Follow Datanami:
May 24, 2016

Datadog Adds Hadoop and Spark Integrations to Cloud-Scale Monitoring Platform

May 24 — Datadog, the leading SaaS-based monitoring platform for cloud applications, today announced support for Hadoop, bringing its unified view of applications to the Hadoop ecosystem. Hadoop users can now benefit from Datadog’s rich dashboards, full stack visibility and correlation, sophisticated and targeted alerts, collaborative tools and integrations, and easy setup with no maintenance. Integrations with HDFS, MapReduce, YARN, and Spark can be turned on immediately, adding to the long list of technologies DevOps teams can monitor easily and collaboratively with Datadog.

“Hadoop is an incredibly successful tool, making complex distributed data processing possible,” said Amit Agarwal, chief product officer at Datadog. “That said, as with most distributed systems running on many machines, when things go wrong it can be quite difficult to pinpoint exactly what happened or why. This is especially true in a team setting where everyone is running simultaneous, siloed investigations. This is why we integrated Hadoop with the Datadog platform. Engineering and operations teams now have the ability to turn data produced by Hadoop into actionable insight.”

The Power of Monitoring Hadoop

By adding the power of Datadog to Hadoop, users can now see hundreds of Hadoop metrics alongside their hosts’ system-level metrics, correlating what is happening within a Hadoop cluster with what is happening throughout their stack. Users can also avoid problems by setting alerts when critical jobs don’t finish on time, on outliers or any other problematic scenarios.

Monitoring Hadoop technologies offers users a variety of benefits:

  • HDFS – enables users to monitor the number of data nodes and blocks, disk space remaining on each host and cluster, as well as namenode load and lock queue length.
  • MapReduce – includes metrics for map and reduce jobs pending, succeeded and failed, bytes read by job or in total, as well as input/output records.
  • YARN – gives visibility to nodes, applications, cluster cores and cluster memory.
  • Spark – ensures users can see driver and executor, RDDs, tasks, job stages and more.

About Datadog

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 to avoid downtime, resolve performance problems, and ensure that development and deployment cycles finish on time. For additional information on Datadog, visit www.datadoghq.com.


Source: Datadog

Datanami