It’s been a long time since I wrote a blog post and I finally found some time 😀 I’ve played a lot recently with the new Azure SQL Database V12 version. It’s really cool because it has a lot of improvements if you compare it to v11. With the V12 version, you have almost the same functionalities like an on premise database and it consists also new functionalities like row-level security, dynamic data masking and the query store. Just like an on premise database, you also have to maintain your indexes and statistics because indexes can also get fragmented on an Azure SQL Database. With an on premise server or a VM in Azure, most DBA’s schedule an index maintenance job under the SQL Server Agent. However, with Azure SQL Database, you have to think inside the database, which means you don’t have any server functionalities, including SQL Server Agent. Luckily, the Azure platform provides the Azure Automation, which can be used as a replacement for the SQL Server Agent. In this blog post, I’m going to explain how you can schedule your index maintenance job or any other job that needs to be scheduled.
Create a new Azure Automation Account
First of all, you have to begin with creating a new Azure Automation Account. Go to the portal and select the Automation tab. Click the Create button to create the new Automation Account. Fill in the name of the account and the region. Choose the region that is the closest to you. r
Create an Azure Automation credential asset
As prerequisite, create an Azure Automation credential asset that contains the username and password for the target Azure SQL DB logical server. Click on the Automation Account that you have just created and select Assets. In this section, select the button “Add Setting” at the bottom.
Select the option “Add Credential”
Select the Credential type “Windows PowerShell Credential” because we’re going to use this credential in the PowerShell Workflow. Give the Credential a name.
Specify the username and the password that you will link to the credential. This will be the user that will connect to your SQL Azure Database.
Click on OK and wait until the credential is created.
Install your maintenance scripts
Make sure that you have installed your maintenance scripts/procedures on all your Azure Databases. In my example, I’ve been using the maintenance scripts of Ola Hallengren. For the index maintenance, I have to install the scripts IndexOptimize.sql and CommandExecute.sql. Make sure you download the latest version because Ola fixed an issue with the index optimize on Azure SQL Database on July 19th 2015. There is a small issue with the scripts. Ola uses cross database stored procedures, which is not supported in Azure DB at the moment. So, the @Database parameter will not work correctly. Please also check the comments of this blog post. You have to implement a workaround in the runbook.
Import the Maintenance Runbook
We have now setup all the prerequisites so we can start with creating a runbook in our Azure Automation account. A runbook is a PowerShell Workflow that needs to be created or imported. You can actually compare it to configuring a job step in the SQL Server Agent job. The runbook contains the SQL Scripts that need to be executed for the index maintenance and will be scheduled later on. Select your Automation Account and go to the runbook tab. Click on the button “Import” at the bottom to upload your PowerShell Workflow. Select your PowerShell script that you have created and upload it.
Here is my script that I have used.
Perform index maintenance
This runbook provides an example of how Azure Automation can be used to accomplish common SQL Agent tasks in the cloud.
As prerequisite, please create an Azure Automation credential asset that contains the username and password for the target Azure SQL DB logical server ($SqlServerName).
Make sure that you have installed the scripts IndexOptimize.sql and CommandExecute.sql of Ola Hallengren (https://ola.hallengren.com/downloads.html)
The check for the MAXDOP value in the IndexOptimize.sql script is using sys.dm_os_sys_info, which is currently not supported
So be sure you disable that check otherwise it will return an error.
AUTHOR: Pieter Vanhove
LAST EDIT: October 20, 2015
# Fully-qualified name of the Azure DB server
# Credentials for $SqlServerName stored as an Azure Automation credential asset
# When using in the Azure Automation UI, please enter the name of the credential asset for the "Credential" parameter
# Setup credentials
$ServerName = $Using:SqlServerName
$UserId = $Using:Credential.UserName
$Password = ($Using:Credential).GetNetworkCredential().Password
# Create connection to Master DB
$MasterDatabaseConnection = New-Object System.Data.SqlClient.SqlConnection
$MasterDatabaseConnection.ConnectionString = "Server = $ServerName; Database = Master; User ID = $UserId; Password = $Password;"
# Create command to query the current size of active databases in $ServerName
$MasterDatabaseCommand = New-Object System.Data.SqlClient.SqlCommand
$MasterDatabaseCommand.Connection = $MasterDatabaseConnection
select name from sys.databases
# Execute reader and return tuples of results <database_name, SizeMB>
$MasterDbResult = $MasterDatabaseCommand.ExecuteReader()
# Proceed if there is at least one database
# Create connection for each individual database
$DatabaseConnection = New-Object System.Data.SqlClient.SqlConnection
$DatabaseCommand = New-Object System.Data.SqlClient.SqlCommand
# Iterate through each database under $ServerName
$DbName = $MasterDbResult
# Apply conditions for user databases (i.e., not master DB)
if($DbName -ne "Master")
# Setup connection string for $DbName
$DatabaseConnection.ConnectionString = "Server=$ServerName; Database=$DbName; User ID=$UserId; Password=$Password;"
# Create command for a specific database $DBName
$DatabaseCommand.Connection = $DatabaseConnection
Write-Output "Perform index maintenance on $DbName"
