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
Tailwind CSS Blog
C
CERT Recently Published Vulnerability Notes
V
Visual Studio Blog
O
OpenAI News
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
The Cloudflare Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Last Week in AI
Last Week in AI
Y
Y Combinator Blog
博客园 - 聂微东
L
Lohrmann on Cybersecurity
P
Proofpoint News Feed
Simon Willison's Weblog
Simon Willison's Weblog
G
GRAHAM CLULEY
AI
AI
S
Security @ Cisco Blogs
TaoSecurity Blog
TaoSecurity Blog
Jina AI
Jina AI
W
WeLiveSecurity
大猫的无限游戏
大猫的无限游戏
腾讯CDC
K
Kaspersky official blog
Hugging Face - Blog
Hugging Face - Blog
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
宝玉的分享
宝玉的分享
AWS News Blog
AWS News Blog
月光博客
月光博客
P
Palo Alto Networks Blog
小众软件
小众软件
V2EX - 技术
V2EX - 技术
罗磊的独立博客
V
Vulnerabilities – Threatpost
J
Java Code Geeks
H
Heimdal Security Blog
S
SegmentFault 最新的问题
博客园 - 【当耐特】
Cyberwarzone
Cyberwarzone
S
Schneier on Security
博客园_首页
T
The Exploit Database - CXSecurity.com
Attack and Defense Labs
Attack and Defense Labs
Forbes - Security
Forbes - Security
N
News | PayPal Newsroom
IT之家
IT之家
Project Zero
Project Zero
Help Net Security
Help Net Security
P
Privacy International News Feed
爱范儿
爱范儿
D
Darknet – Hacking Tools, Hacker News & Cyber Security
T
Threat Research - Cisco Blogs

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
Get immediate visibility into Azure Kubernetes Service with Datadog's powerful AKS dashboard
2022-06-16 · via Datadog | The Monitor blog
Steve Harrington

Steve Harrington

We’re pleased to announce a new out-of-the-box dashboard for Azure Kubernetes Service (AKS) that allows you to immediately visualize the health and performance of your AKS clusters. This dashboard organizes and highlights the most critical information from the standard AKS metrics, while also incorporating log data to provide observability into the control plane.

In an AKS environment, Azure manages the control plane. This makes it simpler to deploy and run your containerized workloads. However, it also means visibility into these components is limited to a handful of standard Azure metrics, even after you’ve enabled Datadog’s Agent-based Kubernetes integration. AKS resource logs contain highly granular data about events occuring in the control plane, but it can be difficult to extract meaningful information from them. With this update, Datadog automatically processes and visualizes these logs in our new AKS dashboard, providing critical insights into the control plane—with no manual configuration required.

Visualize cluster health and performance in our new out-of-the-box AKS dashboard

Datadog’s new AKS dashboard makes it easy to keep tabs on your containerized workloads and visualize trends anywhere in your clusters, including in the control plane, where standard Azure Monitor metrics are limited. Within minutes of installing the Azure integration, the AKS dashboard delivers visibility into your clusters’ health and performance at the cluster, node, and pod levels. This enables you to monitor and alert on important AKS resource utilization metrics like CPU, memory, and storage usage, as well as cluster health information like pod phase and state.

Monitor your cluster’s control plane components

In a Kubernetes cluster, the control plane is responsible for managing worker nodes, scheduling pods, and moving the cluster to a desired state. Our new out-of-the-box AKS dashboard includes critical control plane data from the Kubernetes API server, scheduler, and controller manager.

Control plane data, which includes detailed information about control plane component events and errors, is not available in the standard Azure Monitor metrics. Instead, it is only accessible via AKS resource logs, which can be forwarded to Datadog by using our single-click log forwarding option through the Azure portal. From there, Datadog’s AKS log processing pipeline automatically parses these logs and extracts key data, such as event severity, message, and cause. This processing allows you to immediately leverage this data for insights into the operation of the AKS control plane, without any manual log configuration.

Quickly troubleshoot orchestration issues

The ability to visualize control plane data from the API server can provide valuable insights into the health and performance of your cluster’s orchestration layer. For example, if you’re seeing abnormally high latency in your application, this could indicate a scheduling issue related to the Kubernetes API server, which exposes the Kubernetes API and facilitates communication among cluster components. Using our new dashboard, you can check for an elevated error rate in the API server logs combined with a high or rising inflight request count to determine if this is contributing to the observed latency. The error messages and types will also provide useful context for determining if the API server is the culprit. The API server is managed by Azure, but there are still often actions you can take to mitigate issues in situations like this. For example, if you have the containerized Datadog Agent deployed on your cluster, you may want to explore using the Datadog Cluster Agent to help relieve stress on the API server.

Datadog's out-of-the-box AKS dashboard automatically processes and visualizes Kubernetes API Server control plane data.

Visibility into your cluster’s control plane components can also help you diagnose potential workload issues. The Kubernetes scheduler, for example, is responsible for assigning pods to worker nodes that can satisfy the pods’ resource requirements. You can troubleshoot spikes in the number of failed schedule attempts by checking for corresponding error logs with the scheduler and your worker nodes’ resource utilization. If these values are not in line with expectations, you may need to reduce your pod resource requests or adjust other policy constraints. You can also correlate this metric with Kubernetes audit logs for additional insights into the source of the issue.

Get better visibility into AKS today

Datadog’s AKS integration, which is bundled together with our Azure integration, ingests key health and performance metrics from your AKS clusters, automatically processes logs from your control plane components, and visualizes all of this data in the new AKS dashboard. To get started, simply install our Azure integration and configure log forwarding.

For even deeper visibility into your containerized application, deploy the Datadog Agent into your AKS cluster. The Agent enables collection of Kubernetes logs and events, distributed traces, service-level metrics, application logs, and more, all the way down to the container level.

Not yet a Datadog customer? Get started with a free 14-day trial.