PostgreSQL Discovery and Assessment in Azure Migrate – Public Preview
We’re excited to announce the public preview of PostgreSQL discovery and assessment in Azure Migrate! This feature helps organizations plan their migration journey to Azure by providing deep insights into on-premises PostgreSQL environments. Why This Matters Migrating PostgreSQL workloads to Azure can be challenging without visibility into your current environment. Azure Migrate now offers a unified experience to: Discover PostgreSQL instances across your infrastructure. Assess migration readiness and identify potential blockers. Get configuration-based SKU recommendations for Azure Database for PostgreSQL. Estimate Azure costs for your PostgreSQL workloads. Key Capabilities Comprehensive Discovery Inventory: Catalog PostgreSQL versions and related components. Discovery: Collect database parameters, configurations, table structures, and storage details. Assessment Features Readiness Rules: Determine if your PostgreSQL instances are: Ready: The instance can be migrated to Azure Database for PostgreSQL without any migration issues. Ready with Conditions: The instance has one or more migration issues. Review the identified issues and apply the recommended remediation steps before migration. Not Ready: The assessment did not identify an Azure Database for PostgreSQL configuration that meets the desired performance and configuration requirements. Review the recommendations provided to make the PostgreSQL instance ready for migration. Unknown: Azure Migrate can't assess readiness because discovery is still in progress or there are issues that need to be resolved. To fix discovery issues, check the Notifications blade for details. If the issue persists, contact Microsoft support. Configuration-Based SKU Recommendations: Based on vCores and memory from the machine and storage from the PostgreSQL instance, Example: Memory Optimized – E20ds_v5 Pricing Estimates: Approximate Azure cost for recommended SKUs. Database Parameter Collections - Deep insights into Database parameters How to Get Started? To begin using the PostgreSQL Discovery and Assessment feature in Azure Migrate, follow this four-step onboarding process: Create an Azure Migrate project Initiate your migration journey by setting up a project in the Azure portal. Configure the Azure Migrate appliance Install Windows-based Azure Migrate appliance to obtain a software inventory of servers, PostgreSQL instances, and their attributes, and perform discovery. Review discovered inventory Examine the detailed attributes of the discovered PostgreSQL instances. Create an assessment Evaluate readiness and get detailed recommendations for migration to Azure Database for PostgreSQL. Benefits of Using Azure Migrate for PostgreSQL Single Pane of Glass: Manage PostgreSQL migrations alongside servers, apps, and other databases. Simple Setup: Lightweight collector, no heavy appliances. Actionable Insights: Readiness rules and SKU recommendations tailored to your configuration. For comprehensive, step-by-step instructions, please refer to the discovery and assessment tutorials in the documentation: Provide server credentials to discover software inventory, dependencies, web apps, and SQL Server instances and databases - Azure Migrate | Microsoft Learn Discovery methods in Azure Migrate - Azure Migrate | Microsoft Learn Assessing On-Premises PostgreSQL for Migration to Azure Flexible Server - Azure Migrate | Microsoft Learn Join the Preview and Share Your Feedback! The PostgreSQL Discovery and Assessment feature in Azure Migrate enables you to effortlessly discover, assess, and plan your PostgreSQL database migrations to Azure. Try the features out in public preview and fast-track your migration journey! If you have any queries, feedback, or suggestions, please let us know by leaving a comment below or by directly contacting us at askazurepostgresql@microsoft.com. We are eager to hear your feedback and support you on your journey to Azure
Azure Migrate Appliance
Hi, We are planning to migrate 100 servers to Azure and are looking for guidance on deploying the Azure Migrate appliance. Due to space limitations on-premises, we do not have room to deploy the appliance locally. Is it possible to deploy the Azure Migrate appliance in an Azure virtual machine (VM) within our existing Azure subscription? if so we would like to deploy the VM, install the Azure Migrate appliance, and then use it to assess, discover, and perform dependency analysis for our on-premises virtual and physical servers. Additionally, we are considering using the "Physical Server" option by downloading the installer script from the Azure Migrate appliance. Can you please confirm if this approach is viable, are there any additional steps or considerations we should be aware of by deploying the appliance in Azure on a VM. Thanks
