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Overview

To ensure the continuous and optimal performance of your Rayls Privacy Ledger, effective monitoring is essential. By tracking key metrics such as CPU usage, memory consumption, and transaction throughput, you can proactively detect and resolve issues before they escalate. This guide provides an introduction to monitoring a Privacy Ledger and will direct you to more detailed instructions in the Rayls Infrastructure section.

Monitoring Tools and Best Practices

The Rayls Privacy Ledger infrastructure supports a variety of monitoring tools and techniques. Below are some best practices for setting up your monitoring environment:

Use Prometheus and Grafana: These tools provide a robust solution for collecting and visualizing metrics from your Privacy Ledger.
Log Management: Extract and analyze logs from Rayls components to detect errors or unusual behavior.
Database Monitoring: MongoDB (used by Privacy Ledgers) and PostgreSQL (used by relayers) offer extensive logging and metrics support for tracking performance and health.

For a comprehensive guide on setting up monitoring and integrating tools like Grafana/Prometheus, please refer to the Rayls Infrastructure section within the Rayls product documentation.

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Key Metrics to Monitor

To maintain the health of your Privacy Ledger, it’s crucial to monitor the following metrics:

CPU and Memory Usage: Ensure that your Privacy Ledger and supporting components are not under- or over-utilized.
Disk Space: Track storage usage, especially for databases like MongoDB, which handles the ledger’s data.
Transaction Throughput: Monitor the number of transactions processed per second to identify bottlenecks or performance issues.
Error Rates: Keep an eye on error logs to catch failed transactions or issues with relayers.

For more detailed information on which metrics to monitor for each component, visit the Rayls Infrastructure section.

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