ClickHouse provides SQL-based observability of itself through system tables that continuously write metrics, logs, traces, and other data into these tables. The `system.query_log`, `system.metrics`, `system.asynchronous_insert_log`, and `system.part_log` tables contain relevant information for monitoring asynchronous inserts. Several queries are provided to introspect the execution stages of asynchronous inserts, including part creations, buffer flushes, insert errors during buffer flushes, and pending flushes. These queries can be used to identify root causes of issues with asynchronous insert configurations, such as incorrect flush thresholds or partitioning key usage, and to optimize performance. The queries are parameterized views that can be configured with various parameters to suit specific use cases. By using these queries, developers can gain a deeper understanding of their ClickHouse cluster's behavior and make data-driven decisions to improve its performance.