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

Martin Fowler
Martin Fowler
Webroot Blog
Webroot Blog
博客园 - 叶小钗
阮一峰的网络日志
阮一峰的网络日志
V
V2EX
雷峰网
雷峰网
Apple Machine Learning Research
Apple Machine Learning Research
博客园 - 【当耐特】
Hugging Face - Blog
Hugging Face - Blog
美团技术团队
云风的 BLOG
云风的 BLOG
IT之家
IT之家
S
Secure Thoughts
U
Unit 42
G
GRAHAM CLULEY
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
N
News and Events Feed by Topic
The Cloudflare Blog
月光博客
月光博客
V
Visual Studio Blog
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
Schneier on Security
Schneier on Security
O
OpenAI News
Hacker News - Newest:
Hacker News - Newest: "LLM"
P
Privacy International News Feed
The Hacker News
The Hacker News
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
T
Tailwind CSS Blog
SecWiki News
SecWiki News
M
MIT News - Artificial intelligence
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Simon Willison's Weblog
Simon Willison's Weblog
Stack Overflow Blog
Stack Overflow Blog
爱范儿
爱范儿
Last Week in AI
Last Week in AI
C
Check Point Blog
D
Docker
Scott Helme
Scott Helme
Engineering at Meta
Engineering at Meta
博客园_首页
W
WeLiveSecurity
MongoDB | Blog
MongoDB | Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
V
Vulnerabilities – Threatpost
D
Darknet – Hacking Tools, Hacker News & Cyber Security
J
Java Code Geeks
NISL@THU
NISL@THU
S
Security Affairs
C
Cybersecurity and Infrastructure Security Agency CISA
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More

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
Introducing Host Maps: know thy infrastructure
K Young · 2015-03-10 · via Datadog | The Monitor blog
K Young

K Young

A bird’s-eye view

If you’ve ever needed to understand what is happening right now on all your hosts, today’s a great day. We’ve just added Host Maps to Datadog, and we think you’re going to like them.

Host Maps let you see all of your hosts together on one screen, grouped however you want, filtered however you want, with metrics made instantly comprehensible via color and shape. This is a new and simple way to spot outliers, detect usage patterns, avoid resource problems, and make decisions about how to best manage your infrastructure. Host Maps work at any scale, whether you have 10, 100 or 10,000 hosts.

When you use Host Maps, we wanted the experience to be like waving a magic wand, and having every host leap to attention, telling you the high-level story instantly, ready to report further details on demand. The video above shows Host Maps in action.

Ways to use it

We built Host Maps for ultimate flexibility; with just a few clicks, you can ask innumerable infrastructure-level questions and get instant, visual answers. Below are some common uses, but we would also love to hear on twitter about the ways you use Host Maps at your company (@datadoghq).

Resource Optimization

If you are an AWS user, you probably use a variety of instance types. Some instances are optimized for memory, some for compute, some are small, some are big. If you want to reduce your AWS spend, a great place to start is by figuring out what the expensive instances are used for. With Host Maps this is easy. First group by “instance-type” and then group by role or name. Take a look at your expensive instance types, such as c3.8xlarge. Are there any host roles whose CPU is underutilized? If so, you can zoom in to individual hosts and see whether all that computational horsepower has been needed in the last several months, or whether this group of hosts is a candidate for migrating to a cheaper instance type.

Below is a subset of Datadog’s infrastructure. As you can see, c3.2xlarge instances are pretty heavily loaded.

Datadog Host Maps Instance Groups

As seen below, by clicking on the c3.2xlarge group and then sub-grouping by role, we found that only some of the roles are loaded, while others are nearly idling. If we downgraded those 7 green nodes to a c3.xlarge, we would save almost \$13K per year. That’s worth investigating! ( \$0.21 saved per hour per host x 24 hr/day * 365 days/year * 7 hosts = \$12,877.20 / year )

Datadog Host Maps Instance-Role Groups

Availability Zone Placement

Host maps make it easy to see distributions of machines in each of your availability zones (AZ). Filter for the hosts you are interested in, group by AZ, and you can immediately see whether resources need rebalancing. As seen below, at Datadog we have an uneven distribution of hosts with role:daniels across availability zones. (Daniels is the name of one of our internal applications.)

Datadog Host Maps AZ Balance

Problem Investigation

Imagine you are having a problem in production. Maybe the CPUs on some of your hosts are pegged, which is causing long response times. Host Maps can help you quickly see whether there is anything different about the loaded and not-loaded hosts. You can rapidly group by any dimension you would like to investigate, and visually determine whether the problem servers belong to a certain group. For example, you can group by availability zone, region, instance type, image, or any tag that you use at your company. You will either find a problem very quickly, or rule out these explanations before spending time on deeper investigations.

Below is a screenshot from a recent issue we had a Datadog. As you can see, some hosts had much less usable memory than others, despite being part of the same cluster. Why? We grouped by machine image in Host Maps, and the problem was immediately clear: there were in fact two different images in use, and one of them had become overloaded.

Datadog Host Maps Two Memory Usage Bands
Datadog Host Maps Two Image Groups

Conclusion

We hope you’ll love this new way of using Datadog to understand what is happening on all your hosts right now. We found that Host Maps’ fast and intuitive interface immediately ratcheted up our own team’s level of understanding of our infrastructure and made our daily ops work more efficient... and fun, too.

For details about how to use Host Maps, continue to part two.

Please let us know what you think! Twitter: @datadoghq