Splunk Inc. (NASDAQ:SPLK), provider of the leading software platform for real-time operational intelligence, today announced the availability of new Amazon Machine Images (AMIs) for Splunk® Enterprise 6 and Hunk™: Splunk Analytics for Hadoop. The new AMIs further accelerate the speed at which organizations can deploy Splunk software and gain critical visibility into their cloud-based applications and data. Splunk also released the new version of the Splunk App for Amazon Web Services (AWS), which leverages the newly announced AWS CloudTrail, a new service that logs all AWS API calls, to enable organizations to improve monitoring, security and compliance across all applications and infrastructure running in AWS. The Splunk Enterprise AMI and Hunk AMI are available in the AWS Marketplace. The Splunk App for AWS is available on Splunk Apps.
“Splunk Cloud, Splunk Storm and the new AMIs demonstrate our continued commitment to cloud computing and our innovative work with AWS,” said Leena Joshi, senior director of solutions marketing, Splunk. “Organizations are rapidly moving their applications to the cloud, and AWS is the leader in cloud computing. The release of AMIs for Splunk Enterprise and Hunk makes it easy for customers to use Splunk products in AWS so machine data is accessible, usable and valuable to everyone across the organization. The new version of the Splunk App for AWS will help organizations increase visibility into their cloud deployments by combining AWS access, usage and billing data to provide security intelligence along with operational and business insights.”
“We are very excited about the new Splunk offerings on AWS,” said Terry Wise, director of Worldwide Partner Ecosystem, AWS. “Enterprise customers with large Hadoop deployments can gain significant benefits from the Hunk AMI, which enables them to explore and interact with analytics of raw Hadoop data including Amazon Elastic MapReduce data. The availability of the Splunk Enterprise AMI, coupled with the prebuilt Splunk App for AWS, empowers customers to gain insights from machine-generated data across a range of uses, including operational monitoring, billing, security and compliance.”