Migrate from Azure to AWS: Strategies, Tools, and Secrets

Migrating from Microsoft Azure to Amazon Web Services (AWS) is a significant cloud strategy move that many organizations are now considering. In fact, AWS remains the world’s top cloud provider (holding about 32% market share versus Azure’s 23% as of 2024). Businesses might pursue an Azure to AWS cloud migration to leverage AWS’s broader services, cost advantages, or global infrastructure. This article will explore why and how to migrate from Azure to AWS, providing a step-by-step guide, key migration strategies, tools, and best practices. By understanding the benefits and planning carefully, you can transition to AWS smoothly and harness its capabilities for your organization’s growth.

Why Migrate from Azure to AWS? (Key Benefits)

Switching cloud providers is not a decision to take lightly, but there are compelling reasons why organizations choose to move from Azure to AWS. Below are some key benefits and differences that often motivate an Azure-to-AWS migration:

• Cost Optimization: AWS offers flexible pricing models that can lead to lower costs in certain scenarios. For example, AWS provides deeper discounts with options like Savings Plans and Spot Instances, and even slightly higher discounts on Reserved Instances compared to Azure’s reservations. This means that for steady workloads, AWS may deliver better long-term cost savings. Additionally, once on AWS, you can use built-in cost management tools (AWS Cost Explorer, AWS Budgets, etc.) to optimize spending and avoid surprises. (Notably, a study by Accenture found moving workloads to public cloud can reduce total cost of ownership by up to 40%.)
• Global Infrastructure & Performance: If worldwide reach and low-latency performance are priorities, AWS currently operates in more regions and availability zones than Azure. This expansive global network means you can host applications closer to end-users, potentially improving responsiveness. Both Azure and AWS are reliable, high-performance clouds, but AWS’s larger geographic footprint can give it an edge in serving globally distributed users.
• Service Breadth and Depth: AWS has a reputation for a vast ecosystem of services and integrations. With over 200 fully featured services ranging from compute and storage to AI/ML, IoT, and analytics, AWS offers more specialized solutions than Azure in many domains. For example, AWS has multiple storage services (S3, EFS, EBS, Glacier, etc.) whereas Azure’s storage options, while solid (Blob Storage, Azure Files, etc.), are fewer in number. This breadth means you’re more likely to find an AWS service that perfectly fits your needs or allows new innovations. AWS also boasts a huge developer community and third-party marketplace, which can accelerate development and integration efforts.
• Scalability and Elasticity: Both Azure and AWS can scale to handle enterprise workloads, but AWS was architected with extreme elasticity in mind. Services like Amazon S3 offer virtually unlimited storage that expands automatically, and EC2 instances can scale in or out on-demand with Auto Scaling groups. AWS’s focus on on-demand scalability means you can handle traffic spikes or growth with minimal manual intervention. Azure provides scaling as well, but AWS’s tools for automation and scaling (like Lambda for serverless, or Kubernetes/ECS for containers) are often cited as very mature. This makes AWS attractive for applications that need to scale rapidly or unpredictably.
• Security and Compliance: When it comes to compliance certifications and security features, AWS is a leader. AWS currently holds 143+ security and compliance certifications including standards like FedRAMP High, PCI-DSS, HIPAA, and more. Both Azure and AWS are highly secure platforms with robust identity management and encryption capabilities. However, AWS’s longer list of compliance attestations can simplify audits for organizations in regulated industries. AWS also provides advanced security tools (Security Hub, GuardDuty, IAM Access Analyzer, etc.) to continuously monitor and enforce security best practices. These features help companies migrating to AWS maintain or even improve their security posture post-migration.
• Innovation and Ecosystem: Many cutting-edge cloud innovations (for example, serverless computing with AWS Lambda, or advanced analytics with AWS Redshift and Athena) were pioneered or are exceptionally well-implemented on AWS. Companies sometimes migrate to AWS to take advantage of unique features or new services that may not yet exist on Azure. AWS’s ecosystem of partners and solutions is also very extensive. For instance, AWS has a rich marketplace and partner network for third-party integrations, and services that Azure might not offer. (Our related post Why AWS Is Better Than Azure dives deeper into some of the unique advantages AWS offers over Azure, such as a lower long-term TCO and more robust feature sets.)

