Skip to main content

Logs Visualization

The logs interface is built on OpenSearch Dashboards with custom enhancements for performance and observability integration.

Logs Interface

Overview​

The logs system uses a custom columnar storage engine that handles high-volume queries without timeouts. The interface includes AI-powered analysis, automatic pattern detection, and direct integration with metrics and traces.

Visual Features​

Severity Indicators​

Each log line displays a color-coded severity bar (INFO, WARN, ERROR, etc.). Hover over the bar to see the severity level.

Log Severity Colors

Log Patterns​

The Patterns tab groups logs by fingerprint similarity. The Insights panel shows pattern frequency and distribution over time.

Patterns Tab

JSON Viewer​

Expand any log row to view all fields in either table or JSON format. The JSON view supports:

  • Expandable/collapsible nested objects
  • Copy buttons for individual fields or entire subtrees
  • Direct filtering from field values

Interactive JSON

AI Features​

AI Assistant Experience​

Select any text in a log entry to interact with the AI Assistant. The context menu provides options to:

  • Ask questions about the log message or error
  • Debug the issue with Cursor integration
  • Get troubleshooting suggestions

Ask AI

This works with any selected text, including error messages, stack traces, or field values.

Log Summaries​

Toggle the AI Summary switch to generate an analysis of the current log view. The summary includes:

  • Total log count, rate, and error percentage
  • Critical issues with severity ratings
  • Error pattern frequency
  • Impact analysis and affected components
  • Root cause identification

AI Summary Analysis

The AI can also accept natural language requests to filter and query logs. Examples:

"Show me all errors from the payment service in the last hour"
"Filter logs where container_name is currency"
"Find logs with status code 500"

AI Assistant Filtering Logs

Log Anomaly Detection​

The system continuously monitors your logs and automatically detects anomalies such as new error patterns, spikes in existing errors, and high-volume recurring issues. Detected anomalies appear on the Anomalies page where you can review them, set up alerts, or block repetitive patterns to reduce noise.

Cross-Signal Navigation​

Click "Explore related metrics and traces" on any log line to open an analysis panel with four tabs:

Explore Related Data

Service Graph: Displays the service and its dependencies.

Service Graph

Trace ID: Shows the distributed trace associated with the log entry, including all spans and timing information.

Trace Details

Metrics: Displays CPU and memory usage for the service at the log timestamp.

Service Metrics

Traces: Lists all traces for the service in the selected time range, filterable by error status or duration.

Traces

The analysis panel automatically filters data to match the service and timeframe of the selected log.

Storage and Performance​

The storage engine uses columnar format optimized for log data:

  • Queries do not timeout regardless of data volume or time range
  • Automatic field indexing without manual schema configuration
  • Efficient compression maintains query speed at scale
  • High ingestion throughput with consistent query performance