What is Logz?

Profile

Logz.io is a proprietary SaaS observability tool suite built on open source foundations including OpenSearch, Prometheus, and Jaeger. The solution unifies logs, metrics, traces, and security monitoring in a managed service enhanced by AI-powered analysis capabilities. As a venture-backed company founded in 2014 with over $120M in funding, Logz.io has established itself as a significant player in the cloud-native observability space. Its core value proposition centers on delivering enterprise-grade observability without the operational overhead of managing complex open source monitoring stacks.

Focus

The platform addresses fundamental challenges in modern distributed system observability: the complexity of correlating telemetry across microservices architectures, the operational burden of scaling monitoring infrastructure, and the expertise required to effectively analyze observability data. It serves platform engineering teams who need comprehensive visibility across cloud-native environments without managing multiple disparate tools. The solution particularly benefits organizations running Kubernetes and microservices architectures who want to leverage open source monitoring capabilities while avoiding the operational complexity of self-hosted implementations.

Background

Logz.io was founded by Tomer Levy and Asaf Yigal, who brought extensive experience from Check Point Software and other Israeli technology companies. The platform initially built on the ELK Stack, later transitioning to OpenSearch following Elastic's 2021 license changes. The company played a key role in establishing OpenSearch as a community-governed alternative under The Linux Foundation. The platform remains privately held and actively developed, with headquarters split between Boston and Tel Aviv, serving customers across industries including Dish Network, Unity Technologies, and ZipRecruiter.

Main features

AI-powered observability analysis and automation

The platform's AI Agent employs generative AI and machine learning to automate root cause analysis and accelerate troubleshooting workflows. It enables natural language interaction with observability data, automatically correlates anomalies across logs, metrics, and traces, and generates detailed investigation reports. The system can autonomously analyze alert patterns, identify emerging issues, and provide actionable remediation recommendations, transforming observability from a reactive to proactive discipline.

Unified telemetry management with cost optimization

The Data Optimization Hub provides centralized visibility and control over telemetry ingestion across all data types. It automatically identifies high-volume log patterns and metrics, enables targeted filtering of low-value data, and supports conversion of logs to metrics for more efficient storage. The multi-tiered storage architecture automatically moves data between performance tiers based on access patterns, while maintaining compliance with retention requirements.

Kubernetes-native observability platform

The Kubernetes 360 capability delivers unified monitoring across cluster control planes, worker nodes, pods, and applications. It automatically discovers and monitors Kubernetes resources as they are created and destroyed, collecting logs, metrics, and traces without manual configuration. The solution provides out-of-the-box dashboards for key Kubernetes health indicators and enables seamless correlation between infrastructure metrics, application logs, and distributed traces for rapid problem resolution.