At its Splunk .conf 2017 conference in Washington DC this week, Splunk announced its next range of products, including expanded machine learning capabilities across the portfolio, making "machine learning mainstream", it says.
Specifically, Splunk announced the release of Splunk Enterprise 7.0, Splunk IT Service Intelligence (ITSI) 3.0, Splunk User Behaviour Analytics (UBA) 4.0, and updates to Splunk Cloud, along with an updated suite of solutions to apply analytics and machine learning to fraud and cloud monitoring use cases.
“Machine learning is critical to customer success and to the evolution of Splunk. Our seamlessly integrated capabilities open up machine learning to everyone, enabling our customers to better predict future outcomes and more effectively analyse their data,” said Richard Campione, chief product officer, Splunk. “Data is a strategic advantage and organisations are looking for the fastest, most efficient way to turn data into answers. With machine learning and metrics advancements that anyone can use, Splunk Enterprise 7.0 and Splunk Cloud powerfully deliver mission-critical answers faster and easier than ever before.”
Splunk is already known for delivering performance over big data at scale but states the new products have achieved greater performance, accelerating monitoring and alerting by 20x, and core search by 3x.
While more power and speed is always desirable, Splunk says this performance gain is strategic, not just delivering results faster, but enabling customers to predict future IT, security and business outcomes through the integrated machine learning in the new Splunk product range. These enhancements allow users to collect, prepare transform, explore, visualise and publish data insights.
Machine learning is often talked about and is seen by many as the next frontier of business intelligence and analytics. It brings the potential of turning data analysis around, from delivering high-quality historic and current information to giving companies insights into trends and predictions that it may not have otherwise considered or recognised.
“Staples uses Splunk Enterprise for real-time analysis of critical business transitions — from order management to invoicing, to warehousing — to ultimately enhance our customer experience and stay ahead of online competitors,” said Faisal Masud, chief technology officer, Staples. “Splunk analytics and metrics are helping us optimise every aspect of what we do, including quickly identifying and correcting irregular transactions so customers receive the best possible service. The Splunk Enterprise platform is a critical piece of our business operations foundation.”
These machine learning capabilities are also delivered in Splunk's existing premium-packaged solutions, including Splunk ITSI 3.0, combing service context with machine learning to identify existing and potential issues prioritise restoration of business-critical services and deliver analytics-driven IT operations; and Splunk UBA 4.0, enabling customers to create and load their own machine learning models to identify custom anomalies and threats by opening up Splunk UBA to the world via a newly released software development kit (SDK).
Splunk also released a free Splunk Machine Learning Toolkit (MLTK) to all customers. This is a data science application that includes public machine learning APIs for open source and proprietary algorithms, a data preparation module to help customers prepare and clean their data, and machine learning model management.
Splunk further announced the availability of Splunk Enterprise Security (ES) Content Update, Splunk Security Essentials for Fraud Detection, Splunk Insights for AWS Cloud Monitoring, Splunk Insights for Ransomware, and Booz Allen Hamilton Cyber4Sight for Splunk.
The new Splunk Enterprise 7.0 is available today, and Splunk ITSI 3.0 and UBA 4.0 will be available in October. The next release of Splunk Cloud will be available by January 2018.
The writer is attending Splunk .conf 2017 as a guest of the company.