AI-Powered Observability

Unify logs, metrics and traces with AI-driven insights

Your Observability Challenges Solved

• Leverage AI to detect anomalies and correlate data across logs, metrics, and traces.

• Drastically reduce mean time to resolution (MTTR), finding the root cause in minutes.

• Automatically generate recommended resolution steps and action plans.

• Centralize logs, metrics, and traces with 300+ integrations.

• Get a complete real-time view of your system in one place, eliminating data silos and tool sprawl.

• Simplify monitoring and troubleshooting with Trace Quickview options for log correlation, app performance and infrastructure health.

• Employ unified solutions for Kubernetes and Application performance monitoring, centralizing visualization and analysis.

• Save 30-50% on observability costs without compromising performance.

• Filter out unnecessary data and store it more efficiently.

• Convert logs to metrics to reduce storage overhead and cut costs.

“The industry is rapidly moving away from legacy APM toward modern, AI-powered observability as customers simply cannot afford to maintain the traditional approach…”

Tomer Levy
CEO and Co-Founder, Logz.io

• Easily surface existing production issues to reduce manual analysis.

• Move immediately from detection into automated investigation.

• Execute broad, context-aware analysis highlighting system implications.

• Pinpoint the manner that issues were introduced, including deployments.

• Generate detailed conclusions that inform problem resolution.

• Run high-speed log searches with AI-powered correlation and insights.

• Converse directly with your data using Logz.io AI Agent.

• Automate troubleshooting with AI-driven Root Cause Analysis (RCA).

• Reduce logging volume and storage costs with Data Optimization Hub.

• Store data efficiently with Cold Tier storage to cut costs further.

• Get a complete, real-time overview of infrastructure health with Kubernetes 360.

• Surface critical insights automatically through AI-driven analysis.

• Set up custom alerts and monitoring dashboards with minimal configuration.

• Monitor any component with flexible, customizable dashboards.

• Respond faster to issues with instant, AI-powered infrastructure insights.

• Monitor application performance with AI-driven Service Overview and Service Map.

• Visualize microservices architecture and quickly isolate latency with Distributed Tracing.

• Drill down into performance trends for deeper insights into app behavior.

• Identify bottlenecks and optimize performance across complex environments.

• Troubleshoot faster with real-time, AI-enhanced tracing data.

“[Logz.io] helps expand your visibility into your entire infrastructure and also it helps you identify performance issues.”

David Lemaire

IT Director Life is Good

What can observability platforms do?
Observability helps engineers understand what’s happening in their environment and why through real-time telemetry data analytics – observability platforms such as Logz.io make real-time telemetry analytics possible.

Observability platforms collect and store telemetry data – including logs, metrics, and traces, which are often described as the three pillars of observability – and make this data available for analysis. Engineers use this data to monitor and diagnose system behavior, so they can deliver more performant and reliable services. Now with the additional power of AI integrated into observability platforms like Logz.io, organizations can get answers to critical questions about their data fast.

What is observability-as-a-service?
Observability-as-a-service is a way of delivering real-time telemetry data analytics needed for observability. Unlike self-hosted observability solutions, observability-as-a-service solutions such as Logz.io manage the entire data infrastructure for the user.

Why cloud-native observability?
Cloud-native observability can ensure scalability, reliability, and performance needed for real-time telemetry data collection and analysis.

How is Logz.io priced?
Logz.io’s consumption-based pricing provides the most flexible, efficient observability pricing on the market today – enabling customers to pay for precisely those Open 360 platform services they use, preventing onerous overages and tailoring spend to their unique requirements.

What is Autonomous Observability?
Autonomous Observability is the next-generation approach to system monitoring and management that leverages GenAI and machine learning to automatically detect, diagnose, and resolve issues without human intervention. This evolution allows technical teams to focus on strategic tasks while ensuring optimal system performance and reliability.