Summary: Dapr supports PostgreSQL as a configuration store component of type configuration.postgresql with a stable v1 API since version 1.11 of the Dapr runtime. This allows storing key-value pairs and reacting to changes through database notifications.
Component configuration: To integrate PostgreSQL as a configuration store in Dapr, a component manifest with essential metadata must be created. Key options include connectionString, which specifies the standard PostgreSQL connection string and allows pool parameters, and table, which defines the name of the table that will contain the configuration entries. Recommended tuning options: timeout for operation timeouts, maxConns for connection pool size, connectionMaxIdleTime for maximum connection idle time, and queryExecMode for compatibility with proxies such as PgBouncer.
Database schema: The required table must include at least the columns KEY of type VARCHAR not null, VALUE of type VARCHAR not null, VERSION of type VARCHAR not null, and optional METADATA of type JSON for additional metadata. The table name must match the value configured in the table metadata of the Dapr component.
Notifications and trigger: To enable subscriptions to changes, it is recommended to create a trigger function that emits notifications using pg_notify on a specific channel, for example config. The trigger must run after insert, update, and delete on the configuration table and send a JSON payload that includes the table name, the action, and the affected data. Dapr will use the same channel name specified in the pgNotifyChannel metadata when creating the subscription.
Integration with the Dapr configuration API: Dapr exposes REST APIs to work with the configuration store. Retrieving configuration is done via a GET request to the local Dapr endpoint, specifying the Dapr port, the store name, and the key being searched. To subscribe to changes, a GET request is made to the subscribe endpoint, including pgNotifyChannel metadata with the PostgreSQL channel name. To cancel the subscription, the unsubscribe endpoint is used with the subscription identifier previously returned.
Best practices: Keep pool parameters adjusted to the load using maxConns and connectionMaxIdleTime, use reasonable timeouts, and configure queryExecMode simple_protocol when using connection proxies. Ensure proper indexes on the KEY column for efficient reads and consistent versioning in VERSION to avoid race conditions.
Advantages: Using PostgreSQL with Dapr allows centralizing configuration, enabling real-time notifications for microservices, and leveraging PostgreSQL's reliability and advanced features. This solution is ideal for environments that require fine-grained control over configuration data access, auditing, and compatibility with cloud infrastructures.
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