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20 Best Practices for Monitoring and Visualizing Loki Logs in Grafana

1. Centralize Log Aggregation​

  • Ensure all application, infrastructure, and service logs are sent to Loki. Use Promtail, Fluentd, or Fluent Bit as log shippers to collect logs from various sources.

2. Structure Logs with Labels​

  • Use key-value pairs in labels to efficiently group and filter logs (e.g., app=nginx, env=production).
  • Avoid excessive labels to prevent high cardinality issues.

3. Avoid High-Cardinality Labels​

  • Avoid using dynamic or high-cardinality data (like request_id or timestamp) in labels. Use log content or metadata for such data instead. Here are 10 examples of high-cardinality labels that can negatively impact performance in Loki:
High Cardinality Label Examples

  1. request_id

    • A unique identifier for each request or transaction.
    • Example: request_id="abc123-def456-ghi789"

  2. timestamp

    • Timestamps as labels can create unique values for every log line.
    • Example: timestamp="2025-01-22T12:00:01Z"

  3. user_id

    • Unique identifiers for individual users.
    • Example: user_id="user_12345"

  4. session_id

    • Session identifiers, often regenerated for every user session.
    • Example: session_id="sess-6789abcd"

  5. ip_address

    • IP addresses for requests or users accessing a service.
    • Example: ip_address="192.168.1.1"

  6. url

    • Full URLs with query parameters, which vary widely for different requests.
    • Example: url="https://example.com/api?query=xyz"

  7. file_path

    • Dynamic file paths for logs related to specific files.
    • Example: file_path="/var/log/app/instance123/logfile.log"

  8. container_id

    • Unique container identifiers in Kubernetes or Docker environments.
    • Example: container_id="a1b2c3d4e5f6"

  9. query_param

    • Query parameters that are highly variable.
    • Example: query_param="search=example&sort=asc"

  10. stacktrace

    • Exception stack traces, which can differ significantly across logs.
    • Example: stacktrace="java.lang.Exception: Error at line 42"

4. Use Log Streams​

  • Leverage log streams to organize logs by labels such as app, namespace, or cluster. For example: 
    {app="nginx", namespace="prod"}

5. Query Efficiently​

  • Use the right queries to filter logs effectively. Start with broad queries and then narrow down using conditions: 
    {app="nginx"} |= "error"

6. Use Parsers for Log Formats​

  • Use Loki’s parsers to handle structured logs like JSON or log formats such as Apache and Nginx logs: 
    {app="nginx"} | json

7. Utilize Metrics from Logs​

  • Use LogQL functions to extract metrics from logs, such as counting error occurrences: 
    rate({app="nginx"} |= "error" [5m])

8. Normalize Timestamps​

  • Ensure timestamps in logs are synchronized across sources to avoid skewed log ordering. Use NTP or other time-sync mechanisms.

9. Visualize Logs with Panels​

  • Use Grafana’s Log Panel for raw logs and Graph Panel for aggregated metrics derived from logs.

10. Define Alerts on Log Metrics​

  • Create alert rules for logs to detect anomalies or patterns. For example, alert if 5xx errors exceed a threshold: 
    rate({status=~"5.*"}[5m]) > 10

11. Compress and Retain Logs Efficiently​

  • Configure Loki’s compactor to optimize log storage and ensure logs are retained only for the required period.

12. Tag Logs for Critical Context​

  • Enrich logs with critical metadata such as environment, region, and deployment versions.

13. Use Dashboards for Quick Insights​

  • Build Grafana dashboards for common scenarios like error analysis, HTTP status distribution, or latency spikes.

14. Monitor Loki Performance​

  • Use Grafana dashboards to monitor Loki’s resource usage (e.g., disk, memory, and CPU).

15. Implement RBAC for Logs​

  • Restrict access to logs by setting up Role-Based Access Control (RBAC) in Loki, ensuring that only authorized users can view sensitive logs.

16. Regularly Backup Logs​

  • Configure a backup strategy to store logs in external storage, such as AWS S3 or GCS, for disaster recovery.
  • Group related log streams by combining queries with or conditions. For instance: 
    {app="nginx"} or {app="backend"}

18. Use Loki Query Builder​

  • Leverage Grafana’s Loki Query Builder for crafting LogQL queries interactively, especially for complex queries.

19. Set Up Alerts for Missing Logs​

  • Monitor for missing logs (e.g., if a service stops sending logs): 
    absent({app="nginx"} | rate(1m))

20. Test Queries with Real Data​

  • Test LogQL queries with real data from your system to validate accuracy and efficiency.