How to Migrate from SQL Server to Azure?

How to Migrate a SQL Server Database to Azure

The growing use of database-as-a-service (DBaaS) providers gives a flexible, cloud-based database option through subscription services. Many businesses that previously had to rely on expensive and frequently inflexible on-site database solutions may find it a welcome alternative.

Microsoft Azure® SQL Database has been a go-to option among DBaaS platforms for enterprises looking to transition to a subscription model. Azure’s solution is one of the most cost-effective while delivering solid security and disaster recovery.

Azure database conversion is one of the primary hurdles for many firms. It can be challenging for businesses concerned about the cost and time commitments required for effective cloud migration. However, migrating an Azure database does not have to be complicated. The following pointers can help you succeed. Remember that you may speed up the process using an automated tool like SolarWinds® SQL Sentry®, SolarWinds Database Performance Analyzer (DPA), or SolarWinds Database Performance Monitor (DPM).

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Top Tips for Database Migration

When migrating a SQL Server® database to Azure, here are some database migration suggestions.

Recognize the Problems

The first step in the cloud migration process is determining whether a cloud system is appropriate for your company. Understanding cloud migration’s risks and potential drawbacks might help significantly reduce the migration’s pain points. First and foremost, businesses must know that all cloud migrations include some downtime, whether done at once or in stages. If all of an organization’s data is copied to the cloud while teams are on-premises, it can reduce downtime.

It’s also crucial to understand how a new cloud system differs from an on-premises system in terms of capabilities. Transferring on-premises data into a cloud system may necessitate writing cloud-based programming to accommodate these differences. Working with a new cloud provider to acquire a complete picture of the differences you’ll need to account for during the migration will help you understand the cloud system and how it differs from an on-premises system.

Make a Strategy

Building a precise migration plan for Azure database transfer will be aided by gaining a thorough grasp of your crucial data systems. Here are a few things to keep in mind as you go through the discovery process:

• Data-consumption systems used by the migration target
• Systems that generate data for the migration target
• Versions of software components currently in use
• Utilization of resources (e.g., CPU, storage, memory)
• Performance benchmarks
• Workload examples
• RPOs (recovery point objectives) and RTOs (recovery time objectives) are two types of recovery goals (RTO)
• Owners of applications

Monitoring and documentation software, for example, can help teams collect this data more efficiently. However, some of this critical data necessitate IT experts to enlist business leaders’ help. This partnership has the extra benefit of securing executive support for the relocation. Obtaining this buy-in is essential in the migration process because it indicates that leaders have a thorough understanding of the process and are prepared to support the Azure database migration.

Clear the area

When firms don’t bring extra baggage, migrating to Azure is more manageable. Sorting through data to cull unwanted data sources saves time. It decreases the clutter to sort out later—cull data taking up expensive space but providing no real value to your organization before migrating to the cloud. Starting with a clean, well-organized cloud devoid of unnecessary data saves money and storage space and may result in a speedier system.

Construct a Data Dictionary

Starting a healthy, well-organized cloud requires more than just cleaning up data. Before starting your Azure database migration, SentryOne’s Kevin Kline recommends creating a comprehensive data dictionary. According to his recommendations, migration is a great time to look for “glaring defects” in your SQL code or system design: “For example, because stored procedures employ a data type that is incompatible with the data type stated in the database table, they may generate a high number of implicit conversions.” Examining such concerns aids in the creation of a solid data dictionary.”

Take note of every critical system document as you search through databases before the transfer to create a data dictionary that can be accounted for after the move. While this procedure is time-consuming, ensuring that the new system is completely functional and meets your company’s requirements is necessary.

A robust data dictionary starts with extensive data lineage tracing, which involves recording all of the steps that data has already gone, from source to ETL techniques, as well as notes about production databases or data warehouses. Data lineage documentation helps an organization figure out where its data has been in the past, including whether it has been analyzed, cleansed, edited, or transferred. This procedure aids IT workers in determining whether data has to be updated before being moved to maintain its integrity. Should send not all data to the cloud. Still, the data authorized to go there should have a complete history so that companies can comprehend their new position in the cloud.

Data Replication

While copying and pasting all data into the cloud is impossible, the mirroring process ensures that no data is lost throughout the Azure database transfer. Consider using the Extract, Transform, and Load (ETL) method to help with migration. It allows teams to replicate data and applications into the cloud while keeping end users on-premises and keeping data and applications parallel to the cloud throughout the migration. The initial phase of the migration procedure is reintroduced at this point. Before migrating an Azure database, identify any code that has been built or changed for cloud compatibility.

Test, Test, and Test Some More

Once the database migration is complete, it’s critical to properly test the cloud to discover and prepare for any difficulties that may arise in the future. To begin, compare your previous system to your new cloud to find missing data, disparities between the two systems, and pain points or places that may improve the cloud.

Create a baseline for reports by releasing an introductory paper explaining how the cloud works, rather than merely evaluating it as-is. Keep an eye on the system while updating the baseline reports and looking for any potential problems. Your cloud should grow with your organization, performing just as well months or years later as it did at the start. Please hold off on deploying the new cloud across the company until it has been thoroughly tested and its capabilities have been thoroughly documented.

Tools to Streamline Your Azure Database Migration

Fortunately, you don’t have to do it alone when migrating an Azure database. There are several tools available to make the transition as smooth as possible. Some of the top Azure database migration tools are listed below.

Database Performance Monitor by SolarWinds® (DPM)

This application aids with the transfer of your Azure database by gathering, evaluating, and visualizing the metrics required to diagnose Azure SQL performance issues in real-time. DPM monitors latency, throughput, failures, warnings, index utilization, execution plans, and more for each query conducted, providing in-depth insight into database performance. IT professionals created DPM for IT professionals, designed to be straightforward to use. You can drill down from a global view to analyze particular problem inquiries on individual servers with just a few clicks.

Database Performance Analyzer by SolarWinds® (DPA)

The migration and testing process aims to find problems before they occur. SolarWinds DPA’s Azure SQL database monitoring tool can help you discover the most significant Azure SQL server performance issues in your environment, then drill down into the analysis DPA provides to figure out what’s causing the difficulties. To better understand resource utilization issues, use associated resource measures.

The DPA Azure SQL performance monitoring tool does detailed blocking and deadlock analysis to quantify the impact of blocking on end-users while visualizing the blocking tree to disclose the sessions and queries involved, allowing you to figure out what caused the problem and who was affected. Query-level performance analysis compiles all available data into a single view to help you answer questions like “Why is this query so slow right now?” and more.

SQL Sentry® by SolarWinds

Choosing the proper SQL database for your company necessitates thorough cost-cutting planning. Under- or over-provisioning resources, whether for your software-as-a-service (SaaS) business, enterprise production, or development and testing, can result in a bad user experience and wasted budget.

SQL Sentry keeps track of performance parameters, such as database transaction unit (DTU) use, and notifies you when something goes wrong with your system. SQL Sentry allows you to discern between normal and abnormal performance patterns, which is crucial for ensuring that your data platform provides optimal performance to end-users.

Moving SQL Servers from on-premises to the cloud can have positive and negative consequences, particularly during the transition. SolarWinds, a long-time Microsoft technology partner, can help you migrate SQL Server workloads to Azure SQL Database or an Azure SQL Database Managed Instance.

SolarWinds products help you migrate more smoothly and ensure that your Azure workloads perform at their best.

About Enteros

Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of clouds, RDBMS, NoSQL, and machine learning database platforms.