Slow Root Cause Analysis
“Logz.io turned root cause analysis into a matter of minutes.”
VP of Engineering at Snyk
VP of Engineering at Snyk
AI-Powered Observability
Unify logs, metrics and traces with
AI-driven insights
AI-driven insights
Your Observability Challenges Solved
Siloed Monitoring Tools
“Before Logz.io, we were spending over 20% of our time managing our platform.”
Head of DevOps at The Economist
Head of DevOps at The Economist
Exploding Costs
Dish Network removed 62% of their observability data and costs by filtering out unneeded data
Operational Complexity
“Logz.io allows us to focus more on what matters – building and monitoring our product.”
SRE at ZipRecruiter
SRE at ZipRecruiter
Faster Insights and Automated Root Cause Analysis
- 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.
Unified Observability — Logs, Metrics, and Traces in One Place
- 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.
“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
CEO and Co-Founder
Logz.io
Full Stack Observability – Single Pane of Glass
- 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.
- Kubernetes 360 and Service Overview automatically highlight key telemetry data.
- Use GenAI to debug issues quickly and efficiently with clear investigation paths.
- Correlate logs, metrics, and traces for faster, data-driven troubleshooting.
- Automate Root Cause Analysis (RCA) to resolve issues with minimal effort.
- Get critical app and infrastructure insights out of the box for faster decision-making.
Logz.io Observability Platform FAQs
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.
Since observability data collection, storage, and processing can be a complex and time-consuming task, observability-as-a-service solutions can offload considerable time and effort from engineers who may prefer to focus their time elsewhere.
Why cloud-native observability?
Cloud-native observability can ensure scalability, reliability, and performance needed for real-time telemetry data collection and analysis.
Observability systems must ingest and store large influxes of telemetry over short time frames. Cloud-native architectures like Logz.io’s help ensure the observability system can rapidly adjust its cloud resources and data pipelines in response to fluctuating load. This can prevent performance issues, slow queries, and unavailable data.
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. Eliminate guesswork and transitions into a real-time cost model that empowers flexible usage of every aspect of the platform.
See our Pricing Page for more details.
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.
Logz.io is enabling organizations to get on the pathway to Autonomous Observability today with its Observability IQ platform capabilities – delivering innovative AI-powered log management, observability and root cause analysis that transforms the manner in which engineering teams optimize their cloud applications and infrastructure.
How do I reduce my observability costs?
The surest path to observability cost reduction is through data optimization, which reduces the total computing footprint of your telemetry data. You can filter out unneeded data, move infrequently-accessed data to cold storage, and convert logs to metrics. Additionally, an AI-powered observability platform will reduce costs by cutting down manual tasks and helping speed MTTR so your systems run smoothly.
What can an open source observability platform provide?
Open source observability platforms unify open source logging, metrics monitoring, and tracing observability tools in one centralized view. They can provide the familiarity and interoperability of open source, and the simplicity of SaaS.
Plus, by unifying log, metric, and trace data together, open source observability platforms can help users correlate across the data to investigate the root cause of issues faster.
Why migrate from ELK or open source to Logz.io?
While the ELK stack provides a powerful set of tools for monitoring and troubleshooting cloud environments, it can generate significant management effort, particularly as your requirements scale. Further, ELK lacks a unified approach to observability. By comparison, with an observability platform such as Logz.io, users can analyze their logs, metrics, and traces in a single-pane-of-glass, while enjoying effortless deployment, management, and scaling – saving time and resources previously spent on ELK maintenance.
How can GenAI integration transform observability today?
Integration with Generative AI and use of AI Agent technology is transforming observability at a rapid pace, automating users’ abilities to detect, diagnose, and resolve issues, while off-loading and empowering technical teams to focus on strategic objectives. This current advancement toward the availability of Autonomous Observability immediately empowers organizations to evolve beyond traditional dashboards, alerts and investigation steps to engage a proactive AI-powered system that enables teams to work faster and be more productive, ultimately driving innovation.
