Logentries Revolutionizes "Live Tail" for DevOps in the Cloud

BOSTON, Aug. 5, 2014 /PRNewswire/ -- Logentries, the most connected log management and analytics service, today announced new Aggregated Live Tail view for real-time monitoring of important security and performance events, and proactive troubleshooting across production systems. As a cloud service, Logentries Aggregated Live Tail enables users running on virtually any platform, on-premise, or in the cloud, to watch and filter multiple log streams simultaneously, and instantly validate important events occurring in production.

"The Logentries service, particularly the Aggregated Live Tail, has been invaluable as we continue to expand and enhance our platform," said Scott Rankin, VP of Technology, Motus. "The Aggregated Live Tail saves our developers and operations teams a tremendous amount of time when pushing out releases across multiple machines, and has allowed us to troubleshoot issues much faster than we ever could before."

Today, IT and development teams must fully support distributed networks, systems, and teams across cloud-enabled environments. This often demands real-time, log-level visibility into servers, applications, and systems of all types, which historically have not been easy to access. Logentries has built a log management and analytics service for cloud-enabled environments where real-time access and deep insight into system events and activity is required. The new Aggregated Live Tail view makes this even easier by bringing selected log streams together into one single view, and providing real-time monitoring and alerting.

With Logentries Aggregated Live Tail, users can:

• Dynamically aggregate logs from across different sources into a single view.        
• Watch aggregate log data streams in real-time.
• Search and filter live data to highlight important events in production.           

Logentries' Aggregated Live Tail collects logs in virtually any format, from virtually any system and makes them available in live tail mode within seconds. All logs pass through the Logentries pre-processing engine that automatically tags and creates alerts on important log events and trends. The new aggregated view also enables automated, real-time filtering to only show events that contain particular parameters, which help to quickly identify the most important events amid billion of log files.

"We are very excited to bring Aggregated Live Tail to the Logentries Community and offer the ability to monitor all your log streams aggregated into a single view," said Trevor Parsons, Co-founder and Chief Scientist, Logentries. "Unlike legacy approaches, our customers can now easily monitor in live mode 24/7 to quickly pinpoint where server errors are occurring in seconds."

The cloud-based Logentries service collects and pre-processes log events in real-time for on-demand analysis, alerting and visualization. With custom tagging and filtering, users can correlate security and performance issues with broader infrastructure activity including application usage, server metrics, and user behavior. To get learn more about Aggregated Live tail, or to get started today with a free, all-inclusive 30-day trial of the Logentries service, visit http://logentries.com.

About Logentries
Logentries is the world's most connected log management and analytics service, making business insights from machine-generated log data easily accessible to development, IT and business operations teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users. While traditional log management and analytics solutions require advanced technical skills to use, and are costly to set-up, Logentries provides an alternative designed for managing huge amounts of data, visualizing insights that matter, and sharing that information across its global user community. To sign up for the free Logentries service, visit www.logentries.com.

SOURCE Logentries