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

V
V2EX
Recent Announcements
Recent Announcements
博客园 - 司徒正美
P
Proofpoint News Feed
博客园 - 聂微东
小众软件
小众软件
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
aimingoo的专栏
aimingoo的专栏
量子位
MyScale Blog
MyScale Blog
云风的 BLOG
云风的 BLOG
博客园 - Franky
B
Blog RSS Feed
F
Full Disclosure
The Cloudflare Blog
宝玉的分享
宝玉的分享
Last Week in AI
Last Week in AI
D
DataBreaches.Net
N
News and Events Feed by Topic
S
Secure Thoughts
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
V2EX - 技术
V2EX - 技术
L
LINUX DO - 最新话题
H
Heimdal Security Blog
Recent Commits to openclaw:main
Recent Commits to openclaw:main
Application and Cybersecurity Blog
Application and Cybersecurity Blog
Apple Machine Learning Research
Apple Machine Learning Research
L
LangChain Blog
Hugging Face - Blog
Hugging Face - Blog
C
Check Point Blog
U
Unit 42
G
Google Developers Blog
Forbes - Security
Forbes - Security
S
Schneier on Security
T
Threatpost
W
WeLiveSecurity
I
Intezer
D
Darknet – Hacking Tools, Hacker News & Cyber Security
Security Latest
Security Latest
T
Troy Hunt's Blog
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
I
InfoQ
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
有赞技术团队
有赞技术团队
S
Security Affairs
Cisco Talos Blog
Cisco Talos Blog
T
Tenable Blog
Simon Willison's Weblog
Simon Willison's Weblog
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
V
Vulnerabilities – Threatpost

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
Install updated Datadog integrations as they become available
Hippolyte Henry, John Matson · 2019-06-06 · via Datadog | The Monitor blog

We’re excited to announce a new feature that enables you to install updates to your Datadog Agent integrations as soon as they are released. That means that you can make use of new or updated integrations right away, without waiting for a full release of the Datadog Agent.

Agent integrations, at your command

Every time you download or update the Datadog Agent, the install process automatically pulls in the latest version of all the official Agent integrations that were bundled with that release. The new datadog-agent integration command for Linux and Windows allows users to quickly and securely install individual integrations between Agent releases, so you can put new or updated integrations to work as soon as they become available. (You can read about the security work that made this feature possible on our engineering blog.)

How to use the new command

The datadog-agent integration command has four subcommands:

  • install: install a specific version of an integration

  • remove: remove an integration

  • show: get the version number and other information about an integration

  • freeze: list the Python packages for all installed integrations

To upgrade an integration to a newer version on a Linux host, you can run the following command:

sudo -u dd-agent -- datadog-agent integration install datadog-<integration_name>==<version>

For example, you can use the command to update Datadog’s vSphere integration to version 4.0.0:

sudo -u dd-agent -- datadog-agent integration install datadog-vsphere==4.0.0

For more usage information on Linux and Windows hosts, consult the Agent docs.

More power over your integrations

We’re excited to put this command in your hands so you can start making use of integration enhancements and updates as soon as they are released. To start using the new datadog-agent integration command, ensure that you’re running an updated version of the Datadog Agent. All four subcommands are available as of version 6.9.0 of the Agent. For more info, read the docs for our Agent integration management features here.

If you aren’t yet using Datadog to monitor your infrastructure and applications, you can sign up for a 14-day trial here.