting

Live Tail can help you troubleshoot issues in your CI/CD pipeline in order to improve the efficiency of your development process. You can verify whether a new deployment has been successful by searching for keywords such as “deployment” and “failure” to get a bird’s-eye view of any issues that may have occurred. You can also quickly determine if hot fixes have successfully resolved an issue by viewing all logs that are ingested after you execute a change.

A timeseries visualization on the Live Tail page that shows the time that failed deployments occurred, categorized by service

Reviewing your logs in real time can become extremely valuable during peak traffic times for your application or website, as well as for live streaming major events, such as sports games and television premieres. A continuous, real-time stream of logs lets you better understand what platforms or devices your viewers use to tune in, where they are viewing from, and how many are logged in at any given time. This information can help you engage with your audience effectively and troubleshoot time-sensitive incidents during broadcast to minimize negative impact on viewership.

Correlate directly between live traces and logs

Live Tail for Log Management now conveniently correlates with APM Live Search so you can view, search, and analyze all logs within the last 15 minutes that are associated with a specific trace. This correlation really comes into play during reactive troubleshooting.

As an example, let’s say you’re an engineer and discover that an application is not processing requests. You begin to review live APM traces to try and determine the root cause of the issue, but when you select a trace, all you can see is that there is some form of server error. Instead of shooting in the dark through trial and error, you can directly pivot to the Live Tail page to investigate all logs associated with the trace. Using Live Tail to examine the logs enables you to bypass any sampling or exclusion filters that may be applied to your indexes.

By analyzing the logs, you pinpoint that the root cause is a batch API failure and see the code that was run on the most recent API call attempts. You can continue your investigation by pivoting between 15 minutes of live traces and live logs as needed until the issue is resolved.

Conversely, if you begin your investigation by viewing logs, you can also directly access the related APM traces via APM Live Search for a broader view into your stack.

A list of logs on the Live Tail page. Selecting an individual log shows a log side panel and the associated trace's information, including a flame graph

Because Live Tail enables you to access your unsampled logs in real time, you’ll obtain the context you need to identify root cause faster and accelerate time to resolution.

Logs on the stream

Live Tail for Datadog Log Management is designed to handle data at petabyte scale, and it enables you to view and query all ingested logs for troubleshooting and analysis without any pressure to retain them. With a real-time stream of logs, you have full visibility into the data that matters to you.

To learn more about Datadog Live Tail for Log Management, see our documentation. Don’t have a Datadog account yet? Sign up for a free trial.