Real-world Example: Some organizations move to AWS to solve specific challenges they faced on Azure. For example, Cloudvisor’s client Repsense – an AI-driven data company – undertook a successful migration from Azure to AWS to achieve better flexibility, security, and performance. This move allowed Repsense to leverage AWS’s strengths in those areas and meet its scaling goals. (See Cloudvisor’s case study on Repsense’s migration from Azure to AWS for more details.)

In summary, migrating from Azure to AWS can bring cost efficiencies, access to a wider range of cloud services, improved global performance, and a strong security/compliance framework – all of which align with many businesses’ cloud optimization goals. Next, we’ll look at how to properly plan such a migration to maximize these benefits.

Planning an Azure to AWS Migration Strategy

A successful Azure-to-AWS migration starts with thorough planning and a well-defined strategy. Rushing into cloud migration without a plan can lead to cost overruns or downtime. Here’s how to craft your migration game plan:

1. Assess Your Current Environment: Begin by taking inventory of your existing Azure resources – applications, VMs, databases, storage, networking, and how they interconnect. This assessment helps identify what needs to move and any potential challenges. It’s important to map out dependencies between components (for example, which apps rely on specific databases) and note any Azure-specific services in use. Many organizations create an assessment checklist of all workloads, dependencies, and requirements. This process might reveal, for instance, that you’re using an Azure-specific managed service with no direct AWS equivalent, which will influence your migration approach.

2. Define Migration Goals and Strategy: Clarify why you are migrating and what success looks like. Are you aiming to reduce costs, improve performance, increase reliability, or adopt new features? Setting clear objectives will guide your technical decisions. Based on your goals and the nature of each workload, decide on a migration strategy for each application. The main cloud migration strategies are often referred to as the “6 R’s” – Rehost, Replatform, Refactor, Repurchase, Retain, or Retire. In context of Azure to AWS:

• Rehost (“lift-and-shift”): Move workloads to AWS EC2 instances without major changes. This is the fastest approach for simple migrations.
• Replatform: Make minimal adjustments to use more cloud-native services (e.g., migrate an Azure SQL database to Amazon RDS, or move a Windows VM to AWS but perhaps switch the web server to AWS Elastic Beanstalk).
• Refactor (or Re-architect): Re-write or significantly alter an application to use AWS-native architectures (for example, breaking a monolith into microservices, using AWS Lambda, DynamoDB, etc.). This is the most effort but can offer the greatest long-term cloud benefits.
• Repurchase: Replace the application with a third-party or SaaS solution, if applicable (this might not directly relate to Azure vs AWS, but it’s part of overall cloud strategy).
• Retain: Keep some applications on Azure (or on-premises) if they are not ready or not cost-effective to move.
• Retire: Decommission applications that are no longer needed rather than migrating them at all.

For each workload, choose the approach that balances effort vs reward. Many Azure-to-AWS migrations start as rehosting for speed (using tools to copy VMs over to AWS) and then later refactor certain components to fully optimize on AWS.

3. Create a Detailed Migration Plan: Once strategies are chosen, develop a project plan and timeline. Prioritize what to migrate first – often non-critical or test environments are migrated before production for learning purposes. Set milestones for each phase of the migration. It’s crucial to anticipate potential risks such as downtime or data loss and plan mitigations for each. For example, you might schedule migrations during off-peak hours and ensure you have recent backups of all data before starting. Also plan capacity on AWS so that when you cut over from Azure, the AWS environment can handle the load.

Don’t forget to budget for the migration. During the transition, you may be paying for both Azure and AWS concurrently for a short period. There may also be costs for data transfer (egress from Azure), so estimate these in advance. AWS does offer tools like the AWS Pricing Calculator to model costs, and programs like the AWS Startup Migrate Program (SMP) to help startups migrate with minimal cost (Cloudvisor’s guide “Migrate to AWS for Free: A Guide to AWS SMP” explains how qualified startups can get AWS credits and assistance for migrations).

