On April 8, 2019, this app has been deprecated and reached its End of Life on July 7, 2019. For more information about the end of availability and support for this app, see https://www.splunk.com/blog/2019/03/18/end-of-availability-splunk-built-apps-and-add-ons.html?April.
The Splunk App for Microsoft Windows Active Directory ONLY works on Splunk 5.x systems. For similar functionality on Splunk 6 and later editions, please use the Splunk App for Windows Infrastructure: http://apps.splunk.com/app/1680/
The Splunk App for Microsoft Windows Active Directory gathers performance metrics, log files, and Powershell data from the domain controllers and DNS servers of a Microsoft Active Directory forest and its underlying infrastructure. It presents the data in a series of operational dashboards covering IT Operations, DNS Debugging, Security and Audit, and Change Management functionalities.
Complete visibility into your end-to-end Hadoop operations.
Monitoring and managing Hadoop cluster operations is a big data challenge of its own. Splunk can collect and correlate events and run-time metrics from every service on every host, every job from every user. With HadoopOps, you will gain total visibility into Hadoop's operation status, search across the entire cluster in real-time, troubleshoot and analyze Hadoop with rich, interactive views.
* Preconfigured application that accelerates your Splunk solution for Hadoop operations
* Visualize cluster resources with real-time heat map of key performance metrics
* Filter, sort, and analyze jobs by user, duration, slot usage, and type
* Search and correlate events and metrics from every service, host, job, and user.
* Alert and notify stakeholders on key events using automated proactive health checks
The Splunk App for HadoopOps monitors cluster resources beyond Hadoop itself, including the network, switch, rack, operating system and database.
Core features in the Splunk App for HadoopOps include:
- End-to-end monitoring and troubleshooting of the Hadoop cluster, database and networks in addition to multi-cluster management.
- Headline alerting for numerous threshold conditions, such as crashed disk and slow MapReduce jobs.
- A centralized real-time view of Hadoop nodes using an intuitive heatmap display.
- Measuring current and historical MapReduce jobs to analyze failures or performance issues.