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

The Register - Security
The Register - Security
云风的 BLOG
云风的 BLOG
U
Unit 42
F
Fortinet All Blogs
The GitHub Blog
The GitHub Blog
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
D
Docker
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
S
Secure Thoughts
Hacker News: Ask HN
Hacker News: Ask HN
Vercel News
Vercel News
S
Security @ Cisco Blogs
GbyAI
GbyAI
Stack Overflow Blog
Stack Overflow Blog
Exploit-DB.com RSS Feed
Exploit-DB.com RSS Feed
I
Intezer
MongoDB | Blog
MongoDB | Blog
AI
AI
MyScale Blog
MyScale Blog
Engineering at Meta
Engineering at Meta
Y
Y Combinator Blog
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
P
Proofpoint News Feed
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
W
WeLiveSecurity
博客园 - 叶小钗
S
SegmentFault 最新的问题
N
News | PayPal Newsroom
WordPress大学
WordPress大学
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
D
DataBreaches.Net
小众软件
小众软件
Microsoft Azure Blog
Microsoft Azure Blog
Spread Privacy
Spread Privacy
H
Help Net Security
美团技术团队
博客园 - 司徒正美
T
Threat Research - Cisco Blogs
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
K
Kaspersky official blog
Application and Cybersecurity Blog
Application and Cybersecurity Blog
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
V
Vulnerabilities – Threatpost
TaoSecurity Blog
TaoSecurity Blog
N
Netflix TechBlog - Medium
L
Lohrmann on Cybersecurity
J
Java Code Geeks
量子位
Martin Fowler
Martin Fowler
博客园_首页

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
Quickly remediate issues in your Azure applications with Datadog Workflow Automation
Syed Sarjeel Yusuf, Emma Chadwick · 2024-01-03 · via Datadog | The Monitor blog

Datadog Workflow Automation speeds up incident response and remediation for DevOps, SRE, and security teams by enabling them to automatically run predefined task sequences whenever specific alerts or security signals are triggered. After the feature’s initial release in 2023, Datadog is now excited to announce a significant expansion of its Workflow Automation capabilities with Azure actions, allowing engineers to create automated workflows for their Azure resources for the first time.

With nearly 80 Azure actions already available today and more on the way, you can now use automation to address disruptions, improve response times, and help boost the overall health and security of your Azure-based systems. These new actions use integrations to cover an array of Azure services, providing the means to orchestrate complex workflows across different technologies. These many different Azure integrations also act as categories for actions and automation capabilities in the Workflow Automation UI, and they include:

  • Azure DevOps Pipelines: Automate pipelines to immediately restart services in response to Datadog service outage alerts.

  • Azure VM Scale Sets: Dynamically adjust the number of VM instances based on traffic load, as indicated by Datadog monitors.

  • Azure Blob: Manage access control by automatically updating blob properties when Datadog Cloud Security detects misconfigurations.

This post will explore some of the processes in Azure that you can now automate with Datadog Workflow Automation. We will describe how to:

Automatically restart critical services where needed

With Workflow Automation, you can automate remediation in response to alerts from Datadog monitors.

Imagine your team is running an application on Azure, with Apache Tomcat deployed as the application server. This service is critical to your operations, handling user accounts and financial transactions. To maintain visibility into its performance, you use Datadog to configure metric monitors and anomaly monitors for the Tomcat service.

One day, a monitor alerts you to an issue with the server, indicating a noticeable increase in response times, a higher error rate, and spikes in CPU and memory usage. After researching the issue, you discover that your application is suffering from a memory leak, which is resulting in performance degradation and intermittent unresponsiveness. The ultimate solution is to fix the memory leak, but this undertaking requires some time and cannot be implemented immediately. A temporary solution is needed in the meantime.

In this situation, the next step is clear: you need to restart the Tomcat server to clear the memory and temporarily restore normal operation. And since this problem will likely recur until the memory leak is fixed, it’s important to mitigate impact by having the service restart automatically whenever it exhibits this type of performance issue.

Using an Azure DevOps Pipelines action in a workflow

To speed up the mitigation response, reduce sluggish performance, and minimize downtime for similar issues with your Tomcat servers, you can use Azure actions in Workflow Automation. As mentioned, Azure actions are grouped into distinct categories that correspond to different integrations. To restart Tomcat service automatically, we will draw upon the Azure DevOps Pipelines category of actions in Workflow Automation. Specifically, we will use the Run pipeline action in a workflow that restarts the Tomcat service.

The Azure DevOps Pipelines category of actions.

By adding the workflow as an @-mention to your monitor configuration, the workflow will automatically be triggered when the monitor goes into an alert state.

The workflow is shown below. It will first get all the necessary details about the Tomcat service from the Software Catalog and pass this information to the Run pipeline action.

A workflow to restart the Tomcat servers.

The workflow will then perform the step to run the pipeline, followed by the step to determine whether the monitor has resolved itself. In either case, a corresponding message is then sent to an appropriate Slack channel, informing the right response team.

By combining Datadog’s alerting capabilities with an Azure action in Workflow Automation, your response to disruptions is greatly accelerated. Additionally, the automated execution of tasks in the workflow helps ensure the reliability and availability of your application, reduce the need for manual intervention, and minimize downtime, all while maintaining clear communications surrounding the incident resolution.

Secure your Azure-based applications with the click of a button

Apart from triggering workflows from monitors, you can also trigger workflows either manually or automatically in response to security signals.

Imagine, for example, that you are part of the security team managing Microsoft Entra ID (formerly Azure Active Directory) for your organization and are responsible for user account and access security. One day, you receive a security signal from Datadog Cloud SIEM indicating a potential compromise of a user’s credentials.

This signal is triggered due to suspicious activity related to the user’s account. To respond effectively to this security incident, you have created a workflow that orchestrates a series of actions to contain a compromised user. All you have to do now is run the pre-created workflow, which you can do directly from the details page of the security signal.

The Run Workflow button in a security signal.

By clicking on the Run Workflow button, you will be able to select the correct workflow from the Workflow Library and execute the workflow to immediately contain the user.

Selecting and running a workflow manually.

In addition, you can also trigger your workflow automatically. To do so, you can add the workflow to the Notification Details section of a notification rule or—as shown below—directly to the notify field in the Set rule cases section of a Cloud SIEM detection rule.

Configuring a Cloud SIEM detection rule to trigger a workflow automatically

Get started with Workflow Automation and Azure actions

The workflows described above show just some of the tasks that can be automated for Microsoft Azure. However, with over 75 Azure-related and 550 total actions that can be combined in various ways, the range of different workflows that you can automate is vast.

Discover the full spectrum of available actions in the action catalog for Workflow Automation, or check out the many workflow blueprints available to kick-start your automation journey. The workflows mentioned in this blog are also available as blueprints, ready for you to pick up and configure. To learn more about how Datadog Workflow Automation can help you reduce MTTR and proactively troubleshoot issues, check out our documentation. And if you aren’t already a Datadog customer, get started with a 14-day free trial.