Loggly 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.
“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, CTO 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.
Benefits of Loggly 3.0 include:
- 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.
The Latest
In MEAN TIME TO INSIGHT Episode 5, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the network source of truth ...
A vast majority (89%) of organizations have rapidly expanded their technology in the past few years and three quarters (76%) say it's brought with it increased "chaos" that they have to manage, according to Situation Report 2024: Managing Technology Chaos from Software AG ...
In 2024 the number one challenge facing IT teams is a lack of skilled workers, and many are turning to automation as an answer, according to IT Trends: 2024 Industry Report ...
Organizations are continuing to embrace multicloud environments and cloud-native architectures to enable rapid transformation and deliver secure innovation. However, despite the speed, scale, and agility enabled by these modern cloud ecosystems, organizations are struggling to manage the explosion of data they create, according to The state of observability 2024: Overcoming complexity through AI-driven analytics and automation strategies, a report from Dynatrace ...
Organizations recognize the value of observability, but only 10% of them are actually practicing full observability of their applications and infrastructure. This is among the key findings from the recently completed Logz.io 2024 Observability Pulse Survey and Report ...
Businesses must adopt a comprehensive Internet Performance Monitoring (IPM) strategy, says Enterprise Management Associates (EMA), a leading IT analyst research firm. This strategy is crucial to bridge the significant observability gap within today's complex IT infrastructures. The recommendation is particularly timely, given that 99% of enterprises are expanding their use of the Internet as a primary connectivity conduit while facing challenges due to the inefficiency of multiple, disjointed monitoring tools, according to Modern Enterprises Must Boost Observability with Internet Performance Monitoring, a new report from EMA and Catchpoint ...
Choosing the right approach is critical with cloud monitoring in hybrid environments. Otherwise, you may drive up costs with features you don’t need and risk diminishing the visibility of your on-premises IT ...
Consumers ranked the marketing strategies and missteps that most significantly impact brand trust, which 73% say is their biggest motivator to share first-party data, according to The Rules of the Marketing Game, a 2023 report from Pantheon ...
Digital experience monitoring is the practice of monitoring and analyzing the complete digital user journey of your applications, websites, APIs, and other digital services. It involves tracking the performance of your web application from the perspective of the end user, providing detailed insights on user experience, app performance, and customer satisfaction ...
