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Logentries’ New Analytics Language Makes the Power of Log Data Accessible to the Masses

Logentries’ New Analytics Language Makes the Power of Log Data Accessible to the Masses

 

BOSTON, May 28, 2015 Logentries, the leading provider of log management and analytics built for the cloud, today announced a new Analytics Language that offers an easy-to-use alternative to traditional search languages that require deep technical skill and often include more than 100 search terms. The new Logentries Query Language (LEQL) bridges the gap between management and analysis by enabling users to not only collect and search log data in real-time, but now use logs to visualize high-level trends, perform sophisticated correlation across log data streams, and drill down as needed to the most fine-grained format of their data.

Today's distributed, cloud-based environments produce billions of machine-generated data, making separate tools for monitoring, alerting, troubleshooting and analyzing data across systems, applications and end users completely unmanageable. Organizations need a single tool to monitor, alert and analyze multiple data sources using one shared data format.

The Logentries Query Language (LEQL) helps users to slice-and-dice their data using sophisticated search functions such as Count, Sum, Average, Min, Max, Group By, Sort and more. The new analytics language delivers the ability to see both the high level trend reports and the most fine-grained view of system and application performance using oe single tool. This consolidated, easy-to-use view has become critical to improving efficiency and time to resolution for IT and Dev Ops teams and makes log analysis finally accessible to all members of the IT and Dev Ops teams, not just the data scientists.

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With the addition of the new real-time Analytics language, Logentries now enables the three key pillars of DataOps, a critical approach to better managing and understanding all available data across an organization to inform smarter IT and Dev Ops decision making. Log data uniquely enables DataOps by collecting, centralizing and analyzing all log data across the entire software stack from every type of component using:



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