Database Autonomy Service (DAS) allows you to view the performance trends of database instances based on a wide spectrum of performance metrics and customize charts. DAS can promptly detect events generated by instances, perform automatic diagnostics on the events, and offer root cause analysis and suggestions. DAS also allows you to specify a time range and manually perform diagnostics on instances in the specified time range. DAS provides powerful diagnostic capabilities to help you understand the health status of your instances.
A database instance is connected to DAS and is in the Accessed state.
You can view the performance trend in a specified time range.
- Log on to the DAS console.
- In the left-side navigation pane, click Instance Monitoring.
- On the page that appears, click the ID of the database instance that you want to manage. The instance details page appears.
- In the left-side navigation pane, click Dashboard.
- On the Performance Trends tab, view the charts for performance trends in a specified time range based on the
- Click More Metrics and select the metrics that you want to view.
- On a performance chart, drag-select a time range and click Diagnose to view diagnostic reports within the time range.
- You can click Details in the trend chart of a metric to zoom in the trend chart. In this case, you can change the time range to view the trend of the metric over the specified time range.
- Select the level of events that you want to view. When the system detects events at
the specified level, the system displays the events in the MySQL CPU Utilization/Memory Usage and Session charts.
Click the color block corresponding to the events at the specified level in the trend chart to view the diagnostic results in the event details.
- On the Performance Trend Comparison tab, view the comparison of performance trends in a specified time range based on
Click More Metrics and select the metrics that you want to view.
- On the Custom Chart tab, you can create dashboards to display the performance metrics that you want to
view. When you create a chart, you can specify multiple performance metrics that you
want the chart to display. This way, you can analyze metrics that are displayed on
the dashboards and troubleshoot performance issues.
Note You must create dashboards before you create charts. For more information, see Monitoring dashboards.
- On the Exception Detection tab, view the results of exception detection and prediction for core metrics. For
more information, see Performance anomaly detection.
Click More Metrics and select the metrics on which you want to perform exception detection.
- On the Instance Topology tab, view the topology of the instance.
- On the Performance Trends tab, view the charts for performance trends in a specified time range based on the metrics.
You can view the following metrics for performance trends. An ApsaraDB RDS for MySQL instance is used in this example.
|mysql.tps||Per Second||The number of transactions that are run on the data node per second.|
|mysql.qps||Per Second||The number of queries per second (QPS).|
|mysql.total_session||Count||The total number of sessions.|
|mysql.active_session||Count||The number of active sessions.|
|mysql.bytes_received||KByte||The average number of bytes in the data that is received from all clients per second.|
|mysql.bytes_sent||KByte||The average number of bytes in the data that is sent to all clients per second.|
|mysql.tb.tmp.disk||Count||The number of temporary tables that are automatically created on the disk when MySQL executes statements.|
|mysql.insert_select||Per Second||The average number of INSERT SELECT statements that are executed per second.|
|mysql.insert_ps||Per Second||The average number of INSERT statements that are executed per second.|
|mysql.select_ps||Per Second||The average number of SELECT statements that are executed per second.|
|mysql.replace_select||Per Second||The average number of REPLACE SELECT statements that are executed per second.|
|mysql.update_ps||Per Second||The average number of UPDATE statements that are executed per second.|
|mysql.delete_ps||Per Second||The average number of DELETE statements that are executed per second.|
|mysql.replace_ps||Per Second||The average number of REPLACE statements that are executed per second.|
|mysql.innodb_data_fsyncs||Count||The average number of fsync() executions per second.|
|mysql.open_files||Count||The number of opened files.|
|mysql.innodb_data_written||KByte||The average number of bytes in the data that is written to InnoDB per second.|
|mysql.innodb_data_read||KByte||The average number of bytes in the data that is read from InnoDB per second.|
|mysql.innodb_buffer_pool_reads_requests||Count||The average number of logical page reads from the InnoDB buffer pool per second.|
|mysql.innodb_buffer_pool_write_requests||Count||The average number of page writes to the InnoDB buffer pool per second.|
|mysql.innodb_bp_dirty_pct||%||The ratio of dirty pages in the InnoDB buffer pool. Calculation formula: Innodb_buffer_pool_pages_dirty/Innodb_buffer_pool_pages_data × 100%.|
|mysql.innodb_bp_hit||%||The read hit ratio of the InnoDB buffer pool. Calculation formula: (Innodb_buffer_pool_read_requests - Innodb_buffer_pool_reads)/Innodb_buffer_pool_read_requests × 100%.|
|mysql.innodb_bp_usage_pct||%||The utilization of the InnoDB buffer pool. Calculation formula: Innodb_buffer_pool_pages_data/(Innodb_buffer_pool_pages_data + innodb_buffer_pool_pages_free) × 100%.|
|mysql.innodb_log_writes||Per Second||The average number of physical writes to the InnoDB redo log file per second.|
|mysql.innodb_os_log_fsyncs||Per Second||The average number of fsync() writes to the log file per second.|
|mysql.innodb_rows_deleted||Per Second||The average number of InnoDB rows from which data is deleted per second.|
|mysql.innodb_rows_read||Per Second||The average number of InnoDB rows from which data is read per second.|
|mysql.innodb_rows_inserted||Per Second||The average number of InnoDB rows into which data is inserted per second.|
|mysql.innodb_rows_updated||Per Second||The average number of InnoDB rows in which data is updated per second.|
|mysql.mem_usage||%||The memory usage of the MySQL instance in the entire operating system.|
|mysql.cpu_usage||%||The CPU utilization of MySQL processes. This metric can reach up to 100% for Alibaba Cloud database instances.|
|mysql.innodb_buffer_pool_pages_flushed||Count||The number of buffer pool flushing requests.|
|mysql.innodb_row_lock_time||ms||The longest row lock wait of tables.|
|mysql.innodb_row_lock_time_avg||ms||The average row lock wait of tables.|
|mysql.innodb_row_lock_waits||Count||The average number of row lock waits of a table.|
|mysql.data.size||MByte||The size of the data space.|
|mysql.tmp.size||MByte||The temporary tablespace.|
|mysql.other.size||MByte||The system space.|
|mysql.instance.size||MByte||The total used space of the MySQL instance.|
|mysql.log.size||MByte||The size of the log space.|
|mysql.iops||Count||The IOPS of the MySQL instance.|
|mysql.iops_usage||%||The IOPS usage.|