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

Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
V
Vulnerabilities – Threatpost
L
LINUX DO - 热门话题
H
Hacker News: Front Page
Hacker News - Newest:
Hacker News - Newest: "LLM"
L
Lohrmann on Cybersecurity
Cisco Talos Blog
Cisco Talos Blog
O
OpenAI News
S
Securelist
Security Latest
Security Latest
T
Threat Research - Cisco Blogs
H
Heimdal Security Blog
C
CXSECURITY Database RSS Feed - CXSecurity.com
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
Recorded Future
Recorded Future
Microsoft Azure Blog
Microsoft Azure Blog
MyScale Blog
MyScale Blog
Webroot Blog
Webroot Blog
The Hacker News
The Hacker News
Google Online Security Blog
Google Online Security Blog
Latest news
Latest news
N
Netflix TechBlog - Medium
N
News and Events Feed by Topic
D
Docker
D
DataBreaches.Net
A
About on SuperTechFans
T
Tor Project blog
V
V2EX
G
Google Developers Blog
博客园 - Franky
N
News | PayPal Newsroom
T
The Blog of Author Tim Ferriss
I
InfoQ
H
Help Net Security
V2EX - 技术
V2EX - 技术
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
S
Security Affairs
SecWiki News
SecWiki News
The Register - Security
The Register - Security
人人都是产品经理
人人都是产品经理
NISL@THU
NISL@THU
小众软件
小众软件
B
Blog
T
Threatpost
P
Palo Alto Networks Blog
博客园 - 【当耐特】
L
LangChain Blog
AWS News Blog
AWS News Blog
月光博客
月光博客
宝玉的分享
宝玉的分享

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 your Azure Logic Apps with Datadog
John Matson · 2016-09-27 · via Datadog | The Monitor blog
John Matson

John Matson

Azure Logic Apps lets you connect different Azure services and other software-as-a-service (SaaS) products, so you can automate your responses to events. For instance, you can send an email whenever you add a new customer to Salesforce, or post to Slack when a new GitHub issue is opened in one of your repositories.

If you’re building critical workflows in Azure Logic Apps, you want to ensure that your tasks are executing as expected. So we’re pleased to announce that you can now monitor all your Logic Apps with Datadog.

Datadog dashboard for Logis Apps

Workflow management in the Azure cloud

Logic Apps falls somewhere on the spectrum between simple integration services like IFTTT and open-ended code execution platforms such as Amazon’s Lambda or Azure Functions. Like IFTTT, Logic Apps has a visual interface that lets you build workflows from a library of pre-built connectors. But Logic Apps offers more developer-focused features, such as configurable retry logic and error handling, as well as the ability to add custom processing steps, such as XML validation or transformation.

Monitor your automation

Our new integration lets you access more than 20 metrics from Azure Logic Apps. The metrics cover overall workflows (latency, runs completed, runs failed), plus metrics at a more granular level, including event triggers and the resulting actions.

As soon as you enable the Azure integration, you will see your metrics populating a customizable dashboard for Azure Logic Apps in Datadog. You can easily send alerts via email, Slack, HipChat, or on-call management tools like PagerDuty if workflow errors start to pile up, or if your actions take too long to execute.

Because Azure metrics are automatically tagged with relevant attributes in Datadog, you can slice and dice your metrics along any axis you want. For example, you can monitor the aggregate number of completed actions across all your workflows, or set up an alert for failed runs and apply it to only those workflows running in your production Azure account.

The expanding Azure sea

Logic Apps joins a rapidly growing list of Azure services supported in Datadog, including Azure VMs, Azure App Service, Azure SQL Databases, and, as of today, Azure Redis Cache, which we’ll cover in a forthcoming post. In total, Datadog integrates with more than 1,000 popular technologies, so you can monitor your entire application infrastructure in one place.

The metrics from Azure Logic Apps are available thanks to our integration with Azure’s new Metrics API, which was announced today at Microsoft Ignite. We will continue to add new Azure integrations to Datadog as additional Azure services are connected to the new Metrics API.

See the logic!

If you’re already using Datadog to monitor your infrastructure and applications, you can set up our integration to start graphing, alerting, and correlating Azure Logic Apps metrics today. If you’d like to see how Datadog can help bring observability to your Azure cloud apps and infrastructure, you can sign up for a free trial here.