This topic describes the functions and features of Database Autonomy Service (DAS).
DAS provides Basic Edition and Professional Edition. Features vary based on the edition type. For more information, see Editions.
Features also vary based on the type of the database engine. For more information, see Supported database engines and features.
Monitoring and alerting
DAS allows you to manage and monitor your on-premises databases and cloud databases in a centralized manner. This can reduce management costs by more than 50%. Errors caused by accidental operations can also be significantly reduced.
DAS allows you to monitor databases on a unified platform. You can monitor the performance trends and real-time performance of all database instances in different clusters and environments.
Cost-effectiveness: DAS helps you monitor databases. This way, you do not need to hire engineers to develop and deploy programs for data collection, computing, and storage.
Various metrics: DAS collects, computes, and then displays a variety of key monitoring metrics that are related to database performance.
Fine-grained monitoring: You can configure fine-grained monitoring to detect anomalies at an interval of seconds based on your business requirements.
DAS allows you to configure alerting on a unified platform. You can create custom alert rules for on-premises databases and cloud databases and configure alert notification methods.
Default alert templates: You can use a variety of default alert templates for different types of database engines. These default templates are developed based on the experience of Alibaba Cloud in database O&M.
Custom configuration: DAS supports custom alert templates. You can configure alert rules, alert contacts, and contact groups based on your business requirements. This way, you can create alert templates for different users in your enterprise.
Alert notification: DAS automatically checks whether alert notifications are configured for all the database instances to which DAS is connected. If you do not configure an alert notification for one of these database instances, DAS sends a notification message to you. This protects your business against threats.
Autonomy service for intelligent diagnosis and optimization
DAS provides 24/7 anomaly detection based on machine learning and fine-grained data monitoring. You can enable a variety of features, such as automatic SQL throttling, anomaly snapshots, automatic SQL review and optimization, automatic storage expansion, and auto scaling of computing resources. These features support a closed-loop diagnostic process. This helps you detect anomalies, analyze root causes, mitigate loss or optimize performance, track effects, and perform roll back operations or add knowledge to the knowledge base. The effect of performance optimization can also be quantified. This way, DAS ensures the service continuity of databases.
DAS supports autonomous scenarios without manual intervention. DAS can also continuously develop self-learning capabilities, such as automatic annotation of anomalies, case system setups, anomaly simulation, and quantitative feedback and assessment. DAS accumulates a large number of cases based on various online business scenarios. These cases help continuously accelerate DAS development and improve the autonomy service. DAS provides the following core autonomous features: 24/7 real-time anomaly detection, fault self-repair, automatic optimization, auto scaling, and intelligent stress testing.
The following figure shows the core DAS concepts and how these concepts are applied throughout the design, R&D, and implementation of the service.
Data-driven detection: DAS collects large amounts of real-time data, such as performance metrics, SQL query logs, and logs of O&M changes. The detection capabilities are developed based on the collected data to help you detect real-time security threats and anomalies in runtime environments.
Automatic decision-making: The deep integration of machine learning and database expert experience allows DAS to automatically make decisions in different business scenarios.
Automatic execution: Tasks are automatically orchestrated and implemented based on decisions that are made by Autonomy Center.
Closed-loop management: A closed-loop process is provided to coordinate operations and manage data in DAS. For example, after an anomaly is detected, DAS makes a global decision based on the result of root cause analysis. DAS analyzes the anomaly and optimizes performance based on the global decision. Then, DAS tracks and evaluates the effects of optimization and provides feedback. DAS also allows you to roll back the operations.
Enterprise-grade database management
DAS supports various monitoring scenarios based on years of database O&M and management experience of the Alibaba Cloud database team. The database instances that DAS monitors may be deployed across clusters and environments. DAS provides multi-module dashboards that you can use to view performance data of all database instances.
Database management across environments or clusters
DAS allows you to monitor database instances across environments or clusters. You can perform aggregation and drill-down on monitoring metrics for a specific cluster or environment. DAS meets the requirements for enterprise-grade database management.
Inspection and scoring
DAS inspects all the database instances to which DAS is connected. The inspected items include basic items, SQL statements, storage, performance, and security. Then, DAS generates a score for each database instance based on the inspection results. The score indicates the health status of a database instance.
DAS provides a wide range of features. In addition, DAS identifies the following items for security: high-risk SQL queries, SQL injections, new access sources, and access to sensitive data. DAS also monitors databases in real time, audits full data, and detects suspicious access to databases and data breaches. This ensures data security.
DAS provides the following features for security audit:
Identify SQL injections
Identify high-risk SQL queries
Identify new access sources