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By Libi Michelson
TL;DR Agentic observability uses AI agents to autonomously investigate incidents, identify root causes, and take action in production environments. Unlike traditional monitoring (which alerts and waits) or AIOps (which assists human analysis), agentic platforms conduct the investigation themselves. Key capabilities include autonomous incident triage, evidence-backed root cause analysis, alert noise reduction, and governed remediation.
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By Libi Michelson
Incident investigations take so long not because the fix is hard, but because finding the right fix is. Most engineers spend 20 to 60 minutes just understanding what’s wrong before they can act, not fixing anything, just trying to see the full picture. The framework that changes this has four steps: Orient, Isolate, Hypothesize, and Verify, and the order matters more than the tools.
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By Libi Michelson
TL;DR Choosing the right AI-powered observability platform isn’t about who has the most AI features. It’s about which platform helps your team identify root causes faster and spend less time investigating incidents. Here’s the short version: Logz.io + OrionIQ: Autonomous AI agents investigate incidents, perform root cause analysis, and surface next steps. Open standards, Kubernetes-ready, and deploys in as little as a week.
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By Libi Michelson
TL;DR Picking the right log management platform in 2026 comes down to three things: how much operational overhead you can absorb, how much AI automation you need, and what you’re willing to spend.
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By Libi Michelson
Effective Kubernetes monitoring in 2026 is critical due to increased cluster scale and microservices complexity, demanding a shift toward unified observability (logs, metrics, and traces). The core focus is leveraging AI-driven features to automate anomaly detection, correlate diverse data, and significantly reduce Mean Time to Recovery (MTTR).
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By Tomer Levy
OrionIQ is Logz.io’s new agentic observability platform designed to move teams from detecting issues to resolving them automatically. As AI accelerates software development, operations remain manual: engineers still wake up at 2 a.m. to investigate alerts and rebuild context. OrionIQ uses AI agents to analyze real-time telemetry, investigate incidents, identify root causes, and take action across systems.
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By Spencer Bos
For years, organizations tried to solve operational pain by collecting more data, adding more dashboards, and consolidating more tools. But 2025 exposed a deeper mismatch. Systems had become more distributed, AI-assisted, and interdependent than ever before, while teams had shrunk and on-call pressure had intensified. This wasn’t a tooling failure. It was an architectural and cognitive one.
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By Asaf Yigal
It’s 2026, and developers have more tools at their disposal than at any point in the industry’s history: CI/CD platforms are richer; observability stacks are deeper; security, data, and AI tooling have exploded into crowded, competitive ecosystems. And yet, delivery is still slow, incidents are still noisy, workflows are still brittle. The problem is no longer tool scarcity or feature depth. It’s integration debt.
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By Amos Etzion
We’ve updated Logs Explore to integrate the real-time streaming capabilities of the old “LiveTail” into our new Explore environment. The result? A faster and more seamless experience. Customers can now benefit from.
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By Yotam Loewenbach
Distributed tracing is a core tool for operating modern microservices platforms. For SREs and DevOps teams, it is often the fastest way to understand latency issues, service dependencies, and unexpected failure modes. But achieving comprehensive tracing coverage is resource-intensive and time-consuming. It usually requires application changes, language-specific instrumentation, agent lifecycle management, and ongoing coordination with development teams.
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By Logz.io
Incident investigations take so long not because the fix is hard, but because finding the right fix is. Most engineers spend 20 to 60 minutes just understanding what’s wrong before they can act, not fixing anything, just trying to see the full picture. The framework that changes this has four steps: Orient, Isolate, Hypothesize, and Verify, and the order matters more than the tools.
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By Logz.io
A short demo showing how Logz.io, powered by the AI Agent, helps investigate security incidents by analyzing and correlating data. The AI Agent uses natural language to: Query and correlate SIEM questions with related logs Detect anomalies and highlight unusual activity Summarize findings to speed up root cause analysis Provide recommended actions This video demonstrates a practical SIEM use case for the AI Agent inside Logz.io.
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By Logz.io
Experience the new Open 360 AI, built to help you explore, analyze, and act on your observability data in a smarter way. See how the AI Agent works directly inside dashboards to explain anomalies, summarize trends across your telemetry data, and guide you to root cause, without switching views or writing queries. Everything you know and love is still here, now enhanced with AI.
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By Logz.io
A short demo showing how Logz.io, powered by the AI Agent, helps investigate security incidents by analyzing and correlating data. The AI Agent uses natural language to: This video demonstrates a practical SIEM use case for the AI Agent inside Logz.io.
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By Logz.io
Watch how AI is reshaping observability for the years ahead. In this fireside chat, Logz.io founders Tomer Levy and Asaf Yigal reveal how the most innovative AI-first companies are breaking free from dashboards, avoiding common RFP mistakes, and building future-ready stacks. You’ll see: Watch and learn how autonomous AI eliminates noise, slashes costs, and gives engineering teams back their velocity.
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By Logz.io
Watch AI transform alert management in real-time. This technical demonstration compares manual alert investigation with AI alert investigation. It shows how AI agents automatically investigate production alerts, correlate telemetry across distributed systems, and identify root cause, faster and with more insights than manual processes. Watch and learn how to shift your team from reactive firefighting to proactive system reliability management with agentic AI.
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By Logz.io
Logz.io’s OpenSearch Optimization Tool is a free, open-source CLI utility that gives you fast, actionable insights into your cluster’s performance, cost, and configuration.
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By Logz.io
Struggling with high observability costs? In this video, Jade Lassery breaks down the challenges of managing excessive data and skyrocketing expenses. She introduces the Logz.io AI agent, a powerful solution designed to optimize data usage, reduce unnecessary costs, and improve efficiency. Learn how to take control of your observability spending while maintaining high performance. Watch now to discover smarter data management strategies!
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By Logz.io
Struggling with Kubernetes performance issues? This video introduces an AI-powered agent designed to help users quickly identify and resolve bottlenecks. By analyzing logs, the AI detects performance issues, streamlining troubleshooting and improving system efficiency. Watch now to see how AI can simplify Kubernetes performance management and keep your infrastructure running smoothly!
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By logz.io
In the video, Jade Lassery discusses how to effectively manage complex environments, especially when faced with unexpected spikes in errors. She introduces a Logz.io AI agent prompt that assists users in quickly identifying the root cause of these issues. By simply asking the right questions, users can streamline their troubleshooting process and enhance their operational efficiency.
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Logz.io is an AI-powered log analysis platform that offers the open source ELK Stack as a enterprise-grade cloud service with machine learning technology. Our platform uses AI and and machine-learning algorithms to help DevOps engineers, system administrators, and developers to find critical events in the volumes of information that are now constantly generated in IT environments.
Created by a Check Point veteran and a former algorithm engineer for the Israeli military, the enterprise-grade, cloud platform is built on top of the ELK Stack and provides real-time access to data insights based on the collaborative knowledge of IT executives throughout the world. The ELK Stack -- Elasticsearch, Logstash, and Kibana -- is the world’s most popular open-source log analytics software stack.