Microsoft DP-300 Practice Test - Questions Answers, Page 14

Activity log events - An alert can trigger on every event, or, only when a certain number of events occur. Incorrect Answers:

C: Metric values - The alert triggers when the value of a specified metric crosses a threshold you assign in either direction. That is, it triggers both when the condition is first met and then afterwards when that condition is no longer being met.

Reference:

https://docs.microsoft.com/en-us/azure/azure-sql/database/alerts-insights-configure-portal

There are resource types related to application code, compute infrastructure, networking, storage + databases. You can deploy up to 800 instances of a resource type in each resource group.

Some resources can exist outside of a resource group. These resources are deployed to the subscription, management group, or tenant. Only specific resource types are supported at these scopes.

Reference:

https://docs.microsoft.com/en-us/azure/azure-resource-manager/management/resource-providers-and-types

The number of files depends on the number of (logical) processors on the machine. As a general rule, if the number of logical processors is less than or equal to eight, use the same number of data files as logical processors. If the number of logical processors is greater than eight, use eight data files and then if contention continues, increase the number of data files by multiples of 4 until the contention is reduced to acceptable levels or make changes to the workload/code.

Reference: https://docs.microsoft.com/en-us/sql/relational-databases/databases/tempdb-database

Follow these same steps to create striped virtual disk:

Create Log Storage Pool.

Create Virtual Disk

Create Volume

Box 1: a storage pool

Box 2: a virtual disk that uses stripe layout

Disk Striping: Use multiple disks and stripe them together to get a combined higher IOPS and Throughput limit. The combined limit per VM should be higher than the combined limits of attached premium disks.

Box 3: a volume

Reference:

https://hanu.com/hanu-how-to-striping-of-disks-for-azure-sql-server/

Box 1: sys.resource_stats

sys.resource_stats returns CPU usage and storage data for an Azure SQL Database. It has database_name and start_time columns.

Box 2: DateAdd

The following example returns all databases that are averaging at least 80% of compute utilization over the last one week.

DECLARE @s datetime;

DECLARE @e datetime;

SET @s= DateAdd(d,-7,GetUTCDate());

SET @e= GETUTCDATE();

SELECT database_name, AVG(avg_cpu_percent) AS Average_Compute_Utilization

FROM sys.resource_stats

WHERE start_time BETWEEN @s AND @e

GROUP BY database_name

HAVING AVG(avg_cpu_percent) >= 80

Incorrect Answers:

sys.dm_exec_requests:

sys.dm_exec_requests returns information about each request that is executing in SQL Server. It does not have a column named database_name.

sys.dm_db_resource_stats:

sys.dm_db_resource_stats does not have any start_time column.

Note: sys.dm_db_resource_stats returns CPU, I/O, and memory consumption for an Azure SQL Database database. One row exists for every 15 seconds, even if there is no activity in the database. Historical data is maintained for approximately one hour.

Sys.dm_user_db_resource_governance returns actual configuration and capacity settings used by resource governance mechanisms in the current database or elastic pool. It does not have any start_time column.

Reference:

https://docs.microsoft.com/en-us/sql/relational-databases/system-catalog-views/sys-resource-stats-azure-sql-database

Azure HDInsight offers pre-made, monitoring dashboards in the form of solutions that can be used to monitor the workloads running on your clusters. There are solutions for Apache Spark, Hadoop, Apache Kafka, live long and process (LLAP), Apache HBase, and Apache Storm available in the Azure Marketplace.

Note: With Azure HDInsight you can set up Azure Monitor alerts that will trigger when the value of a metric or the results of a query meet certain conditions. You can condition on a query returning a record with a value that is greater than or less than a certain threshold, or even on the number of results returned by a query. For example, you could create an alert to send an email if a Spark job fails or if a Kafka disk usage becomes over 90 percent full.

Reference:

https://azure.microsoft.com/en-us/blog/monitoring-on-azure-hdinsight-part-4-workload-metrics-and-logs/

The performance capacity of a query is determined by the user's resource class.

Smaller resource classes reduce the maximum memory per query, but increase concurrency. Larger resource classes increase the maximum memory per query, but reduce concurrency.

Reference:

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/resource-classes-for-workload-management

Backlogged Input Events: Number of input events that are backlogged. A non-zero value for this metric implies that your job isn't able to keep up with the number of incoming events. If this value is slowly increasing or consistently non-zero, you should scale out your job, by increasing the SUs.

Reference:

https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-monitoring

To react to increased workloads and increase streaming units, consider setting an alert of 80% on the SU Utilization metric. Also, you can use watermark delay and backlogged events metrics to see if there is an impact. Note: Backlogged Input Events: Number of input events that are backlogged. A non-zero value for this metric implies that your job isn't able to keep up with the number of incoming events. If this value is slowly increasing or consistently nonzero, you should scale out your job, by increasing the SUs.

Reference:

https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-monitoring