Query Examples

This guide provides practical examples for common log analytics scenarios using LogChef. Each example includes both the LogchefQL syntax and the equivalent SQL query.

Error Analysis

Finding All Errors

Find all errors across all services to get an overview of system health.

level="error"

SQL Equivalent

SELECT *
FROM logs.app
WHERE level = 'error'
ORDER BY timestamp DESC
LIMIT 100

Service-specific Errors

Narrow down errors to a specific service when troubleshooting issues in that component.

level="error" and service="payment-api"

SQL Equivalent

SELECT *
FROM logs.app
WHERE level = 'error'
  AND service = 'payment-api'
ORDER BY timestamp DESC
LIMIT 100

Errors Excluding Debug Noise

Find errors while excluding specific patterns that aren’t relevant.

level="error" and message!~"health check"

SQL Equivalent

SELECT *
FROM logs.app
WHERE level = 'error'
  AND positionCaseInsensitive(message, 'health check') = 0
ORDER BY timestamp DESC
LIMIT 100

Critical vs Warning Analysis

Compare different severity levels.

severity_number>=4 or level="critical"

SQL Equivalent

SELECT *
FROM logs.app
WHERE severity_number >= 4
   OR level = 'critical'
ORDER BY timestamp DESC
LIMIT 100

HTTP Logs Analysis

Server Errors (5xx Status Codes)

Identify all server-side errors to find potential backend issues.

status>=500

SQL Equivalent

SELECT *
FROM logs.app
WHERE status >= 500
ORDER BY timestamp DESC
LIMIT 100

Slow API Requests

Find API requests that took longer than 1 second to complete, which may indicate performance bottlenecks.

request_path~"/api/" and response_time>1000

SQL Equivalent

SELECT *
FROM logs.app
WHERE positionCaseInsensitive(request_path, '/api/') > 0
  AND response_time > 1000
ORDER BY timestamp DESC
LIMIT 100

Client Errors for a Specific Endpoint

Find client errors (4xx) for a specific API endpoint to identify potential client integration issues.

status>=400 and status<500 and request_path~"/api/payments"

SQL Equivalent

SELECT *
FROM logs.app
WHERE status >= 400
  AND status < 500
  AND positionCaseInsensitive(request_path, '/api/payments') > 0
ORDER BY timestamp DESC
LIMIT 100

Request Latency Analysis

Find requests within specific latency ranges.

# Very slow requests (over 5 seconds)
response_time>5000

# Fast requests (under 100ms)
response_time<100

# Requests in a specific range
response_time>=100 and response_time<=500

Nested Field Queries

LogchefQL supports querying nested fields in Map and JSON columns using dot notation.

Map Column Access

Query logs by attributes stored in Map columns (common in OpenTelemetry logs).

# Filter by user ID in attributes
log_attributes.user_id="user-12345"

SQL Equivalent

SELECT *
FROM logs.app
WHERE log_attributes['user_id'] = 'user-12345'
ORDER BY timestamp DESC
LIMIT 100

Multi-level Nesting

Access deeply nested fields.

# Query nested request attributes
log_attributes.http.request.method="POST"

# Query nested error details
log_attributes.error.code="CONNECTION_REFUSED"

SQL Equivalent

SELECT *
FROM logs.app
WHERE log_attributes['http.request.method'] = 'POST'
ORDER BY timestamp DESC
LIMIT 100

Pattern Matching in Nested Fields

Use contains operator on nested values.

log_attributes.request.url~"/api/v2/"

SQL Equivalent

SELECT *
FROM logs.app
WHERE positionCaseInsensitive(log_attributes['request.url'], '/api/v2/') > 0
ORDER BY timestamp DESC
LIMIT 100

JSON Column Extraction

For JSON or String columns containing JSON, LogchefQL uses JSONExtractString.

body.request.user_agent~"Mozilla"

SQL Equivalent

SELECT *
FROM logs.app
WHERE positionCaseInsensitive(JSONExtractString(body, 'request', 'user_agent'), 'Mozilla') > 0
ORDER BY timestamp DESC
LIMIT 100

Quoted Field Names

For field names containing dots or special characters.

# Field name literally contains a dot
log_attributes."service.name"="payment-api"

# Mixed quoted and unquoted
log_attributes."nested.key".subfield="value"

Using the Pipe Operator

The pipe operator (|) lets you select specific columns instead of SELECT *.