A quick way to generate Azure SQL migration assessments
Overview Azure Migrate doesn’t allow users to import the SQL Server Inventory and discovery information from sources other than Azure Migrate appliance as of today. As a result, users who cannot deploy Azure Migrate appliance to discover their SQL Server estate for technical, business or compliance reasons or have already discovered their SQL Server estate using tools like rvtools and want a quick and approximate way to check readiness and total cost savings by moving to Azure, cannot leverage the rich capabilities SQL assessment and business case capabilities that Azure Migrate offers. To help customers quickly get migration readiness and cost savings by migrating to Azure, we are introducing “Import SQL Server Discovery data as CSV” feature in Azure Migrate that allows users to import the SQL Server inventory as a CSV file and use the discovery data to generate assessments and business cases. This feature is launched in private preview. In this blog post, we will do a deep dive on how to use this feature to generate quick assessments for your off-Azure SQL Server estate. Here are the high-level steps for importing your off-Azure SQL Server inventory as a CSV: 1) Step-1: Identify the SQL Server Instances and extract the discovery data into a CSV file. 2) Step-2: Validate and upload the inventory data to Azure Migrate 3) Step-3: Generate and view Assessments Pre-requisites: Import SQL Discovery data as a CSV feature is built on top of the new Azure Migrate experience which is also in Private Preview phase. To use Import SQL Discovery data as CSV feature, you must onboard to the private preview of new Azure Migrate experience and here is the form to sign up for Private preview: Azure Migrate Private Preview Sign-Up Survey. We will share the instructions to onboard via the contact details you provided. Make sure you have the credentials to connect to the SQL Server Instances of interest Make sure you have the requisite roles and privileges on each SQL Server Instance to access and extract the required metadata from Dynamic Management Views. To generate a login with required privileges, please run the scripts listed here: Configure custom login for SQL Server Discovery An Azure Subscription. Please note you don't need to deploy an Azure Migrate appliance to use the SQL import CSV feature. Step-1: Identify and extract the discovery data of SQL Server Instances you intend to migrate to Azure SQL into a CSV file Identify the list of all off-Azure SQL Server Instances you intend to migrate to Azure SQL from either on-premises infrastructure or other cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP). To extract the discovery data, please run the SQL Script below against the SQL Server Instance which you would like to import into Azure Migrate via CSV and store the output into a CSV file. /* PLEASE ENTER THE FULLY QUALIFIED DOMAIN NAME OF THE HOST IN THE LINE BELOW BEFORE RUNNING THE QUERY */ Declare @FullyQualifiedDomainName varchar(200) = ''; With ServerCores AS( SELECT cpu_count AS [Logical CPU Count], hyperthread_ratio AS [Hyperthread Ratio], cpu_count/hyperthread_ratio AS [Physical CPU Count], sqlserver_start_time FROM sys.dm_os_sys_info ), Config AS( SELECT value_in_use AS [Max Server Memory(MB) In Use] FROM sys.configurations WHERE name = 'max server memory (MB)'), UserCount AS( SELECT count(database_id) AS [Number User Databases] FROM sys.databases WHERE database_id > 4 ), DbSize AS( SELECT SUM(CAST(Size AS bigint))*8/1024 AS [Max server memory (in MB)] FROM sys.master_files WHERE database_id > 4 ), TempDbSize AS ( SELECT SUM(CAST(Size AS bigint))*8/1024 AS [TempDb Size (In MB)] FROM sys.master_files WHERE db_name(database_id) = 'tempdb' ), Logins AS (Select count(name) AS [NumOfLogins] from sys.syslogins), Properties AS ( select db.name as database_name, db.database_id as database_id, cast(db.compatibility_level as int) as database_compatibility_level, db.collation_name as database_collation, db.is_broker_enabled as is_service_broker_enabled, '0' as [Number of Nics], SERVERPROPERTY ('servername') as instance_name, SERVERPROPERTY ('productversion') as instance_version, SERVERPROPERTY ('edition') as instance_edition, SERVERPROPERTY ('productlevel') as instance_level, SERVERPROPERTY ('IsHadrEnabled') as is_hadr_enabled, SERVERPROPERTY ('collation') as server_collation, CASE WHEN SERVERPROPERTY ('IsClustered') = 1 THEN 'TRUE' ELSE 'FALSE' END as is_failover_clustered, COALESCE(SERVERPROPERTY ('IsIntegratedSecurityOnly'), 0) as is_integrated_security_only, COALESCE(SERVERPROPERTY ('IsPolyBaseInstalled'), 0) as is_polybase_installed, CASE WHEN 'A' = 'a' THEN 0 ELSE 1 END as is_server_case_sensitive, /* '' + @host_platform + '' as host_platform,*/ db.state as database_state, /* db.is_auto_close_on as is_auto_close_on,'+ CASE when @check_cdc = 1 THEN 'db.is_cdc_enabled' else '0' END + ' as is_cdc_enabled,*/ CASE when db.user_access = 0 THEN 1 ELSE 0 END as is_multi_user, CASE when db.recovery_model = 0 THEN 0 ELSE 1 END as is_full_recovery_model, db.is_read_only as is_read_only, case when source_database_id IS NULL THEN 0 ELSE 1 end as is_snapshot, case when is_published = 1 OR is_subscribed = 1 OR is_merge_published = 1 or is_distributor = 1 THEN 1 ELSE 0 end as is_replication_enabled, db.is_encrypted from sys.databases db where db.name not in ('master', 'tempdb', 'model', 'msdb') and is_distributor <> 1), EachDbSize AS( SELECT database_name = DB_NAME(database_id), CAST(SUM(CAST(size AS bigint)) * 8. / 1024 AS DECIMAL(12,2)) AS [Database size (in MB)], convert(varchar(12),CAST((sum(case when physical_name like '%ldf'then 0 else size end)*8.0)/1024.0 AS numeric(8,2))) AS [Data file size (in MB)], convert(varchar(12),CAST((sum(case when physical_name like '%ldf'then size else 0 end)*8.0)/1024.0 AS numeric(8,2))) AS [Log file size (in MB)] FROM sys.master_files WHERE database_id > 4 GROUP BY database_id) select @FullyQualifiedDomainName as [Fully qualified domain name], instance_name as [Instance Name], p.database_name as [Database Name], database_state as [Database Status], instance_edition [SQL Edition], instance_version as [SQL Version], [Logical CPU Count], [Hyperthread Ratio], [Physical CPU Count], [TempDb size (in MB)], is_failover_clustered as [Is FCI Enabled], '' as [Failover cluster name], '' as [Failover cluster instance role], '' as [Failover cluster shared disk count], '' as [Is failover cluster multi subnet], [Max server memory (in MB)], [Number of Nics], instance_level as [Service pack], '' as [ESU status], 'FALSE' as [IS AG enabled], instance_level as [Build version], 'Online' as [Service status], 'FALSE' as [Is database highly available], 'FALSE' as [Is part of distributed availability group], [Database size (in MB)], [Data file size (in MB)], [Log file size (in MB)], database_compatibility_level as [Compatibility level], '' as [Availability group ID], '' as [Availability group name], '' as [Availability group type], '' as [Availability replica ID], '' as [Availability replica name], '' as [Commit mode], '' as [Replica type], '' as [Replica state], 'FALSE' as [Is AG multi subnet], '' as [AG replica sync status], '' as [AG replica seed mode], '' as [AG replica read mode] from ServerCores, Config, UserCount, DbSize, TempDbSize,Logins, Properties p LEFT JOIN EachDbSize s on p.database_name = s.database_name order by p.database_name Collate the output of all SQL Server Instances of interest into a single file. Step-2: Validate and upload the CSV file To validate and upload the generated CSV file with SQL Server discovery data: 1) Go to the Azure Migrate experience link you would have received from Microsoft after you signed up for the private preview of this feature. Click on “Create Project” to create a new Project (if not done already): 2) Fill in the required fields in create project wizard 3) Click on the created project and select “Using custom Import” option under “Start Discovery” button. 4) In the Discover page, select “File Type” as “SQL Server inventory (CSV)” 5) (Optional) Click on “Download” button under Step 1: Download template to view and understand the template expected by Azure Migrate. Optionally, you can skip this step as the CSV file generated by SQL script shared above confirms to the template. 