Grafana Loki 2.7.4

• Scalable, horizontally distributed architecture
• PromQL-style filtering language for log data
• Integration with Grafana for data visualization and alerting
• Ability to handle high volumes of logs with low storage requirements
• Flexible deployment options, including Kubernetes and Docker containers
• Multi-tenancy support for secure data access

• Log aggregation: Loki can collect and store logs from multiple sources, allowing for centralized log management and analysis.
• Troubleshooting and debugging: With Loki, you can easily search and filter through logs to find the root cause of issues and errors in your system.

To use Loki, you can follow these general steps:

1. Deploy and configure Loki in your environment, either as a standalone service or as a component of a larger system like Kubernetes.
2. Ingest logs from your applications or infrastructure into Loki using one of its supported integrations or APIs.
3. Use the PromQL-style query language to search and filter through your log data.
4. Visualize and an

• Written in Go programming language
• Uses the same data model and query language as Prometheus
• Supports log data storage in object stores like AWS S3 and Google Cloud Storage
• Can be deployed on Kubernetes using the Helm chart or through Docker containers
• Supports authentication and authorization through integration with external authentication providers.