Complexity rules the day within the world of data systems and pipelines. A goal for any observability practice is to help reduce complexity and give users and administrators a clear view of what’s happening in any system. This is the path to unified observability, a mature system where monitoring and troubleshooting are streamlined. This has been difficult to achieve for many organizations.

As digital applications and infrastructures grow increasingly complex, managing and understanding log data has become increasingly vital in achieving practical observability, enabling organizations to detect, diagnose, and prevent issues across their systems. However, traditional log analysis methods often struggle with the volume and complexities of modern log data in cloud-native environments.

These days, one of the most important decisions that organizations can make as it relates to their observability strategy is: “How much data do we want to retain in Hot storage to ensure we have everything needed for real time analysis — without running up associated costs?”

We’re rolling out new visualization capabilities in the Explore log management interface that are available now in some accounts and will be added to all in the coming weeks and months. With these updates you can: Warm Tier: There is now a new option for log storage and access that bridges the gap between high-performance Hot storage and the low-cost Cold Tier. Reach out to your customer success team for more information.

A critical component of any monitoring and observability system is alerting. But alerts in and of themselves aren’t enough—when something goes wrong, time is of the essence, and your team needs to figure out not just what’s going on but how to fix it, and fast. Additionally, constantly chasing down alerts can be the bane of any observability practitioner’s existence.

As Gartner predicts, AI will support up to 70% of performance monitoring and troubleshooting tasks in the next few years. The Logz.io AI Agent helps teams get ahead of this curve today. Too much time spent troubleshooting? You’re not alone. Manual investigation, jumping between dashboards, and piecing together scattered data are time-consuming and frustrating.

In the webinar, the experts explained why a log management strategy is crucial if you want to accurately assess the health and compliance of your applications. Topics include: Cloud native technologies have made it harder to understand how systems are behaving. Logs are the answer, but they can be voluminous and complex in any environment. How do you make sense of them?

We’ve improved the filter pane to include: Additionally, a new time-picker option lets you mix absolute and relative times and manually set the date and time to the second. Additionally, you can view your data in either UTC or your local time zone. Saved searches from Explore can now be used to create visualizations and dashboards in OpenSearch Dashboards, streamlining data analysis.

Logz.io introduces its AI Agent in Beta, using GenAI to revolutionize observability. The AI Agent simplifies monitoring with automated data analysis and root cause detection, accelerating issue resolution by 3-5x for beta users—marking a critical step toward fully autonomous observability.

Autonomous observability for system monitoring and management aims to use GenAI and machine learning to automatically detect, diagnose and resolve issues. In conversations about cloud observability today, discussions often shift from “what’s possible” to “what’s practical.” Too often, these conversations highlight the shortcomings of current observability processes, tools and financial models.