NEW YORK–(BUSINESS WIRE)–Datadog, the widely-used SaaS-based monitoring platform for cloud applications, today announced a redesigned, deeper integration with Microsoft Azure. The new Azure Extension for Datadog brings data from Azure Diagnostics along with over 100 cloud and application data sources together. With this new extension, Azure customers can set up monitoring at cloud-scale within minutes and get a complete view of their applications’ availability and performance.
“Azure provides a robust and highly scalable platform for modern, web-scale applications,” said Will Xu, integrations product manager at Datadog. “With many DevOps teams choosing Azure as their cloud platform, we are thrilled to be collaborating with Microsoft to provide visibility into Azure, and helping our joint customers easily manage their applications in the cloud.”
Since launching in 2010, Datadog has been adopted by thousands of companies, including Netflix, EA, Spotify and AdRoll. Datadog allows operations and development teams to turn the massive amounts of data produced by their apps, tools and services into actionable insight. It integrates monitoring and web operations data from close to 100 commonly used technologies in modern applications and processes hundreds of billion records a day for its customers.
“Microsoft Azure enables developers to build and manage applications using the tools and frameworks of their choice,” said Vibhor Kapoor, director of product marketing, Microsoft Azure. “We look forward to providing our customers real-time insight into the health and performance of their Azure applications, built with the rich ecosystem of technologies that Datadog supports.”
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Datadog is a monitoring service that brings together data from servers, databases, applications, tools and services to present a unified view of the applications that run at scale in the cloud. These capabilities are provided on a SaaS-based data analytics platform that enables Dev and Ops teams to work collaboratively on the infrastructure to avoid downtime, resolve performance problems and ensure that development and deployment cycles finish on time.