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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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Track your PHP-FPM performance with Datadog
2015-07-09 · via Datadog | The Monitor blog

We’re pleased to announce that Datadog can now help you track your PHP-FPM performance with our new integration.

PHP-FPM (FastCGI Process Manager) serves as a proxy for your PHP backend, balancing the requests sent to PHP. It’s a popular tool used with web servers like Apache and NGINX. FPM is included as part of the standard PHP package.

Datadog’s PHP-FPM integration comes with a built-in screenboard that displays some of the metrics our Agent collects from FPM (e.g., listen queue, active processes, pool size adjustments, slow log, etc.).

The integration automatically collects FPM metrics in Datadog to let you visualize and correlate them with the rest of your applications. You can make comments on specific FPM activity and discuss specific metrics and events with your team members. You can also set up custom service checks and monitors to notify you in case there are problems with your FPM instances.

PHP-FPM performance

Track multiple FPM instances

Most of our customers have many instances of FPM running for redundancy/failover purposes. Datadog lets you easily track these associated FPM clusters, as well. Datadog recognizes and records all of the tags associated with a server instance, allowing you to easily get the big picture of what’s going on across multiple FPM instances by aggregating data on different dimensions.

PHP-FPM performance

When using a dynamic pool of processes, these metrics will allow you to pinpoint when FPM is underpowered and help you adjust your pool configuration or capacity.

PHP-FPM performance

Service checks

The PHP-FPM service check is easy to setup and use in Datadog. You just turn it on, point it to the set of instances that have FPM, and it starts reporting on their status. As with all Datadog service checks, you can customize what matters to you. For example, you could set it to only throw an alert if a certain percentage of instances in a pool is not responding.

PHP-FPM performance

Free trial

Do you use PHP-FPM? Sign up for a free 14-day trial of Datadog to see how you can increase your understanding of your PHP-FPM performance. Setting up the FPM integration after signing up takes a minute and will begin to collect metrics immediately.