6) Browse and select the inventory file in Step-2 and click on Validate to validate the uploaded SQL Inventory data. 7) If the uploaded doesn’t contain any warnings or error messages, it will show validation completed successfully with 0 errors and warnings. If there are any errors or warnings Azure Migrate will show a count of warning and error messages. To view and resolve the warnings or errors (if any) with the imported file, click on Download ErroDetails.csv, which displays errors/warning messages corresponding to each database along with remedial action. Please note warnings are non-blocking messages, i.e., user can still go ahead and complete the Import operation. Whereas errors are blocking in nature i.e. users will not be allowed to import unless the error messages are resolved. 8) Once the validation phase is completed, click on Import button to complete the import operation. Step-3: Create Assessments using imported SQL Discovery Data SQL Server Instances and the databases uploaded via CSV import route are treated at par with the SQL Server instances that are discovered by Azure Migrate appliance. You can view the SQL Server Instance properties like Version details, Number of databases, Support status and all other properties uploaded via CSV file. The quality of property details and the assessments generated is directly dependent on the quality of data uploaded via CSV. To create SQL assessments for the uploaded SQL Server Instances, go to the Azure Migrate project's resource page and click on Create Assessments button: Give a name for the assessment and click on Add workloads to add the imported and appliance discovered workloads: In the following page, select the SQL Server instances that have value “Import” for Discovery Source column. You can also create assessments on a combination of workloads that are imported and appliance discovered. Click Add button to add the workloads and click on Review + Create Assessments to create assessment. For imported SQL Server instances, the quality of assessments is only as good as the data uploaded via CSV, please ensure that the data uploaded via CSV accurately depicts the metadata of the SQL Server instance. Like regular SQL assessments, you will have all the assessment configuration options like choosing Sizing criteria (performance-based vs as on-premises), migration strategy (optimizing cost vs migration to PaaS), comfort factor etc. By default, Azure Migrate will try to create a performance-based incase the performance-metrics are not available, it defaults to As-on-premises assessment. Assessment created on the imported SQL Servers will help you know which SQL Server Instances are ready for migration to Azure SQL, the recommended Azure SQL Target type. Linking and Rediscovery Linking If the host where the imported SQL Instance currently hosted is discovered via import of VM Servers or via appliance, the SQL Server Instance will be automatically associated with that host. SQL Server Instance will be rolled up under that VM Server in the discovery view. The SQL Server instance will be uniquely identified based on the FQDN and the SQL Server Instance name. The combination of attributes is used for conflict resolution as well. Rediscovery and precedence rules 1) If the SQL Server instance is originally imported via CSV and is reuploaded again via CSV, upload operation will rewrite all the properties. 2) If the SQL server instance is first imported via CSV and then discovered via Azure Migrate appliance and the user has provided credentials to do deep discovery via Azure Migrate appliance, then the appliance discovered data will override the data imported via CSV. 3) If the SQL server instance is first imported via CSV and then discovered via Azure Migrate appliance and the user has not provided SQL Server credentials to do deep discovery, then the appliance discovered data will only update the additional data that appliance discovered. 4) If the SQL Server Instance is first discovered via the Azure Migrate appliance and is deep discovered (correct SQL Server credentials are provided), and if the SQL Server is imported via CSV, data imported via CSV will be discarded. 5) If the SQL Server Instance is first discovered via the Azure Migrate appliance and is only inventoried (correct SQL Server credentials are not provided), and if the SQL Server is later imported via CSV, upload operation will completely overwrite the appliance discovered details. How to onboard to Private Preview To onboard Preview of SQL Inventory import as CSV, please fill the Signup form for Private preview What’s Next 1) In the next release will ship out capabilities to create Business case for SQL Servers imported via CSV. 2) We will also build support for Availability Groups and Failover cluster Instances for the SQL Server instances imported via CSV.
