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

WordPress大学
WordPress大学
F
Fortinet All Blogs
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
S
Secure Thoughts
SecWiki News
SecWiki News
Hacker News: Ask HN
Hacker News: Ask HN
Google DeepMind News
Google DeepMind News
N
Netflix TechBlog - Medium
Recorded Future
Recorded Future
Hacker News - Newest:
Hacker News - Newest: "LLM"
Webroot Blog
Webroot Blog
Cloudbric
Cloudbric
博客园 - 司徒正美
The Cloudflare Blog
W
WeLiveSecurity
T
Tailwind CSS Blog
V2EX - 技术
V2EX - 技术
H
Heimdal Security Blog
Jina AI
Jina AI
MyScale Blog
MyScale Blog
S
SegmentFault 最新的问题
Apple Machine Learning Research
Apple Machine Learning Research
雷峰网
雷峰网
罗磊的独立博客
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Project Zero
Project Zero
C
CXSECURITY Database RSS Feed - CXSecurity.com
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
博客园 - 【当耐特】
Forbes - Security
Forbes - Security
Last Week in AI
Last Week in AI
G
GRAHAM CLULEY
C
Check Point Blog
P
Proofpoint News Feed
L
LINUX DO - 最新话题
博客园 - Franky
P
Proofpoint News Feed
T
Tor Project blog
S
Security @ Cisco Blogs
Hugging Face - Blog
Hugging Face - Blog
阮一峰的网络日志
阮一峰的网络日志
J
Java Code Geeks
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
宝玉的分享
宝玉的分享
C
Cyber Attacks, Cyber Crime and Cyber Security
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
O
OpenAI News
小众软件
小众软件
云风的 BLOG
云风的 BLOG
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报

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 Tanzu Kubernetes Grid on vSphere with Datadog
Aaron Kaplan · 2023-01-06 · via Datadog | The Monitor blog

With vSphere and Tanzu Kubernetes Grid (TKG), VMware enables enterprise organizations to combine the economic advantages of virtual machines (VMs) with the agility, portability, and scalability provided by Kubernetes.

vSphere is VMware’s platform for the provisioning and management of VMs. vSphere’s vCenter Servers enable organizations to centrally manage and monitor their VMs, while its ESXi hypervisors help them optimize their infrastructure and reduce costs by strategically allocating bare-metal server resources. TKG is VMware’s turnkey solution for deploying and managing Kubernetes clusters at enterprise scale.

We’re pleased to announce that Datadog now supports monitoring TKG clusters deployed on vSphere as well as their underlying VM resources. Our vSphere integration now comes with an additional out-of-the-box (OOTB) dashboard and base configurations that enable you to start monitoring your TKG VMs immediately. And by installing the Datadog Agent on your TKG clusters, you can collect container-, pod-, and node-level metrics.

This post will guide you through monitoring TKG on vSphere holistically using real-time metrics and events from both your TKG clusters and their underlying vSphere hosts and VMs.

Monitor your entire vCenter and Kubernetes environment in real time

Our new OOTB dashboard, shown below, provides a fine-grained overview of your entire TKG and vSphere environment.

Get the big picture of your vSphere-hosted containers in real time

This dashboard foregrounds key data on your TKG clusters and their host VMs via the vSphere Containers map and the TKG event stream. The container map provides a high-level breakdown of your containers by namespace, while the event stream provides an up-to-the-minute record of container activity, highlighting any errors or warnings. You can use template variables to easily adjust the scope of your monitoring by homing in on individual containers, VMs, vCenters, pods, hosts, clusters, and namespaces.

The dashboard Overview panel, shown below, graphs the total number of pods running—both overall and by namespace—as well as the CPU and memory usage of your vSphere hosts. This data can be instrumental in ensuring that your VMs have sufficient resources, providing cues for scaling, as well as highlighting any unexpected dips or spikes in your pods.

The dashboard overview provides a detailed breakdown of your running TKG pods as well as the resource usage of your vSphere hosts

Manage and troubleshoot your TKG resources

The OOTB dashboard also features dedicated overviews of your TKG pods and containers. These overviews utilize events alongside a broad array of metrics generated from Datadog’s Kubernetes and Kubernetes State Metrics Core integrations so that you can oversee, optimize, and troubleshoot your vSphere environment’s Kubernetes resources in a single pane of glass.

Monitor your TKG environment with rich metrics on your individual pods and containers

The Pods overview panel provides detailed visibility into the overall status and resource consumption of your pods.

The number of active, failed, and successful pods in a given scope is measured via the kubernetes_state.pod.status_phase metric, providing a high-level breakdown of the health and performance of your overall TKG environment or any subset of it. For a measure of activity by namespace, the kubernetes_state.pod.count and kubernetes_state.pod.ready metrics are used to rank your namespaces both by number of pods running and by number of unavailable pods. The latter metric is also used to measure the number of pods in a Ready state per node.

In order to keep you apprised of any potential strain on your compute resources, the kubernetes.cpu.usage.totaland kubernetes.memory.usage metrics are used to highlight resource-intensive pods, providing visibility that can be critical for pinpointing errors.

The Containers overview offers rich visibility into the states and performance of your TKG containers, providing further angles from which to troubleshoot and optimize performance.

The kubernetes_state.container.status_report.count.waiting metric can highlight potential issues by proportionally mapping the top reasons your containers are Waiting. These can range from ContainerCreating to CrashLoopBackOff states.

The Containers overview also provides several perspectives on the states of your containers as a whole, graphing the total numbers of Ready, Running, Terminated, and Waiting containers in a given scope. To facilitate troubleshooting, this overview also visualizes the number of inoperative or potentially faulty containers per pod via a range of metrics, including:

  • kubernetes.containers.state.terminated: the number of containers OOMKilled (i.e., terminated due to insufficient memory resources)

  • kubernetes.containers.state.waiting: the number of containers in a CrashLoopBackOff state

  • kubernetes.containers.restarts: the number of container restarts

The kubernetes.network.rx_bytes, kubernetes.network.tx_bytes, kubernetes.network.rx_errors, and kubernetes.network.tx_errors metrics are used to track the network throughput and error rate of containers by pod.

Finally, for a broader picture of the health and performance of your TKG infrastructure, the kubernetes.cpu.usage.totaland kubernetes.memory.usage metrics are used to graph resource usage by container.

Manage and troubleshoot your vSphere resources

The vSphere overview, shown below, leverages metrics and events to provide critical visibility into the VMs and bare-metal hypervisors that underpin your TKG environment.

Assess the health and performance of your vSphere hosts, VMs, and datastores

The vsphere.cpu.usage.avg and vsphere.mem.usage.avg metrics are used to graph the CPU and memory usage of your VMs and their ESXi hosts, and to highlight those consuming the most resources.

For visibility into your vSphere datastores, the vsphere.disk.capacity.latest metric enables you to assess their available storage space, while the vsphere.disk.used.latest and vsphere.disk.capacity.latest metrics provide a clear picture of their disk utilization.

By correlating these metrics with vSphere events, as well as Kubernetes metrics and events from your TKG clusters, you can stay on top of errors and make the most of your usage of TKG on vSphere.

Optimize and troubleshoot TKG on vSphere

Our new OOTB dashboard and base configurations for Datadog’s vSphere integration enable you to quickly start monitoring your TKG clusters and their underlying vSphere VMs. They provide you with the real-time insights you need in order to continuously optimize your organization’s virtualized and containerized resources and rapidly troubleshoot issues with the aid of event and log tracking. Check out our documentation to get started. If you’re brand-new to Datadog, sign up for a 14-day free trial today.