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Loggly Connects the Dots: Logs, Metrics, Monitoring, and Source Code Access to Streamline DevOps Processes
Loggly today announced Loggly 3.0, a unified log analysis and monitoring solution designed for companies building modern software applications running on private or public clouds and serverless architectures. Combining new metrics and monitoring capabilities with deep log analysis and one-click access to source code, Loggly 3.0 gives DevOps teams one-stop visibility to identify and solve problems, collaborate on fixes, and report to stakeholders.

"Loggly 3.0 charts give us a variety of ways to quickly visualize data, and its dashboards let us organize this data in the most useful ways for detecting and understanding the problems that arise in software and infrastructure"

"Loggly 3.0 charts give us a variety of ways to quickly visualize data, and its dashboards let us organize this data in the most useful ways for detecting and understanding the problems that arise in software and infrastructure," said Ryan Jung, site reliability engineer at ClearCare. "This is the latest example of how Loggly continues to improve."

"Our customers are facing exploding volumes of machine data generated by dynamic infrastructure, microservices, and devices, as well as the constant change of continuous delivery," said Manoj Chaudhary, chief technology officer at Loggly. "Their monitoring toolkits have grown to address the data overload, sometimes creating even more complexity. This is what is driving convergence in the DevOps ecosystem between logs and monitoring. Loggly 3.0 offers a simple and comprehensive path to dealing with data and tool overload, and it builds up DevOps teams' efficiency and collaboration."

Loggly customers can now address three distinct needs with a single cloud-based service:
  • Proactive monitoring for potential issues, anomalies, or suspicious activity across their code and infrastructure. New charts and dashboards reveal the full story and can be created in just a few clicks. In addition to the ability to display any log-resident or Amazon CloudWatch metric, Loggly will support metrics collection using the collectd daemon in the fourth quarter of 2017.
  • Deep-dive investigations, discovering root causes by searching and filtering on individual log events. A new integration with GitHub connects insights from dashboards to logs to individual lines of source code, without any additional instrumentation. The GitHub integration initially supports Java, JavaScript, and Python.
  • Data analysis and visualization to characterize software performance, answer key business questions, spot trends, report on KPIs, and track SLA compliance. Users can work in Loggly without support from a dedicated administrator.
The new GitHub integration builds on previous Loggly integrations designed to improve teamwork by incorporating data and analysis within the tools that software teams use every day, including New Relic, PagerDuty, Slack, Atlassian HipChat, and Atlassian Jira Software.

Summary Benefits
  • Reduced complexity with one unified solution for monitoring, visualization, and log analysis.
  • Improved service quality through proactive monitoring of metrics across the entire software stack, along with the deep analysis needed to know where to make improvements.
  • Shorter mean time to resolution (MTTR) through rapid root cause analysis and tighter connections between metrics and relevant events.
  • Better teamwork through common insights on shared dashboards, comprehensive reporting, and integration with the DevOps toolchain.
To learn more about how Loggly 3.0 can help your organization, visit https://www.loggly.com
Published Wednesday, October 04, 2017 12:32 PM by David Marshall
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