Performance anomaly detection - Database Autonomy Service

Database Autonomy Service (DAS) uses machine learning and intelligent algorithms to monitor and predict the anomalies in the core metrics of database instances. DAS also provides the one-click diagnostics feature to help you identify root causes.

Prerequisites

Your database instance must meet the following requirements:

Your database instance is an ApsaraDB RDS for MySQL instance.
The database instance is connected to DAS and is in the Normal Access state. For more information, see Connect an Alibaba Cloud database instance to DAS.

Procedure

Log on to the DAS console.
In the left-side navigation pane, click Instance Monitoring.
On the page that appears, find the database instance that you want to manage and click the instance ID. The instance details page appears.
In the left-side navigation pane, click Dashboard. On the page that appears, click the Exception Detection tab.
On the Exception Detection tab, specify a time range to view the detection and prediction results of metrics within the specified time range.
Note
When you select a time range, the end time must be later than the start time, and the interval between the start time and the end time cannot exceed seven days.
- Click More Metrics and specify metrics that need to be detected and predicted. For more information about metrics, see the Metrics section of this topic.
- In the Exception Information section, click Diagnose in the Diagnose column of a metric. In the Diagnostic Tree dialog box, view the overall performance of the database instance and figure out the cause of the exception.

Metrics

DAS supports the following metrics for anomaly detection.

Metric	Description
tps	The transactions per second (TPS).
qps	The queries per second (QPS).
active_session	The number of active sessions.
delete_ps	The average number of DELETE statements that are executed per second.
insert_ps	The average number of INSERT statements that are executed per second.
update_ps	The average number of UPDATE statements that are executed per second.
select_ps	The average number of SELECT statements that are executed per second.
bytes_received	The average number of bytes that are received from all clients per second
bytes_sent	The average number of bytes that are sent to all clients per second
innodb_bp_hit	The read hit ratio of the InnoDB buffer pool.
innodb_data_written	The average number of bytes that are written to the InnoDB table per second.
innodb_data_read	The average number of bytes that are read from the InnoDB table per second.
mysql.innodb_log_writes	The average number of physical writes to the InnoDB redo log file per second.
innodb_rows_deleted	The average number of rows that are deleted from the InnoDB table per second.
innodb_rows_read	The average number of rows that are read from the InnoDB table per second.
innodb_rows_inserted	The average number of rows that are inserted into the InnoDB table per second.
innodb_rows_updated	The average number of rows that are updated in the InnoDB table per second.
mysql.mem_usage	The memory usage of the ApsaraDB RDS for MySQL instance in the entire operating system.
mysql.cpu_usage	The CPU utilization of MySQL processes. The maximum value of this metric is 100% for Alibaba Cloud database instances.