Design a Scalable Logging Service

Functional Requirements

1. Log Collection:

   • The service should be able to collect logs from various sources, including applications, servers, and devices.
   • Support for multiple log formats (e.g., JSON, plain text).
   • Real-time log ingestion to ensure minimal delay in log collection.

2. Log Storage:

   • Efficient storage of logs to handle large volumes of data.
   • Support for both structured and unstructured log data.
   • Ability to archive older logs for long-term storage.

3. Log Retrieval and Querying:

   • Provide a robust querying mechanism to search and filter logs based on various parameters (e.g., timestamp, log level, source).
   • Support for complex queries and aggregations.
   • Real-time log retrieval to facilitate quick analysis.

4. Log Analysis and Monitoring:

   • Integration with analytics tools to provide insights and trends from log data.
   • Support for setting up alerts based on specific log patterns or thresholds.

5. Access Control:

   • Implement role-based access control to ensure only authorized users can access or modify logs.
   • Audit logging to track access and changes to log data.

6. Scalability:

   • The system should be able to scale horizontally to handle increasing log volumes and sources.

7. Integration:

   • Provide APIs or SDKs for easy integration with existing systems and applications.

Non-Functional Requirements

1. Performance:

   • Low latency in log ingestion and retrieval.
   • High throughput to handle a large number of log entries per second.

2. Reliability:

   • Ensure high availability of the logging service with minimal downtime.
   • Implement redundancy and failover mechanisms to prevent data loss.

3. Scalability:

   • Ability to scale seamlessly with increasing data volume and user load.

4. Security:

   • Ensure data encryption both at rest and in transit.
   • Implement strong authentication and authorization mechanisms.

5. Data Consistency:

   • Ensure eventual consistency in log data across distributed systems.

6. Cost Efficiency:

   • Optimize storage and processing costs while maintaining performance.

7. Extensibility:

   • Design the system to easily accommodate new features and integrations in the future.