This topic describes the features of the autonomy service (CloudDBA) for MyBase Redis.
Background information
Database Autonomy Service (DAS) is an Alibaba Cloud service that uses machine learning and expert experience to provide database self-perception, self-healing, self-optimization, self-O&M, and self-protection. DAS eliminates complex database management and service failures caused by manual operations. This ensures your database services are stable, secure, and efficient. For more information, see What is Database Autonomy Service (DAS)?.
Feature overview
The autonomy service (CloudDBA) for MyBase Redis includes the following features:
You can view real-time information about large keys and hot keys in an instance. You can also view historical information for large keys and hot keys from the last four days. This feature helps you understand the memory usage and access frequency of keys to support your optimization efforts.
You can analyze Redis backup files to quickly find large keys in an instance. This feature helps you understand key memory usage, distribution, and time-to-live (TTL). You can use this data to support your optimization efforts and avoid issues such as out of memory errors and performance degradation caused by key skew.
You can monitor the basic performance and trends of a Redis instance over a period of time. Metrics include CPU utilization, memory usage, queries per second (QPS), total connections, response time, network traffic, and key hit information.
You can view the real-time performance of a Redis instance. Metrics include CPU utilization, memory usage information, queries per second (QPS), network traffic, server information, key information, client information, and connection information.
You can view real-time session information between a Redis instance and its clients, including client information, executed commands, and connection duration. You can also stop abnormal sessions as needed.
You can view the details of slow query logs to monitor and analyze slow request issues.
You can run diagnostics on the health of an instance for a specified time period. This helps you evaluate the instance health from multiple aspects, such as performance levels, access skew, and slow query logs, to quickly locate instance anomalies.
You can collect latency statistics for all Redis database commands and custom events. The feature provides latency data that is accurate to the microsecond. You can use this feature to troubleshoot Redis database failures and performance degradation.
When the average memory usage reaches a threshold, the specifications of the Redis instance are automatically upgraded. This helps you quickly scale to adapt to business peaks, avoid the risk of out of memory errors, and ensure online service stability.
This feature uses the historical data of an instance from the last 10 days to predict the usage of performance metrics for the next 24 hours. If the predicted metric value is greater than or equal to the target value, a scale-out suggestion is provided.
You can scale up the specifications of a database instance at a scheduled time based on a preset policy. The instance automatically reverts to its original specifications after the specified duration. You can use this feature to handle predictable, periodic changes in database payload, meeting business requirements while controlling costs.