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

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
Apple Machine Learning Research
Apple Machine Learning Research
T
Tailwind CSS Blog
月光博客
月光博客
爱范儿
爱范儿
有赞技术团队
有赞技术团队
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
aimingoo的专栏
aimingoo的专栏
GbyAI
GbyAI
腾讯CDC
The Cloudflare Blog
人人都是产品经理
人人都是产品经理
MongoDB | Blog
MongoDB | Blog
Microsoft Azure Blog
Microsoft Azure Blog
IT之家
IT之家
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
云风的 BLOG
云风的 BLOG
U
Unit 42
博客园 - 三生石上(FineUI控件)
A
About on SuperTechFans
N
Netflix TechBlog - Medium
Google DeepMind News
Google DeepMind News
雷峰网
雷峰网
L
LangChain 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
How to monitor Microsoft Azure VMs
2015-08-13 · via Datadog | The Monitor blog

This post is part 1 of a 3-part series on monitoring Azure virtual machines. Part 2 is about collecting Azure VM metrics, and Part 3 details how to monitor Azure VMs with Datadog.

What is Azure?

Microsoft Azure is a cloud provider offering a variety of compute, storage, and application services. Azure services include platform-as-a-service (PaaS), akin to Google App Engine or Heroku, and infrastructure-as-a-service (IaaS). In the most recent Gartner “Magic Quadrant” rating of cloud IaaS providers, Azure was one of only two vendors (along with Amazon Web Services) to place in the “Leaders” category.

In this article, we focus on IaaS. In an IaaS deployment, Azure’s basic unit of compute resources is the virtual machine. Azure users can spin up general-purpose Windows or Linux (Ubuntu) VMs, as well as machine images for applications such as SQL Server or Oracle.

Key metrics to monitor Azure

Whether you run Linux or Windows on Azure, you will want to monitor certain basic VM-level metrics to make sure that your servers and services are healthy. Four of the most generally relevant metric types are CPU usage, disk I/O, memory utilization and network traffic. Below we’ll briefly explore each of those metrics and explain how they can be accessed in Azure.

This article references metric terminology introduced in our Monitoring 101 series, which provides a framework for metric collection and alerting.

Users can monitor Azure with the following metrics via the Azure web portal or can access the raw data directly via the Azure diagnostics extension. Details on how to collect these metrics are available in the companion post on Azure metrics collection.

CPU metrics

CPU usage is one of the most commonly monitored host-level metrics. Whenever an application’s performance starts to slide, one of the first metrics an operations engineer will usually check is the CPU usage on the machines running that application.

NameDescriptionMetric type
CPU percentagePercentage of time CPU utilizedResource: Utilization
CPU user timePercentage of time CPU in user modeResource: Utilization
CPU privileged timePercentage of time CPU in kernel modeResource: Utilization

CPU metrics allow you to determine not only how utilized your processors are (via CPU percentage) but also how much of that utilization is accounted for by user applications. The CPU user time metric tells you how much time the processor spent in the restricted “user” mode, in which applications run, as opposed to the privileged kernel mode, in which the processor has direct access to the system’s hardware. The CPU privileged time metric captures the latter portion of CPU activity.

Metric to alert on: CPU percentage

Although a system in good health can run with consistently high CPU utilization, you will want to be notified if your hosts’ CPUs are nearing saturation.

Azure CPU heatmap

Disk I/O metrics

Monitoring disk I/O is critical for understanding how your applications are impacting your hardware, and vice versa. For additional visibility beyond the VM-level metrics covered here, you can also collect metrics from your Azure storage accounts to determine if your storage is being throttled or has availability issues that could impact performance.

NameDescriptionMetric type
Disk readData read from disk, per secondResource: Utilization
Disk writeData written to disk, per secondResource: Utilization

Metric to alert on: Disk read

Monitoring the amount of data read from disk can help you understand your application’s dependence on disk. If the application is reading from disk more often than expected, you may want to add a caching layer or switch to faster disks to relieve any bottlenecks.

Metric to alert on: Disk write

Monitoring the amount of data written to disk can help you identify bottlenecks caused by I/O. If you are running a write-heavy application, you may wish to upgrade the size of your VM to increase the maximum number of IOPS (input/output operations per second).

Azure disk write speed

Memory metrics

Monitoring memory usage can help identify low-memory conditions and performance bottlenecks.

NameDescriptionMetric type
Memory availableFree memory, in bytes/MB/GBResource: Utilization
Memory pagesNumber of pages written to or retrieved from disk, per secondResource: Saturation

Metric to alert on: Memory pages

Paging events occur when a program requests a page that is not available in memory and must be retrieved from disk, or when a page is written to disk to free up working memory. Excessive paging can introduce slowdowns in an application. A low level of paging can occur even when the VM is underutilized—for instance, when the virtual memory manager automatically trims a process’s working set to maintain free memory. But a sudden spike in paging can indicate that the VM needs more memory to operate efficiently.

Azure memory paging

Network metrics

Azure’s default metric set provides data on network traffic in and out of a VM. Depending on your OS, the network metrics may be available in bytes per second or via the number of TCP segments sent and received. Because TCP segments are limited in size to 536 bytes each, the number of segments sent and received provides a reasonable proxy for the overall volume of network traffic.

NameDescriptionMetric typeAvailability
Bytes transmittedBytes sent, per secondResource: UtilizationLinux VMs
Bytes receivedBytes received, per secondResource: UtilizationLinux VMs
TCP segments sentSegments sent, per secondResource: UtilizationWindows VMs
TCP segments receivedSegments received, per secondResource: UtilizationWindows VMs

Metric to alert on: Bytes/TCP segments sent

You may wish to generate a low-urgency alert when your network traffic nears saturation. Such an alert may not notify anyone directly but will record the event in your monitoring system in case it becomes useful for investigating a performance issue.

Metric to alert on: Bytes/TCP segments received

If your network traffic suddenly plummets, your application or network may be overloaded.

Azure network out

Conclusion

In this post we’ve explored several general-purpose metrics you should monitor to keep tabs on your Azure virtual machines. Monitoring the metric set listed below will give you a high-level view of your VMs’ health and performance:

Over time you will recognize additional, specialized metrics that are relevant to your applications. Part 2 of this series provides step-by-step instructions for collecting any metric you may need to monitor Azure.

Acknowledgments

Many thanks to reviewers from Microsoft for providing important additions and clarifications prior to publication.


Source Markdown for this post is available on GitHub. Questions, corrections, additions, etc.? Please let us know.