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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 - 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Monitor API Performance with Runscope and Datadog
John Sheehan · 2015-07-30 · via Datadog | The Monitor blog
John Sheehan

John Sheehan

By John Sheehan, Co-founder and CEO of Runscope, which provides API performance monitoring and testing tools.

Like many companies today, we at Runscope rely on a microservices architecture with 60+ APIs and small services running through our infrastructure. As backend systems increasingly rely on APIs, monitoring those services to know not just when problems occur, but why, have become business imperatives that affect both your front-end applications and your internal operations.

api performance
api performance

Now, you can get more targeted insights on API health and how it relates to your infrastructure with a turn-key integration with Runscope, a suite of API performance monitoring and testing tools. With Runscope, you can easily create tests, no code required, and monitor your APIs for uptime, performance and correctness.

Correlate API performance with infrastructure data

With Runscope, you’re the first to know about any API-related issues before they impact your system. By integrating Runscope API monitoring with Datadog, it’s even easier to dig deep into API performance with the dashboards you’ve already built for your broader system. Runscope was built for teams, so whether you use APIs for front-end applications or devops, Datadog instantly records the data from your API tests. By measuring API performance against your IT infrastructure data, you can more quickly and precisely discover the cause of API issues that might be related to your infrastructure.

api performance
api performance

The screenshot above is an example of measuring API performance data from Runscope at the top and CPU load data from a backend server on the bottom. When API response time begins to spike after 00:20 (top), you can use your Datadog dashboard to easily correlate a spike in CPU usage that began several minutes before. After CPU load settles back to its normal near-idle state, the API response times will also begin to fall down.

Keen IO uses Runscope with Datadog to monitor the average duration of queries of various classes and move thresholds into its existing corpus of alerts. Cory Watson, Principal Infrastructure Engineer at Keen IO says, “The combination of Runscope API monitoring with Datadog infrastructure monitoring provides Keen IO with an easy way to integrate our mission-critical API data directly into the Datadog dashboards we already use, which gives us fine-grained control.”

Connecting Runscope tests to your Datadog account is easy. All you have to do is create an API key from your Datadog account and enter your key when you select the Datadog integration for your selected Runscope test in your Runscope instance. Check out the docs or read the blog post for a more detailed walk-through.

Start using the integration

If you haven’t started to monitor API performance, sign up for Runscope for free today to see how you can add API monitoring into your existing Datadog dashboards and alerts.