Splunk is to add machine learning capabilities to its four main software packages and services, and roll out a new user interface for its analytics tools that makes them easier to use for occasional and less technical users.
The updates, announced at the company's seventh .conf2016 user conference in Orlando, are being rolled into Splunk Enterprise 6.5, Splunk IT Service Intelligence, Splunk Enterprise Security and Splunk User Behaviour Analytics.
All are available as on-premise software packages or on a subscription-based model in the cloud.
The company has incorporated a series of packaged algorithms to provide new automated functions, as well as the ability for users to build their own custom algorithms.
The move is part of a shift towards predictive analytics based on behavioural analysis to let organisations use machine learning tools to optimise IT, security and business operations, with the machine learning providing more automated responses.
The company has suggested four key uses for the machine learning tools:
- Security investigation and analysis, helping security teams to identify and resolve IT and security incidents by automatically detecting anomalies and patterns in data
- Intelligent alerting, to help reduce 'alert fatigue' by identifying normal patterns for specific sets of circumstances and hence abnormal patterns
- Predictive actions, so that organisations can better anticipate the consequences of, for example, proactive maintenance that might otherwise disrupt operations
- Business optimisation, to help organisations better forecast demand, manage inventory and react to changing business conditions via the analysis of historical data and models.
Splunk Enterprise 6.5, unveiled today, will include a guided workbench to create customer machine learning models. In addition, the company claimed that it will simplify data preparation and enable organisations to expand analytics to a wider range of users with a more intuitive interface and table-data views that can be used by occasional, less technically advanced, users as well as specialists.
It will also offer tighter integration with Hadoop, and organisations will be able to roll historical data into Hadoop and use hybrid search to analyse all their data in Splunk.
Likewise, Splunk IT Service Intelligence 2.4, also unveiled today, adds tools to let users apply machine learning to event data. It will include pre-built machine learning algorithms that can be dynamically applied to baselined 'normal' operational patterns, taking account of different thresholds at different times. The aim is to reduce false positives and 'alert fatigue'.
It will also prioritise incidents through event analytics, such as multivariate anomaly detection, supported with business and services context and, like Splunk Enterprise, offer a new interface that Splunk claimed is easier to use. It will also reduce the need for costly customisations.
Splunk Enterprise Security 4.5 will also feature the new user interface, while Splunk User Behaviour Analytics 3.0 will include the new machine learning tools, as well as additional data sources and content updates of use cases.
"Digital transformation has changed the way that organisations work. The big secret is that all of the change is underpinned by machine data," said Splunk CEO Doug Merritt.
"Machine learning enables organisations to get deeper insights from their machine data and ultimately increases the opportunity our customers can gain from digital transformation.
"The enterprise machine data fabric is the foundation for managing and deriving insights from that data at scale, and only Splunk provides the end-to-end analytics platform and ecosystem to support it."
Splunk's technology is widely deployed in major organisations around the world to cover a diverse range of applications.
These include Valve Software, which uses Splunk to monitor the performance on its wildly popular Steam PC gaming platform, French bank BNP Paribas, which rolled out the software to senior business managers, and Paddy Power Betfair, which uses Splunk across its organisation for security monitoring and customer big data projects.
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