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Let's dive deeper into how to effectively monitor and manage your Databricks resource usage. One of the first things you should do is familiarize yourself with the Databricks usage dashboards. These dashboards provide detailed insights into your compute, storage, and other resource consumption. Use these dashboards to track your usage against the free tier limits and identify areas where you can optimize your resource consumption. Set up alerts and notifications. Databricks allows you to set up alerts and notifications to be informed when your resource usage exceeds a certain threshold. This can help you prevent unexpected costs and ensure you stay within the free tier limits. Regularly review your cluster configuration. Make sure you're using the smallest instance type that meets your needs. Review the cluster settings and shut down idle clusters when they are not in use. Review your data storage. If you're working with large datasets, consider using cloud storage services like AWS S3, Azure Blob Storage, or Google Cloud Storage. Monitor your storage consumption to avoid exceeding the free tier limits. Review your code for efficiency. Optimize your data processing scripts to minimize the amount of compute power and time needed. Write clean, well-documented code and use optimized libraries like Apache Spark. By taking these proactive measures, you can stay on top of your resource consumption and avoid unwanted charges. These practices are crucial for sustainable free usage.
* `api`: Specifies the minimum Figma API version your plugin is compatible with. This ensures your plugin works correctly with the Figma version your users are running.
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