Elastic expanded its Elastic Stack with a new release that adds enhanced capabilities to the platform for data analytics and management.
The Elastic Stack integrates multiple elements and was originally known as the ELK stack, which is an acronym for the origin core components, Elasticsearch, Logstash and Kibana. Elasticsearch provides search and analytics capabilities, Logstash helps to inject and collect data, while Kibana provides the visualization elements.
Among the key new additions in Elastic Stack 7.3 is a capability known as Data Frames, which provide a different way to manage data in terms of entities such as hosts, which in turn can lead to different types of analysis
"What data frames allow you to do is transform event-based data into entity-centric data," said Steve Kearns, VP of Product Management, Elastic. "In some cases, you want to transform data so instead of an index of event-based data, you want an index of entities and host and a set of properties about those hosts."
Another key new feature in the Elastic Stack 7.3 update is the integration of machine learning capabilities into Kibana that provide enhanced analytics capabilities.
Kearns explained that the way a Kibana visualization works is the user chooses what they want to search and then the system creates a visualization from the time series data. Including machine learning now enables a user to benefit from advanced analytics to identify different trends from the data. The machine learning can be used for any number of different use cases, including enabling an unsupervised anomaly detection capability from logs.
Another key addition in the Elastic Stack 7.3 update is the general availability of the Maps feature, which can be used to help visualize network usage and infrastructure.
"It's a rich way of visualizing and exploring geospatial data," Kearns said. "We realized that users want to be able to display multiple layers of data and want to be able to overlay multiple different views and be able to bring in different kinds of queries."
Kearns noted that Elastic Stack 7.3 provides more data sources as well. Among the data sources now supported are Oracle database, Amazon RDS and CockroachDB alongside improved integration with Amazon Kinesis data streams. For application performance monitoring, Elastic Stack 7.3 now gains support for Microsoft's .net framework and its data libraries.
"One of the things that we've been doing to make usage easier over the years has been producing what you can really think of as pre-canned data sources," he said. "We've continued to expand the set of data sources that we support and this release really has quite a few."
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