LogRack is an AI-assisted logging and debugging platform. Centralize logs, correlate events across services, and resolve incidents faster with intelligent analysis.
A unified platform for log aggregation, cross-service correlation, and AI-powered incident analysis.
Aggregate logs from every service into a single searchable interface. Filter by severity, service, time range, and custom attributes without switching tools.
Trace events across service boundaries. Correlate distributed logs by request ID, user session, or custom identifiers to reconstruct full execution paths.
Use AI to summarize incidents, detect recurring patterns, and accelerate root-cause analysis. Reduce mean-time-to-resolution with intelligent, context-aware diagnostics.
Three stages from raw logs to actionable insight.
Ship logs via structured SDKs or standard protocols. LogRack normalizes and indexes data in real time with no schema configuration required.
Automatic event correlation across services using trace context, request identifiers, and temporal proximity. See connected events without manual stitching.
AI surfaces anomalies, summarizes incident timelines, and suggests root causes. Engineers spend less time reading logs and more time resolving issues.
Built for teams operating production systems at scale.
When production breaks, LogRack surfaces the relevant logs, correlates affected services, and generates an AI summary of what happened and why.
Trace requests across microservices, queues, and async workers. See the full lifecycle of a request without manually grepping across dozens of log streams.
Detect error rate spikes, unusual patterns, and degraded performance before they become incidents. AI-assisted pattern detection flags issues early.
Reconstruct incident timelines with correlated logs, AI-generated summaries, and exportable reports. Build institutional knowledge from every outage.
LogRack gives your engineering team the observability tooling they need to operate production systems without guesswork.
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