Better Stack Log Management (Logtail)
Overview
Better Stack Logs (formerly Logtail) provides centralized log management with structured log ingestion, real-time search, and log-based alerting. MSPs use it to aggregate logs from client infrastructure, investigate incidents, and set up proactive alerting on error patterns.
Key Concepts
Log Sources
Sources define where logs come from and how they're ingested:
- Platform sources - AWS, Azure, GCP, Heroku, Vercel, etc.
- Language sources - Node.js, Python, Ruby, Go, etc.
- Infrastructure sources - Docker, Kubernetes, syslog, HTTP
- Each source gets a unique source token for authentication
Log Structure
Logs in Better Stack are structured JSON documents:
dt- Timestamp (ISO 8601)level- Log level (info, warn, error, debug, fatal)message- Log message text- Any additional custom fields (request_id, user_id, service, etc.)
Query Language
Better Stack supports SQL-like queries for log searching:
- Field-based filters:
level:error,service:api - Text search:
"connection refused" - Time ranges:
dt:[2026-03-27T00:00:00Z TO 2026-03-27T23:59:59Z] - Boolean operators:
AND,OR,NOT - Wildcards:
host:prod-*
Log-Based Alerts
Create alerts that trigger when log patterns match:
- Error rate thresholds (e.g., more than 10 errors in 5 minutes)
- Specific error message patterns
- Absence of expected log entries (heartbeat-style)
API Patterns
Query Logs
betterstack_query_logs
Parameters:
query- Search query string (required)source_id- Filter to a specific sourcefrom- Start time (ISO 8601)to- End time (ISO 8601)batch_size- Number of results to return (default 100)order- Sort order:newest_firstoroldest_first
Example response:
{
"data": [
{
"dt": "2026-03-27T10:15:30.123Z",
"level": "error",
"message": "Connection refused to database at 10.0.1.5:5432",
"service": "api-gateway",
"host": "prod-api-01",
"request_id": "req-abc-123"
},
{
"dt": "2026-03-27T10:15:29.456Z",
"level": "error",
"message": "Health check failed for postgres pool",
"service": "api-gateway",
"host": "prod-api-01"
}
]
}
List Log Sources
betterstack_list_sources
Parameters:
page- Pagination cursor
Example response:
{
"data": [
{
"id": "src-789",
"type": "source",
"attributes": {
"name": "Production API",
"platform": "node",
"token": "xxxx...xxxx",
"ingesting_paused": false,
"records_count": 1500000
}
}
]
}
Create Log Source
betterstack_create_source
Parameters:
name- Source name (required)platform- Platform type: node, python, ruby, go, docker, kubernetes, syslog, http, etc.
Common Workflows
Incident Log Investigation
- Get the incident details and identify the affected monitor/service
- Call
betterstack_query_logswith the service name and time range around the incident - Filter for error and fatal level logs
- Look for patterns: connection errors, timeout spikes, OOM events
- Trace request IDs across services for distributed issues
- Summarize findings with root cause analysis
Error Rate Monitoring
- Query logs for
level:errorover the last hour - Group by service to identify which services have elevated errors
- Compare error counts against baseline
- Drill into the highest-error services for specific error messages
- Correlate with uptime monitor incidents
Setting Up Logging for a New Client
- Create log sources for each client service (API, web, workers)
- Distribute source tokens for log ingestion configuration
- Verify logs are flowing with a test query
- Set up log-based alerts for critical error patterns
- Create saved queries for common investigation patterns
Security Log Review
- Search for authentication failures:
"authentication failed" OR "invalid token" OR "unauthorized" - Look for unusual access patterns:
level:warn AND "rate limit" - Check for privilege escalation attempts
- Review admin action logs
- Document findings for compliance reporting
Error Handling
Source Not Found
Cause: Invalid source ID or source was deleted Solution: List sources to verify the correct ID
Query Syntax Error
Cause: Invalid query syntax Solution: Verify query follows the supported syntax (field:value, boolean operators, quotes for phrases)
No Results
Cause: No logs match the query for the given time range Solution: Broaden the time range, check source ID, verify logs are being ingested
Best Practices
- Use structured logging with consistent field names across services
- Include request IDs for distributed tracing across services
- Query with specific time ranges to improve performance
- Use source filters to scope queries to relevant services
- Create saved queries for common investigation patterns
- Set up log-based alerts for critical error patterns
- Rotate source tokens periodically for security
- Use log levels consistently: error for failures, warn for degradation, info for operations
- Include contextual fields (user_id, tenant_id, request_id) for efficient filtering
Related Skills
- api-patterns - Pagination and error handling
- monitors - Monitors correlated with log data
- incidents - Incident investigation with logs
- status-pages - Status context from log analysis