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

Hacker News: Ask HN
Hacker News: Ask HN
C
Cisco Blogs
The Hacker News
The Hacker News
T
Tor Project blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
The GitHub Blog
The GitHub Blog
A
Arctic Wolf
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
The Register - Security
The Register - Security
云风的 BLOG
云风的 BLOG
Simon Willison's Weblog
Simon Willison's Weblog
P
Palo Alto Networks Blog
Vercel News
Vercel News
C
CERT Recently Published Vulnerability Notes
I
InfoQ
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
M
MIT News - Artificial intelligence
I
Intezer
aimingoo的专栏
aimingoo的专栏
U
Unit 42
C
Cyber Attacks, Cyber Crime and Cyber Security
L
LINUX DO - 热门话题
Microsoft Security Blog
Microsoft Security Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
Cyberwarzone
Cyberwarzone
P
Proofpoint News Feed
P
Proofpoint News Feed
B
Blog
T
Threat Research - Cisco Blogs
博客园 - 叶小钗
Recorded Future
Recorded Future
Last Week in AI
Last Week in AI
N
News and Events Feed by Topic
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
Know Your Adversary
Know Your Adversary
Engineering at Meta
Engineering at Meta
G
Google Developers Blog
PCI Perspectives
PCI Perspectives
Google DeepMind News
Google DeepMind News
WordPress大学
WordPress大学
Application and Cybersecurity Blog
Application and Cybersecurity Blog
MyScale Blog
MyScale Blog
Security Archives - TechRepublic
Security Archives - TechRepublic
Schneier on Security
Schneier on Security
N
News | PayPal Newsroom
C
Cybersecurity and Infrastructure Security Agency CISA
H
Help Net Security
博客园 - 聂微东
H
Hackread – Cybersecurity News, Data Breaches, AI and More
G
GRAHAM CLULEY

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 the Datadog Architecture Center
David M. Lentz · 2024-11-04 · via Datadog | The Monitor blog

To prevent visibility gaps in your cloud environment, you need to efficiently deploy observability solutions that integrate easily with key technologies in your stack and scale reliably with new applications and migrated workloads. But observability deployments can be complex, often requiring deep and specific knowledge that may not be available within your teams. Now, the Datadog Architecture Center accelerates your observability implementation so you can quickly achieve secure, scalable, and enterprise-ready insights into your environment without starting from scratch.

Introducing the Datadog Architecture Center

The Architecture Center is a collection of detailed guides and reference diagrams that draw on best practices and deep knowledge from Datadog experts. These customizable blueprints help your teams efficiently roll out and manage observability solutions that provide comprehensive visibility as your cloud environment evolves. Each entry in the collection explains and illustrates how to implement Datadog to maximize your visibility with valuable details and context such as:

  • Descriptions of the benefits and challenges embodied in the implementation

  • Reference architecture diagrams that illustrate the structure and interaction of its components

  • Use cases detailing the observability and business value gained from the implementation

A reference architecture diagram shows the components and data flow involved in monitoring an SD-WAN implementation.

The collection covers log management, infrastructure and network monitoring, observable cloud environments, and more. Architectures include step-by-step explanations of how monitoring data is collected, suggestions for optimizing your observability strategy and governance, and links to relevant resources that can help you understand and manage your observability solutions.

Each entry in the Architecture Center templates a repeatable process for deploying Datadog to gain visibility into a technology or component in your stack. Taken together, the entries in the collection offer a roadmap for meeting both immediate and long-term observability needs and enable you to avoid common pitfalls that can plague complex deployments.

Efficiently deploy enterprise-ready observability with the Datadog Architecture Center

The Architecture Center provides a frictionless path to deploying observability implementations that are consistent, manageable, and reproducible. Visit the Architecture Center today to tap into Datadog expertise and gain immediate insights without the need to build from the ground up. New architectures and technical guides are added and updated regularly, so you can continue to draw on our deep expertise as your cloud environment expands and your observability needs evolve.

If you’re not already using Datadog, you can start today with a free 14-day trial.