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

cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
Hacker News - Newest:
Hacker News - Newest: "LLM"
S
Security Affairs
PCI Perspectives
PCI Perspectives
Google Online Security Blog
Google Online Security Blog
W
WeLiveSecurity
www.infosecurity-magazine.com
www.infosecurity-magazine.com
Recent Commits to openclaw:main
Recent Commits to openclaw:main
P
Privacy & Cybersecurity Law Blog
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
S
Security @ Cisco Blogs
Security Archives - TechRepublic
Security Archives - TechRepublic
Cyberwarzone
Cyberwarzone
L
Lohrmann on Cybersecurity
TaoSecurity Blog
TaoSecurity Blog
V
Visual Studio Blog
博客园 - 聂微东
Scott Helme
Scott Helme
博客园 - 【当耐特】
K
Kaspersky official blog
Security Latest
Security Latest
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
MyScale Blog
MyScale Blog
Schneier on Security
Schneier on Security
WordPress大学
WordPress大学
博客园 - 叶小钗
C
Check Point Blog
V2EX - 技术
V2EX - 技术
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
博客园 - Franky
T
Tor Project blog
Apple Machine Learning Research
Apple Machine Learning Research
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
腾讯CDC
雷峰网
雷峰网
博客园_首页
美团技术团队
Y
Y Combinator Blog
C
CERT Recently Published Vulnerability Notes
AWS News Blog
AWS News Blog
月光博客
月光博客
N
Netflix TechBlog - Medium
Last Week in AI
Last Week in AI
Recent Announcements
Recent Announcements
Google DeepMind News
Google DeepMind News
Help Net Security
Help Net Security
P
Proofpoint News Feed
MongoDB | Blog
MongoDB | Blog
C
Cybersecurity and Infrastructure Security Agency CISA

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
Datadog Security extends compliance and threat protection capabilities for Google Cloud
Sourabh Katti, Sarah Elkaim, Mallory Mooney · 2024-03-28 · via Datadog | The Monitor blog

Organizations are adopting Google Cloud at a growing rate. This growth is partially influenced by both the rise of AI computing and a push towards multi-cloud usage. A recent report found that 85 percent of organizations deploy their applications on multi-cloud architecture. With the shift to AI computing and multi-cloud adoption, organizations are reconsidering their cloud security coverage now more than ever. Google Cloud already offers built-in security monitoring for its environments, and Datadog has expanded its security platform to complement Google Cloud’s capabilities. In this post, we’ll look at how Datadog Security and Google Cloud work together to help you:

Establish unified visibility into suspicious events and potential attackers

Google Security Command Center, Google Cloud’s security monitoring service, enables you to review vulnerabilities and reported threats in your environments. But in order to understand the why and how behind an attack, you need to bring your security and operations teams’ existing monitoring under the same centralized platform. With this shared context, your teams can work together to accurately pinpoint attack attempts or vulnerable areas in your environments, which allows them to respond to incidents more efficiently.

Datadog provides turn-key integrations for both Google Cloud Security Command Center and Google Cloud Armor, enabling you to forward event logs directly to Datadog Cloud SIEM. With these integrations, both security and operations teams can use the same event data to uncover suspicious activity or attackers in their infrastructure.

Google Security Command Center dashboard
Google Security Command Center dashboard

The detail in these logs enables your teams to correlate events and their metadata—such as type, severity, and source—with the existing infrastructure performance data in Datadog. Having this context is crucial for pinpointing which parts of your environment are vulnerable and need to be patched—from application services down to the underlying resources.

Ensure continuous compliance with industry-standard frameworks

A key first step to improving security coverage is expanding visibility into your Google Cloud environment. But once you have a view into your services and resources, you also may need to continuously maintain compliance with certain standards, such as PCI DSS, HIPAA, CIS, and GDPR. Missing any one of these requirements could easily lead to unintentional data exposure or even costly data breaches.

Datadog Cloud Security complements Google Security Command Center by providing compliance and misconfiguration support for CIS GCP Foundations Benchmark v1.3, in addition to other industry-standard frameworks. This ensures that you are able to monitor and continuously maintain and improve your compliance posture while you expand your Google Cloud or multi-cloud environment.

Google Security Command Center CIS GCP Foundations Benchmark

Protect your application and infrastructure attack surface from threats

A typical cloud environment is made up of a complex network of APIs, microservices, and web applications, all of which are vulnerable to threats. This is especially true if they access sensitive data, such as a customer’s personal information, credit card information, and more. With this level of risk, you need to ensure that your teams have end-to-end, continuous visibility into their environment’s security posture before and after deploying new features in production. This is in addition to getting insights into applications that are written in popular languages, such Java, Node, Go, and deployed on various compute services, like Google App Engine and Google Cloud Run.

Datadog App and API Protection (AAP) takes advantage of an organization’s instrumented applications in order to identify threats and provide protection capabilities. Datadog AAP also includes support for serverless environments like Google Cloud Run, which many organizations are also adopting at a rapid pace to support their cloud migrations. Once enabled, Datadog AAP will detect common threats, such as OWASP’s Top 10, across APIs, microservices, and applications.

Datadog’s Google Cloud Run integration

Unify your security monitoring with Datadog

As you migrate to cloud environments, your applications become increasingly more exposed to threats, so it’s critical to identify and mitigate any security and compliance gaps along the way. Datadog Security not only provides a centralized platform for visibility into these gaps, but also helps you keep your cloud environments safe from a rapidly growing threat landscape. Check out our documentation to learn more about integrating with Google Security Command Center, enabling Datadog AAP for Google Cloud Run, and Datadog Cloud Security’s supported frameworks. If you don’t already have a Datadog account, you can sign up for a free 14-day trial.