NEW YORK–(BUSINESS WIRE)–Datadog, the essential monitoring service for modern cloud applications, today announced its new integration with Cloud Foundry®, an open-source application platform that provides streamlined application development and deployment by leveraging cloud-based infrastructure. Cloud Foundry is widely used within large enterprise organizations as they move to microservices architectures, continuous delivery methods, and DevOps practices. Due to Cloud Foundry’s central role in application deployment and operations, monitoring Cloud Foundry’s various components is crucial for maintaining the health and performance of large applications.

“Cloud Foundry has become the leading application deployment platform for many of our enterprise customers that have large-scale, multi-team environments,” said Ilan Rabinovitch, Director of Product Management at Datadog. “Our latest integration enables Cloud Foundry cluster operators to automatically monitor the health of their environments.”

Datadog’s Cloud Foundry integration works by collecting metrics that determine cluster health by component and by resource consumption. Metrics can be collected from critical Cloud Foundry components including BOSH, Cloud Controller, Loggregator, Gorouter, and Diego. These metrics can then be visualized so DevOps teams can monitor their performance, identify patterns and anomalies, and create alerts.

“Pivotal Cloud Ops has happily used Datadog to monitor Pivotal Web Services, our Cloud Foundry as a service environment, for some time,” said Ian Andrews, Vice President of Product at Pivotal®. “This new integration gives Datadog and Cloud Foundry users an easy, out of the box experience.”

Additional Resources

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About Datadog

Datadog is the world’s leading monitoring service for cloud-scale applications, bringing together data from servers, databases, tools, and services to present a unified view of your entire stack. These capabilities are provided on a SaaS-based data analytics platform that enables Dev and Ops teams to work collaboratively to avoid downtime, resolve performance problems, and ensure that development and deployment cycles finish on time.