This guide covers various methods to access and analyze R2R logs, as well as leverage R2R’s powerful analytics and observability features. These capabilities allow you to monitor system performance, track usage patterns, and gain valuable insights into your RAG application’s behavior.
If you’re running R2R using Docker:
List running containers:
View real-time logs:
Using Docker Compose:
For local deployments without Docker:
The features described in this section are typically restricted to superusers. Ensure you have the necessary permissions before attempting to access these features.
You can fetch logs using the client-server architecture:
Expected Output:
R2R offers an analytics feature for aggregating and analyzing log data:
Expected Output:
You can specify different filters and analysis types to focus on specific aspects of your application’s performance:
To get meaningful analytics, you can preload your database with random searches:
To get analytics for a specific user:
grep
, awk
, or sed
to filter logs.less
with search functionality.Consider using log aggregation tools for more advanced setups:
R2R’s logging, analytics, and observability features provide powerful tools for understanding and optimizing your RAG application. By leveraging these capabilities, you can:
Remember to rotate logs regularly and set up log retention policies to manage disk space, especially in production environments.
For more advanced usage and customization options, consider joining the R2R Discord community or referring to the detailed R2R documentation.
This guide covers various methods to access and analyze R2R logs, as well as leverage R2R’s powerful analytics and observability features. These capabilities allow you to monitor system performance, track usage patterns, and gain valuable insights into your RAG application’s behavior.
If you’re running R2R using Docker:
List running containers:
View real-time logs:
Using Docker Compose:
For local deployments without Docker:
The features described in this section are typically restricted to superusers. Ensure you have the necessary permissions before attempting to access these features.
You can fetch logs using the client-server architecture:
Expected Output:
R2R offers an analytics feature for aggregating and analyzing log data:
Expected Output:
You can specify different filters and analysis types to focus on specific aspects of your application’s performance:
To get meaningful analytics, you can preload your database with random searches:
To get analytics for a specific user:
grep
, awk
, or sed
to filter logs.less
with search functionality.Consider using log aggregation tools for more advanced setups:
R2R’s logging, analytics, and observability features provide powerful tools for understanding and optimizing your RAG application. By leveraging these capabilities, you can:
Remember to rotate logs regularly and set up log retention policies to manage disk space, especially in production environments.
For more advanced usage and customization options, consider joining the R2R Discord community or referring to the detailed R2R documentation.