Open Source Insider

May 14 2017   1:07PM GMT

Elastic twangs in snappy machine learning

Adrian Bridgwater Adrian Bridgwater Profile: Adrian Bridgwater


No self-respecting data management firm operates today without a healthy dose of machine learning at the heart of its technology stack. Data search, logging, security and analytics shop Elastic clearly resonates with this new de facto reality as it now adds machine learning into its core arsenal or capabilities.

Elastic is of course the company behind the open source Elasticsearch and the Elastic Stack products.

Into the Elastic 5.4 release then… (as a result of the recent acquisition of data anomaly detection business Prelert) Elastic’s machine learning features will work on any time series data set to automatically apply machine brain intelligence.

What functions evidence machine learning?

That’s an easy question to answer i.e. functions such as:

  • identifying anomalies,
  • streamlining root cause analysis,
  • reducing false positives within real-time apps.

The concept behind this technologies is that it should be used when trying to spot infrastructure problems, cyber attacks or business issues in real-time.

“Our vision is to take complexity out and make it simple for our users to deploy machine learning within the Elastic Stack for use cases like logging, security and metrics,” said Shay Banon, Elastic Founder and CEO. “I’m excited that our new unsupervised machine learning capabilities will give our users an out-of-the-box experience, at scale to find anomalies in their time series data — and in a way that is a natural extension of search and analytics.”

Elastic Stack is being used to by developers for collecting, enriching and analysing log files, security data, metrics and text documents etc.

Why machine learning is tough

The firm says that machine learning is tough to bring online. Why is this?

Because the biggest challenge lies in developing real-time operational systems for existing workstreams and use cases.

“Scarce and expensive data science skills are needed to figure-out the correct statistical models for different, diverse data sets and hand-crafted rules are brittle and often generate many false-positives,” says Elastic.

Elastic’s new machine learning capabilities use a familiar Kibana UI . The software installs into Elasticsearch and Kibana with a single command as part of X-Pack.

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