Monitoring integrated databases in Watson Query

Procedure

To monitor integrated databases, follow these steps.

1. On the navigation menu, click Data > Data virtualization

   The service menu opens to the Data sources page by default.

2. Click Monitor dashboard > Summary to get an overview of the Watson Query service health, based on the following metrics:

   Metric	Description
   Availability	Indicates whether the service is up or down and the history of availability.
   Responsiveness	Indicates whether the system is responding well to the incoming requests.
   Throughput	Indicates how much workload the system is handling.
   Resource usage	Indicates the resource usage of the service in terms of CPU, memory, storage, and log space.
   Time spent	Indicates the percentage of time that is taken for service calls.
   Contention	Indicates that the number of lock waits in the last hour and the number of concurrent connections.

3. Click Monitor dashboard > Alerts to access the Notification center.

   You can view and filter alerts for Watson Query. To set up custom alerts, see 10.

4. Click Monitor dashboard > Database to get performance data about your database based on the following metrics

   Menu option	Description
   Database time spent	Indicates the percentage of time that is taken for database calls.
   Database usage	Indicates the resource usage of the database in terms of CPU, memory, storage, and log space.

5. Click Monitor dashboard > Statement to get performance data about queries executed in Watson Query, based on the following metrics:

   Menu option	Description
   In-flight executions	See a list of the SQL statements that are currently running or that ran recently on Watson Query. You can use these metrics to identify costly or long running statements. You can cancel individual statements or disconnect a user or application when the statement needs to be stopped.
   Individual executions	Displays the details of running SQL statements as system activity.
   Package cache	See information about statements that previously ran on Watson Query. For example, you can see the number of executions and the total amount of CPU used for these executions. You can use these metrics to identify statements that use a disproportionate amount of system resources.
   Stored procedures	Displays the aggregated execution metrics for procedures, external procedures, compiled functions, external functions, compiled triggers, and anonymous blocks invoked since the service was activated in Db2 Data Management Console.

6. Click Monitor dashboard > Applications to get an overview of the service usage, based on the following metrics:

   Option	Description
   Top consumers	Displays the top consumers of the system resources.
   Connections	See the different users or applications that have open connections to the service. A user or application can open multiple connections. You can use these metrics to find the source of disruptive behavior.

7. Click Monitor dashboard > Throughput to get an overview of query performance, based on the following metrics:

   Option	Description
   Connection summary	Displays a summary of all connections established to the console.
   Partition summary	Displays the information for each data partition used by Watson Query.
   WLM workload summary	Represents the accumulation of all metrics for requests that were submitted by connections, and were mapped to the identified workload objects. This metric is based on Workload Manager.
   WLM service class summary	Represents the accumulation of all metrics for requests that have executed under the indicated service subclass.

8. Click Monitor dashboard > I/O to get an overview of input/output for each data partition, based on the following metric:

   Option	Description
   Buffer pools	Watson Query uses the Db2 buffer pools to store cached data and to improve service performance. Adequate buffer pool size is essential for good service performance because it reduces the disk I/O, which uses a considerable amount of time.
   Prefetchers	Watson Query uses Db2 prefetching to retrieve one or more pages from disk in the expectation that they will be required by an application. You can monitor prefetch ratios, wait time, asynchronous reads per minute, and more. Prefetching index and data pages into the buffer pool can help to improve performance by reducing I/O wait times. In addition, parallel I/O enhances prefetching efficiency.
   Logging performance	You can monitor logging statistics for each database.

9. Click Monitor dashboard > Storage to get an overview of storage, based on the following metrics:

   Option	Description
   Table performance	You can use this page to see performance data for each table or each schema.
   Storage	You can use this page to see storage data for each table or each schema.
   Table space performance	You can use this page to see performance data for each table space.

10. Click Settings to get information about the following profiles:

    Required role: To access these profiles, you must have the Watson Query Admin role.

    Option	Description
    Monitoring profile	You can use this page to configure general monitor settings to collect data for your Watson™ Query connection. You can also create custom alerts using SQL scripts and schedule them to run at a specific time.
    Event monitor profile	Displays the information about the profile created to monitor specific event types that occur on Watson Query.