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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
Automate incident response and security workflows with Blink in the Datadog Marketplace
Nicholas Thomson · 2023-08-30 · via Datadog | The Monitor blog

Security and DevOps engineers often spend a lot of time and effort creating and managing complex, repetitive workflows, such as incident response, honeypotting, recovery and remediation, and more. Blink is a no-code security platform that enables users to create workflow automations, triggers, and self-service apps to streamline processes, better enforce guardrails, and eliminate operational bottlenecks. These capabilities help reduce the time and effort required for your security and DevOps teams to create a more dependable, secure system.

Datadog now offers an out-of-the-box Blink integration and software license via the Datadog Marketplace. Joint users can enhance their infrastructure monitoring and incident response workflows by utilizing Blink’s workflow automations powered by native Datadog actions—such as creating a monitor, creating events, and querying metrics.

In this post, we’ll show you how to:

  • Automate infrastructure monitoring as you scale

  • Enhance cyber incident response by automatically triggering Datadog actions

  • Enrich your Datadog alerts with Blink workflow automations

Automate infrastructure monitoring as you scale

Once you’ve enabled the integration, you can create workflow automations that will ensure your infrastructure is being thoroughly monitored as you spin up new cloud resources. For instance, say you’re a platform engineer at a startup that is scaling quickly and runs on Amazon EC2 instances. Because your infrastructure is growing fast, you want to make sure that all your new cloud resources are being monitored to avoid visibility gaps, which could lead to application performance issues and degraded end-user experience. You can leverage a Blink automation for Datadog that scans your EC2 instances to find ones that aren’t yet monitored.

Blink automations scan EC2 instances and alerts on ones that aren’t yet monitored

The automation lists all your active Datadog monitors and synthetic tests, then gets all your AWS EC2 instances. It then compares your monitors with your EC2 instances to find any discrepancies, which it will report to you via Slack automatically. Once you have a list of unmonitored cloud resources, you can create a monitor for the instance to alert you when changes in critical metrics—such as latency, resource usage, errors, and more—violate SLAs or require investigation.

Enhance cyber incident response by automatically triggering Datadog actions

In addition to helping you monitor your infrastructure as you scale up and down, the integration also allows you to automatically trigger Datadog actions from Blink workflows.

For example, say you’re a SecOps engineer on a healthcare application that must adhere to strict compliance regulations. You create a daily scheduled Blink automation that checks misconfigured resources in Datadog Cloud Security for potential SOC 2 compliance violations. If any issues are discovered that violate SOC 2 requirements, the workflow automation will create a new incident in Datadog. From there, you can pivot to Datadog Incident Management to track your team’s progress in investigating and remediating the issue from a single, consolidated platform. In performing your investigation, you can utilize other areas of the Datadog platform, such as Cloud Security Misconfigurations, where you can identify any misconfigured cloud resources or other issues that may be at the root of the SOC 2 compliance violation.

Set up Blink automations to check for misconfigured resources in Datadog Cloud Security

Or, say you’re a SecOps engineer at a social media site with a large attack surface. You create a Blink action that is triggered when Datadog detects a Security Signal with a high or critical priority status. This action will then query the Datadog Events Stream for events that occurred during the time frame when the Security Signal was triggered and are tagged with the associated service. To complete the incident response workflow, your Blink action can then automatically send a list of events matching these criteria to the appropriate member of your team via Slack, so they can investigate further and determine the severity of the Security Signal.

Finally, you can create Blink workflow automations that trigger on Datadog actions, such as alerts, events, and metric thresholds, so that you can automate an entire incident response process.

For example, say you are a DevOps engineer working on a banking app, and your team uses Datadog to monitor your infrastructure. You have set up a monitor in Datadog to alert you when a service running on Kubernetes fails after a recent deployment. Within Blink, you can set up an automated rollback and incident response workflow that initiates every time this Datadog alert triggers.

Set up Blink automation to rollback a deployment when a Datadog alert triggers

Datadog sends the alert to Blink, where the workflow automation will be triggered and automatically roll back the most recent deployment to the last stable version and run a performance test to confirm the issue is resolved.

Blink also integrates with communication tools like email, Slack, and Microsoft Teams to optimize incident response and allow teams to notify each other about what’s been done, add decision points or questions to bring clarity and context to your workflows, and collaborate on troubleshooting. To continue our example, you can get, list, and query specific metric metadata from the service failure incident that was created following the alert, and send an interactive notification over Slack—including the test result—to the service owner to ask whether the incident should be closed in Datadog. After a decision has been made, you or the service owner can close the incident directly from Slack.

Start automating your incident response and critical workflows

Datadog’s Blink integration enables you to trigger workflow automations in Blink from Datadog events, as well as trigger native Datadog actions from Blink workflows, helping you enforce compliance and security guardrails across your distributed infrastructure. Datadog’s Blink integration complements Datadog Incident Management, Cloud Security, SIEM, Infrastructure Monitoring, Container Monitoring, and more. If you’re new to Datadog, sign up for a 14-day free trial.

The ability to promote branded marketing tools is a membership benefit offered through the Datadog Partner Network. You can learn more about the Datadog Marketplace in this blog post. If you’re interested in developing an integration or application that you’d like to promote, you can contact us at marketplace@datadog.com.