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

Stack Overflow Blog
Stack Overflow Blog
博客园 - Franky
MyScale Blog
MyScale Blog
Jina AI
Jina AI
B
Blog
Microsoft Security Blog
Microsoft Security Blog
T
Troy Hunt's Blog
博客园_首页
T
Threatpost
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
L
Lohrmann on Cybersecurity
GbyAI
GbyAI
T
Tenable Blog
B
Blog RSS Feed
S
Securelist
T
Threat Research - Cisco Blogs
P
Privacy International News Feed
P
Proofpoint News Feed
T
The Exploit Database - CXSecurity.com
H
Hackread – Cybersecurity News, Data Breaches, AI and More
量子位
博客园 - 三生石上(FineUI控件)
大猫的无限游戏
大猫的无限游戏
雷峰网
雷峰网
C
CXSECURITY Database RSS Feed - CXSecurity.com
罗磊的独立博客
AWS News Blog
AWS News Blog
V
V2EX
宝玉的分享
宝玉的分享
J
Java Code Geeks
小众软件
小众软件
Spread Privacy
Spread Privacy
腾讯CDC
Google Online Security Blog
Google Online Security Blog
月光博客
月光博客
V
Visual Studio Blog
The Hacker News
The Hacker News
C
CERT Recently Published Vulnerability Notes
Project Zero
Project Zero
Know Your Adversary
Know Your Adversary
T
The Blog of Author Tim Ferriss
Last Week in AI
Last Week in AI
Apple Machine Learning Research
Apple Machine Learning Research
NISL@THU
NISL@THU
C
Check Point Blog
Webroot Blog
Webroot Blog
D
DataBreaches.Net
Cloudbric
Cloudbric
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
IT之家
IT之家

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
Secure your web apps running on Azure App Service with Datadog App and API Protection
Sourabh Katti, Addie Beach · 2023-12-15 · via Datadog | The Monitor blog
Sourabh Katti

Sourabh Katti

Addie Beach

Addie Beach

Technical Content Writer

Azure App Service is a platform-as-a-service (PaaS) commonly used to deploy applications and APIs, as well as functions, mobile apps, and more. It provides flexibility and reliability when deploying new applications and infrastructure, but it also introduces new security risks to your system. In particular, reduced visibility into the infrastructure and deployment of your application leads to a greater chance of application vulnerabilities being exploited by an attacker.

Datadog App and API Protection (AAP) now supports Azure App Service, enabling you to manage application security risk across even more of your system with continuous, real-time monitoring of vulnerabilities in and threats against your web applications and APIs. Additionally, AAP integrates with distributed traces and code-level context, empowering your development, operations, and security teams to build and run secure applications in production.

In this post, we’ll explore how monitoring Azure App Service with AAP enables you to:

  • Detect attackers targeting your Azure App Service-deployed applications

  • Prioritize fixing the most impactful vulnerabilities

  • Correlate security and performance data

Detect attackers targeting your Azure App Service-deployed applications

While cloud-based deployments enable you to scale dynamically, they can present unique security challenges for your system. Risks like insecure code and misconfigured API endpoints can expose your application to malicious actors. And while Azure provides a variety of built-in security capabilities, there often isn’t enough visibility at the application layer to detect every attack attempt.

Datadog AAP provides comprehensive attack coverage for over 140 types of attacks out of the box—including the OWASP Top 10 rules, which cover threats such as SQL injection, cross-site scripting, and Log4Shell. Additionally, AAP enables you to create custom rules for business logic exploits and tailor detection rules to specific applications. For example, let’s say you want to monitor your web apps for unauthenticated user access on sensitive endpoints, a common risk when using cloud-based hosting services like Azure App Service. You can instrument the user monitoring SDK for AAP, then build a business logic rule that alerts for unusual activity on these endpoints.

The Detection Rule creation window, including user monitoring SDK options.

AAP also provides actionable next steps for remediating these threats and securing your system. By viewing security signals in AAP, you can see which services have been targeted as well as any malicious input from the attacker. This enables you to quickly determine whether this signal corresponds to a legitimate attack and block the attacker’s IP address using Datadog’s native blocking capabilities. You can then investigate further alongside your organization’s SRE and development teams to find a permanent remediation for the attack.

A security signal in AAP showing the ability to block attackers.

Prioritize fixing the most impactful vulnerabilities

Modern apps are a mix of custom code and third-party libraries, the latter of which introduce additional risk to your applications by increasing the number of dependencies. When combined with deployment platforms like Azure App Service, it’s difficult to detect these vulnerabilities and determine which ones actually pose risks to your system. For example, vulnerabilities in an API running in a staging environment are less likely to be exploited compared to vulnerabilities in an API that’s exposed to public traffic.

Datadog AAP detects vulnerabilities in applications hosted on Azure App Service across both your third-party libraries and custom code. By using runtime detection, AAP is able to report on an application’s attack surface and prioritize the most critical vulnerabilities. For each vulnerability, you can view attributes such as the package name, impacted services, and remediation details. Additionally, vulnerability severities are adjusted based on the runtime behavior of the application, enabling you to focus on fixing the most pressing risks. For example, the vulnerability severity will increase if the application is running in production or if attack attempts have been detected.

The factors influencing a vulnerability’s priority score in Datadog, including environment, exploit probability, and active attacks.

Correlate security and performance data

Security insights for applications hosted on Azure App Service fully integrate with the health and performance metrics provided by other Datadog products. For example, suspicious requests are highlighted in APM and stack trace errors are included in AAP, enabling teams to investigate issues more quickly. Additionally, the Service Catalog provides complete visibility into security, performance, and reliability metrics for all of your services.

A list of vulnerabilities in a service within Service Catalog.

Start securing your apps hosted on Azure App Service today

With AAP, you can view security signals and vulnerabilities from all your Azure App Service web deployments directly within Datadog. AAP enables you to quickly detect risks to your cloud-hosted services, view suggested remediation actions for quick troubleshooting, and pivot to APM for more information about the affected services.

You can use our documentation to enable AAP on your applications deployed on Azure App Service. Or, if you’re not yet a Datadog customer, you can sign up for a 14-day free trial.