4. Map Azure Services to AWS Equivalents: A practical aspect of planning is figuring out the AWS counterpart for each Azure service you’re using. For example, if you currently use Azure Blob Storage, you’ll likely migrate that data into Amazon S3 (object storage on AWS). For Azure SQL Database or Cosmos DB, you might use Amazon RDS or DynamoDB on AWS. It’s helpful to create a mapping document of Azure services to AWS services. This ensures you have a target design for the AWS environment that meets all the same requirements. In some cases, the mapping is straightforward; in others, you might need a combination of AWS services to replace one Azure service. (Microsoft even provides an “Azure for AWS Professionals” guide to compare services, and AWS has Prescriptive Guidance on migrating specific Azure services to AWS.) By singling out AWS services equivalent to those in Azure, you minimize compatibility issues during migration.

5. Prepare Your Team and Skills: Ensure that your IT team is prepared to work with AWS. Cloud engineers and developers familiar with Azure will need to learn AWS’s platform (which has its own terminology and console). Invest in training or certification for key team members on AWS fundamentals. If you lack AWS expertise in-house, consider partnering with an AWS consulting firm or using managed services for the migration period. Having the right skills available is critical – for instance, understanding AWS Identity and Access Management (IAM) for setting up accounts securely, or knowing how to configure networking (VPCs, security groups) in AWS. The planning phase should account for any skill gaps: will you need outside help or additional training before executing the migration?

6. Use Migration Tools for Planning: Take advantage of tools to assist with planning. AWS offers AWS Migration Hub, which can help track the migration of multiple resources in one place. It can also import application inventory data from Azure (or on-prem) to analyze what you have and plan moves. Additionally, third-party tools and cloud management platforms can assess your Azure environment and recommend migration steps or even automate parts of the planning.

7. Consider a Phased Approach: It’s often wise to migrate in waves rather than all at once. Plan a sequence – for example, migrate one application or one department at a time. This phased approach allows you to test and learn from each smaller migration, refine your process, and ensure minimal impact on business operations. After each phase, you can validate that everything works on AWS before proceeding.

By meticulously planning your Azure to AWS migration strategy, you reduce the risk of surprises. Remember that cloud migration is common – in fact, about 80% of organizations utilize multiple clouds (AWS, Azure, private clouds, etc.), and many are in the process of shifting more workloads to the cloud. With a solid plan in hand, you’ll join those who migrate with confidence, knowing the move is grounded in business goals and careful preparation.

Addressing Common Azure to AWS Migration Challenges

Migrating between cloud providers comes with a unique set of challenges and concerns. Here we address some of the most frequently asked questions and issues that arise when moving from Azure to AWS, along with tips to handle them:

1. “Will we experience downtime during the migration?” – Minimizing downtime is a top concern. The good news is that with proper tools and planning, you can keep downtime very low. AWS provides migration services that replicate your workloads in real-time. For example, the AWS Application Migration Service (MGN) can continuously copy over your Azure virtual machines (including their data) to AWS in the background. This allows you to do a controlled cutover at a chosen time with minimal service interruption. According to AWS, Application Migration Service supports lift-and-shift moves “without compatibility issues, performance disruption, or long cutover windows”. In practice, you might run both environments in parallel during a transition period: keep your Azure servers live until the AWS ones are fully synchronized, then switch traffic to AWS. Strategies like database replication, and performing migrations during off-hours, further reduce user impact. It’s also wise to inform users of a maintenance window just in case. But many migrations have been done where users barely notice any downtime.

2. “How do we securely transfer large amounts of data?” – Moving gigabytes or terabytes of data from Azure to AWS can be daunting. The challenge is twofold: transfer time and security. There are a few approaches:

• Online data transfer: For moderate data volumes, you can transfer over the internet or a direct connection. AWS DataSync is a service that can automate data transfer from Azure storage to AWS securely and efficiently. You deploy a DataSync agent in Azure, which moves data to AWS S3 or EFS, handling encryption and verification.
• Direct Connect or VPN: If you have a large pipe between Azure and AWS (for example, via AWS Direct Connect or a VPN tunnel), you can use that for faster transfers without sending data over the public internet. This can improve speed and security.
• Offline transfer: For very large datasets (many terabytes or more) or where bandwidth is limited, AWS Snowball provides a physical appliance. You can export data from Azure onto a Snowball device and ship it to AWS to import. This avoids long upload times and is highly secure.
• Open-source tools: There are also tools like Rclone (an open-source utility) which can sync data from Azure Blob Storage to Amazon S3. AWS’s Prescriptive Guidance even provides patterns for using Rclone to migrate blob data. Rclone can be run on an AWS EC2 instance to pull from Azure and push to S3, and it handles encryption and checksums for data integrity.

