Users can now monitor the four most widely-used technologies in the Hadoop ecosystem: HDFS, MapReduce, YARN, and Spark
NEW YORK – May 24, 2016 – 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 can be turned on immediately, adding to the long list of technologies DevOps teams can monitor easily and collaboratively with Datadog.
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 Hadoop 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.
This product update supports:
HDFS: Using the HDFS integration, users can 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: The MapReduce integration 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: The YARN integration gives visibility to nodes, applications, cluster cores and cluster memory.
- Spark: With the Spark integration, users can see driver and executor, RDDs, tasks, job stages and more.
Since launching in 2010, Datadog has been adopted by thousands of enterprises, including Twilio, Airbnb, Netflix, EA, Spotify, Warner Bros. Games and AdRoll. For additional information on Datadog, please visit www.datadoghq.com.
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.
Heather Fitzsimmons, 650-279-4360