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

Google DeepMind News
Google DeepMind News
Jina AI
Jina AI
IT之家
IT之家
J
Java Code Geeks
博客园_首页
Stack Overflow Blog
Stack Overflow Blog
量子位
I
InfoQ
博客园 - 【当耐特】
阮一峰的网络日志
阮一峰的网络日志
WordPress大学
WordPress大学
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
博客园 - 司徒正美
V
V2EX
博客园 - Franky
U
Unit 42
S
SegmentFault 最新的问题
美团技术团队
The Register - Security
The Register - Security
Last Week in AI
Last Week in AI
G
Google Developers Blog
aimingoo的专栏
aimingoo的专栏
博客园 - 叶小钗
M
MIT News - Artificial intelligence
博客园 - 聂微东
腾讯CDC
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
T
Troy Hunt's Blog
B
Blog
P
Palo Alto Networks Blog
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
P
Privacy International News Feed
K
Kaspersky official blog
The GitHub Blog
The GitHub Blog
C
Cisco Blogs
Microsoft Azure Blog
Microsoft Azure Blog
F
Fortinet All Blogs
S
Schneier on Security
C
CERT Recently Published Vulnerability Notes
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
Engineering at Meta
Engineering at Meta
TaoSecurity Blog
TaoSecurity Blog
小众软件
小众软件
T
Threatpost
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
Martin Fowler
Martin Fowler
AWS News Blog
AWS News Blog
V
Visual Studio Blog
Simon Willison's Weblog
Simon Willison's Weblog
H
Heimdal Security Blog

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 Windows app metrics and events with Datadog’s WMI and Microsoft Event Viewer integrations
Remi Hakim · 2015-08-14 · via Datadog | The Monitor blog
Remi Hakim

Remi Hakim

Microsoft’s Windows Management Instrumentation (WMI) is used to collect and manage performance metrics and counters for a wide range of popular Windows-based applications, including Microsoft Exchange, SharePoint, SQL Server, and IIS. WMI can also be used to track metrics for .NET applications. WMI’s counterpart, Microsoft Event Viewer, similarly collects discrete events and alerts from the same applications.

With Datadog’s WMI integration, you can pull in metrics from Windows applications for graphing, analysis, and alerting. In addition to being able to pull a wide range of common, preset performance counters, you can create your own metrics to be monitored from inside WMI for custom built applications within the .NET framework. Likewise, alerts and discrete events from Microsoft Event Viewer can be sent to Datadog’s Event Stream as well as being available for commenting and correlation analysis with metrics collected from WMI or from other sources.

Collecting metrics from custom .NET applications

Datadog’s WMI integration is especially useful for engineering teams that use the full Microsoft stack and who develop in .NET. You can use WMI and Datadog to track and report on your high-level .NET app metrics. In addition to WMI metrics, you can use Datadog’s StatsD .NET port to emit custom metrics directly from within your applications, allowing you to graph and correlate both system and application metrics.

IO read bytes per sec
IO read bytes per sec

Aggregating Windows app data precisely with tagging

Modern applications are often hosted on cloud platforms where underlying servers can scale up or down dynamically. As a result, performance data for these many servers must often be aggregated to gain an understanding of how an entire cluster of machines is performing. Any WMI or Microsoft Event Viewer data pulled into Datadog will have certain tags associated with it, originating from the cloud platform, configuration management tool, and other sources.

Tagging in graphs
Tagging in graphs

In an Azure environment, for instance, this would include region, clusters, and any other tags associated with that server. When you create your own WMI metrics or Microsoft Event Viewer events to track, you can also associate those metrics with whatever tags you set, and they can also be tracked and parsed in Datadog.

If you develop with .NET or run your application on Windows, you can sign up for a free trial of Datadog to gain visibility into these components.