Cloud Logging is a critical component for monitoring and debugging in Google Cloud, and cost optimization is important when using it efficiently. Here are some best practices to help you reduce Cloud Logging costs and optimize queries:

1. Logs Expiration and Retention: Cloud Logging allows you to set the expiration time for logs to control the retention period. By default, logs are kept for 30 days. However, for data governance purposes or to comply with industry regulations, you may need to maintain logs for a more extended period. In such cases, you may set a longer retention time, or you may export the logs to cheaper long-term storage options such as Google Cloud Storage.
   ‍
2. Log Filtering: Using log filters is an effective way to reduce Cloud Logging costs. Filters help you narrow down the logs that need to be processed, so you only pay for what you need. You can use advanced queries to filter logs based on resource type, severity level, or custom labels. The more filters you use, the more specific the log data you collect, which can significantly reduce logging costs.
   ‍
3. Log Export to Different Destinations: Cloud Logging allows you to export logs to various destinations such as Google Cloud Storage, BigQuery, and Pub/Sub. If you only need to store logs for future reference or compliance purposes, exporting logs to Google Cloud Storage may be a more cost-effective option. In contrast, exporting logs to BigQuery allows you to analyze log data in real-time.
   ‍
4. Use log-based Metrics: You can create custom metrics from logs to help you analyze and monitor your system's behavior. Log-based metrics are computed based on the log data, which means that you only pay for the logs processed to generate the metrics. This is a cost-effective way to gain insight into your system's performance and behavior.
   ‍
5. Log-based Alerts: Use log-based alerts to monitor logs for specific events and patterns. Log-based alerts trigger notifications when specific log entries meet certain conditions. By setting up alerts, you can avoid excessive logging, reduce logging costs, and focus only on critical events.
   ‍
6. Use Labels to Group Log Entries: Assigning labels to your logs can help you group them based on a specific attribute, such as project, environment, or application. This allows you to filter logs by label, reducing the number of logs processed and ultimately reducing logging costs.
   ‍
7. Disable Log Exports for Non-Essential Logs: If you have enabled log exports to destinations such as BigQuery or Pub/Sub, make sure that you only export logs that are essential for your use case. Exporting non-essential logs increases logging costs without providing any significant value.
   ‍
8. Use Log Views: Log Views allow you to create a customized view of your logs, displaying only the log entries that meet specific criteria. This can help reduce logging costs by filtering out unnecessary logs.
   ‍

Remember that cost optimization is an ongoing process, and you should continually monitor and adjust your usage to ensure that you are getting the most value for your investment in Cloud Logging.