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.

At Logz.io, we believe that observability should be simple, smart, and fast—powered by AI to help teams move with confidence. This Fall, our users recognized that commitment by awarding Logz.io 15 badges on G2 across multiple categories and global markets. From ease of use to fast implementation, users and businesses alike are experiencing how AI-driven observability can transform their operations. Here’s a breakdown of what we achieved and why it matters for you.

Observability is critical to innovation, but for many organizations, soaring costs make it impossible to achieve. Logz.io is here to change that.

GenAI promises evolutionary changes in how we use observability tools, but meeting expectations means heeding the lessons of our AIOps mistakes. The emergence of generative AI in observability tools was inevitable, but there’s already been an extreme degree of hype in the market. Monitoring, DevOps and ITOps have never been immune to trends, and with GenAI capabilities, the propagandahype machine is running out of control.

When Gartner publishes their annual observability industry research, it’s always exciting to find your company named among the most successful and high-profile providers in this space. That’s why Logz.io is thrilled to find itself listed as a Visionary for the third consecutive year in the Gartner Magic Quadrant for Observability Platforms (previously known as the Magic Quadrant for Application Performance Monitoring and Observability).

That’s the assessment of Senior DevOps Engineer and Logz.io user Armin Morattab when discussing the impact of AI on his day-to-day job. He dives deep on AI, observability, and strategies for improving workflows with Logz.io Co-founder Asaf Yigal in our webinar, AI in Observability: Real Engineers Talk Real Uses Cases.

Your team is responsible for ensuring the reliability and performance of your organization’s critical applications and infrastructure. What keeps you up at night? Your applications are more complex, distributed and cloud-native than ever, meaning that understanding what’s happening under the hood has never been more complex than it is now. Is it system bugs, or data bottlenecks? Chasing alerts for latency or service degradation that may or may not be business-critical?