Datadog Announces Java Support for Application Performance Monitoring and Distributed Tracing | Datadog

Datadog Announces Java Support for Application Performance Monitoring and Distributed Tracing

  • Last year, Datadog announced the general availability of Datadog APM & Distributed Tracing, helping software developers troubleshoot code and optimize application performance
  • Datadog APM will now support Java alongside Python, Ruby, and Go – extending functionality and availability to more enterprise users

NEW YORK–(BUSINESS WIRE)–Datadog, the essential monitoring service for modern cloud environments, today announced Java support for Datadog Application Performance Monitoring and Distributed Tracing. With this support, all Datadog customers can easily monitor the health of the code within their Java applications and take advantage of various out-of-the-box integrations with Java frameworks (Spring Boot and Dropwizard), application servers (Tomcat and Jetty), and calls to databases (JDBC, MongoDB, and Cassandra). Datadog APM also supports OpenTracing, the vendor-neutral open standard for distributed tracing. This will bring application performance monitoring to more enterprise customers that often write their applications in the Java programming language.

“This is a crucial step in bringing full-stack visibility to our largest Java customers,” said Julie Levine, Product Manager at Datadog. “By giving them the ability to monitor their applications alongside the underlying cloud infrastructure within AWS, Azure, and Google Cloud, we are providing a true platform of observability that saves our customers money and time.”

“We need a unified view of both our applications and the cloud infrastructure underneath those applications in order to effectively troubleshoot” said Matt Jones, Head of Platform Engineering at Fitch Solutions. “Because many of our apps are built in Java, the new support from Datadog APM and Distributed Tracing is crucial in granting us deep visibility into our performance.”

Datadog APM supports performance optimization and outage diagnosis to reduce the impact of costly downtime for large-scale environments. Highlights include:

Highlights

  • Quick installation via a hosted SaaS solution that takes minutes to configure
  • Automatic tracing of individual requests from end to end across hosts and services
  • Rich visualizations for quickly and accurately identifying frequently used code paths
  • Easily customizable dashboards for data aggregation and correlation
  • Built-in collaboration between Dev and Ops teams
  • Smart alerting via email, SMS, and cloud-based collaboration tools
  • Anomaly detection based on machine learning
  • Transparent tag-based aggregation of performance data from microservices, containers, and other ephemeral hosts
  • Collection of JVM-level metrics as part of Datadog’s existing JMX integration Datadog also recently announced the public beta of its Log Management product following the acquisition of Logmatic.io, a Paris-based log management company. By combining infrastructure metrics, application traces, and log analysis within the same platform, users of the Datadog platform are able to greatly increase productivity, troubleshoot performance issues within applications, and avoid costly downtime.

Additional Resources

Start your 14-day free trial: http://dtdg.co/Start-Free-Trial

Read the blog post: http://dtdg.co/java-apm

About Datadog

Datadog is a monitoring service for hybrid cloud applications, assisting organizations in improving agility, increasing efficiency, and providing end-to-end visibility across the application and organization. These capabilities are provided on a SaaS-based data analytics platform that enables Dev, Ops and other teams to accelerate go-to-market efforts, ensure application uptime, and successfully complete digital transformation initiatives. Since launching in 2010, Datadog has been adopted more than 6000 enterprises including companies like Asana, eBay, PagerDuty, Stripe, Samsung, The Washington Post, and Zendesk.

Contact

Adam LaGreca

adam.lagreca@datadoghq.com