# ExampleTable is a place holder for a table that holds a large volume of less important and expendable data
# that can be truncated to save space on the database.
@Databases = '" + $DbName + "',
@FragmentationLow = NULL,
@FragmentationMedium = 'INDEX_REORGANIZE,INDEX_REBUILD_ONLINE,INDEX_REBUILD_OFFLINE',
@FragmentationHigh = 'INDEX_REBUILD_ONLINE,INDEX_REBUILD_OFFLINE',
@FragmentationLevel1 = 5,
@FragmentationLevel2 = 30,
@UpdateStatistics = 'ALL',
@OnlyModifiedStatistics = 'Y'
$NonQueryResult = $DatabaseCommand.ExecuteNonQuery()
# Close connection to $DbName
# Close connection to Master DB
It’s based on the script that I have found on Codeplex. As you will notice, I have specified 2 parameters. $SqlServerName: this is the server name where we want to perform the index maintenance $Credential: This is the username that will be used to connect to the SQL Server. This will be linked to the credential that we have created in step 2 The workflow is first going to connect to the master database to retrieve all the online databases. As mentioned the install maintenance script part, I had to find a workaround because you cannot use cross DB stored procedures on Azure DB, which are used by the Ola’s IndexOptimize script. Once I get the list of all the databases, I connect to each of the DB’s separatly and execute the index optimize. Please not that the @Databases parameter should contain the current DB name. This solution is not (yet) as flexible as Ola’s solution but it’s a good start. Once the import is done, you will notice that the column Authoring still has a “New” Status. The runbook still needs to be published (see next chapter)
Test your Workflow and Publish
Before you can actually start using this Workflow, you have to publish it, however, I recommend to first test this if everything works fine. Once the Runbook has been created, you can click on it and go the Author section
In the “Draft” section you can see the Workflow that you have just imported. Click on the button “Test” at the bottom to test your Runbook. Before the Runbook is actually executed, you have to provide the 2 parameters. In my example, the Credential will be the AzureDBCredential that I have created in step 2. The name of my SQL Server is called pvhv12.database.secure.windows.net. This is the “SQL Server” where my databases are running on.
If all goes well, you should see an empty output pane with a status: COMPLETED
If not everything goes well, you will notice the errors in the output pane. As soon as you have tested the job and everything works fine, you can publish the runbook and start using it.
Schedule the runbook
The last step is to schedule the published runbook. This is actually the same like in the SQL Server Agent. You have to link a schedule to the job or in this case the runbook. In the runbook, click on the section “Schedule” and select “Link to a New Schedule”
Type in the name of your schedule. Again, the same principle as the name of a job schedule of the SQL Server Agent
Secondly, you need to configure the schedule. Currently you can choose between One time, Hourly or Daily. In my example, I want my Index Maintenance on a daily basis starting at 23:00.
In the final step, you have to specify the runbook parameters that will be used when the job is executed. This will be the same values that I have used in the test phase. Once the schedule is created, your index maintenance will be done on a daily basis.
Verify job history
Just like in the SQL Server Agent, you can also verify the job history of a Runbook. You can select “Jobs” in your runbook to verify the job history. When you click on one of the jobs, you can even see the error output, job summary and the parameters that have been used.
So summarize I will make a comparison between the Azure Automation and the SQL Server Agent Job.
||SQL Server Agent Job
|Create an Azure Automation Account
||Create an SQL Server Agent Job
|Create a runbook
||Create a Job Step
|Test the runbook
||Start Job at Step
|Publish the runbook
||Save the job
|Schedule the runbook
||Schedule the SQL Server Agent Job
|View jobs of the runbook