Basic Column Selection

Select only the fields you need.

level="error" | timestamp service level message

SQL Equivalent

SELECT timestamp, service, level, message
FROM logs.app
WHERE level = 'error'
ORDER BY timestamp DESC
LIMIT 100

Extracting Nested Values

Pull specific values from nested structures.

namespace="prod" | timestamp log_attributes.user_id log_attributes.request_id body

SQL Equivalent

SELECT
  timestamp,
  log_attributes['user_id'] AS log_attributes_user_id,
  log_attributes['request_id'] AS log_attributes_request_id,
  body
FROM logs.app
WHERE namespace = 'prod'
ORDER BY timestamp DESC
LIMIT 100

Minimal Output for Scanning

When you just need to scan for specific patterns.

message~"error" | timestamp message

Service Overview

Get a quick view of service activity.

namespace="production" | timestamp service_name level

Security Analysis

Failed Authentication Attempts

Identify potential brute force attacks by finding multiple failed login attempts.

event="login_failed" and ip_address~"192.168."

SQL Equivalent

SELECT *
FROM logs.app
WHERE event = 'login_failed'
  AND positionCaseInsensitive(ip_address, '192.168.') > 0
ORDER BY timestamp DESC
LIMIT 100

Suspicious Activity Detection

Find logs that might indicate suspicious activities based on warning messages.

level="warn" and (message~"suspicious" or message~"unauthorized")

SQL Equivalent

SELECT *
FROM logs.app
WHERE level = 'warn'
  AND (
    positionCaseInsensitive(message, 'suspicious') > 0
    OR positionCaseInsensitive(message, 'unauthorized') > 0
  )
ORDER BY timestamp DESC
LIMIT 100

Access Pattern Analysis

Track access to sensitive endpoints.

request_path~"/admin" or request_path~"/api/internal"

System Monitoring

High Resource Usage

Detect potential resource bottlenecks by finding instances of high CPU or memory usage.

type="system_metrics" and (cpu_usage>90 or memory_usage>85)

SQL Equivalent

SELECT *
FROM logs.app
WHERE type = 'system_metrics'
  AND (cpu_usage > 90 OR memory_usage > 85)
ORDER BY timestamp DESC
LIMIT 100

Failed Service Health Checks

Monitor service health by finding instances where health checks have failed.

event="health_check" and status!="ok"

SQL Equivalent

SELECT *
FROM logs.app
WHERE event = 'health_check'
  AND status != 'ok'
ORDER BY timestamp DESC
LIMIT 100

Disk Space Warnings

Identify servers that are running low on disk space and might need attention.

type="system_metrics" and disk_free_percent<15

SQL Equivalent

SELECT *
FROM logs.app
WHERE type = 'system_metrics'
  AND disk_free_percent < 15
ORDER BY timestamp DESC
LIMIT 100

Distributed Tracing

Complete Request Trace

Trace a complete request flow across multiple services using a trace ID.

trace_id="abc123def456"

SQL Equivalent

SELECT *
FROM logs.app
WHERE trace_id = 'abc123def456'
ORDER BY timestamp ASC
LIMIT 1000

Service Dependency Analysis

Find all the services involved in a specific transaction to understand service dependencies.

trace_id="abc123def456" and level="info" and event="service_call"

SQL Equivalent

SELECT service, remote_service, timestamp
FROM logs.app
WHERE trace_id = 'abc123def456'
  AND level = 'info'
  AND event = 'service_call'
ORDER BY timestamp ASC
LIMIT 100

Trace with Specific Fields

Get a focused view of a trace with only relevant fields.

trace_id="abc123def456" | timestamp service_name span_id body

OpenTelemetry Log Queries

LogchefQL works great with OpenTelemetry log data.

Filter by Resource Attributes

log_attributes.service.name="frontend" and severity_text="ERROR"

Kubernetes Context

log_attributes.k8s.namespace.name="production" and log_attributes.k8s.pod.name~"api-"

Span Correlation

trace_id!="" and span_id!="" and level="error"

Effective Query Tips

1. Start Specific, Then Broaden

   • Begin with specific conditions that target your issue
   • Add or remove filters to adjust the result set size

2. Use Comparison Operators for Metrics

   • response_time>1000 is cleaner than text matching
   • Works well with numeric fields like status codes, durations, counts

3. Leverage Nested Field Access

   • Query Map and JSON columns directly: log_attributes.user_id="123"
   • No need to flatten your log schema

4. Use the Pipe Operator for Focus

   • level="error" | timestamp service message reduces noise
   • Faster queries when you don’t need all columns

5. Combine Multiple Conditions

   • Use and to narrow results
   • Use or to broaden results
   • Use parentheses for complex conditions: (condition1 or condition2) and condition3

6. Filter by Context First

   • Start with service, component, or environment
   • Then add conditions for errors, warnings, or specific events
   • Finally, add free-text search terms with the ~ operator

7. Switch to SQL Mode for Aggregations

   • LogchefQL is for filtering; use SQL mode for COUNT, GROUP BY, etc.