Throughout the transfer, ensure data is encrypted (Azure storage and AWS S3 both support encryption). Validate data at the destination to make sure everything arrived intact before you decommission the Azure copies.

3. “Will AWS end up costing more than Azure?” – Cost anxiety is common when changing platforms. It’s true that cloud bills can grow if not managed, but AWS offers many tools to equal or lower your costs compared to Azure, especially if you optimize correctly. As noted earlier, AWS has more discount programs (Savings Plans, Spot instances) which, if utilized, can make running equivalent workloads cheaper on AWS in some cases. One key is to right-size your AWS resources during or after migration – often, you discover that your Azure VMs were over-provisioned, and you can choose smaller or fewer AWS instances to do the same job. Also, consider the licensing: if you run Windows or SQL Server, you’ll need to account for license costs on AWS (you can bring your own licenses or use AWS’s license-included options). To avoid any billing surprises, take advantage of AWS Cost Explorer and set up AWS Budgets alerts in your new AWS account. These will notify you if spending starts to exceed thresholds you define. Real-world outcome: many companies find that after migrating, with proper governance, they reduce IT costs or at least get more value for the same spend. (One study found 30-40% TCO savings by moving workloads to public cloud, but results vary by case.) The bottom line: AWS can be very cost-competitive, but it requires active cost management – a practice you should maintain regardless of cloud platform.

4. “Are AWS services compatible with our applications? What about reconfiguring our apps?” – Compatibility is a critical consideration. Most common application stacks (Linux or Windows VMs, Docker containers, web frameworks, databases) run just as well on AWS as on Azure, since both are general-purpose clouds. However, any Azure-specific PaaS services will need to be addressed. For example, if your application uses Azure Functions, you’d switch to AWS Lambda or run those functions in an EC2 instance or container. If you rely on Azure-specific APIs, you may need to update those portions to call AWS APIs. Workload compatibility should be evaluated in the planning phase – identify if your apps require refactoring. In many cases, the migration can start with a straight rehost (just move VMs over) to ensure everything continues to run the same on AWS. Post-migration, you can gradually modify the apps to better fit AWS (for instance, using S3 for file storage instead of Azure Files, etc.). Testing is your friend here: in a pre-production environment on AWS, deploy your application and see if anything breaks or behaves differently. Common adjustments include configuration changes (like connection strings pointing to new database endpoints on AWS). Also note, if you have software licenses tied to Azure, you might need to obtain equivalent licenses for AWS (or use AWS Marketplace images). The good news is most popular third-party platforms (databases, OS, enterprise software) are supported on AWS. And AWS’s documentation often has guides for migrating specific technologies (for example, migrating .NET applications from Azure App Service to AWS Elastic Beanstalk). With careful planning and perhaps some code tweaks, your applications should run as well or better on AWS.

5. “How do we manage the team’s learning curve and operations on AWS?” – Adopting a new cloud means your IT team will be using new tools and consoles. This is a valid concern – team productivity can dip during the transition if not addressed. To mitigate this:

• Start training early: Enroll your team in AWS training courses or workshops while planning the migration. Even a basic AWS overview can familiarize them with key concepts (EC2, S3, VPC, etc.).
• Leverage AWS’s documentation and support: AWS has extensive documentation and an active support ecosystem (forums, knowledge base). Encourage the team to use these resources when encountering issues.
• Consider hybrid experts: If possible, involve engineers who have experience in both Azure and AWS to bridge knowledge gaps. If you don’t have any, consulting partners like Cloudvisor (an AWS partner) can provide guidance during the migration and even manage AWS operations temporarily as your team ramps up.
• Use managed services where feasible: AWS managed services (like RDS for databases, AWS Managed Microsoft AD for identity, etc.) can offload some complexity since AWS handles a lot of the maintenance. This reduces the amount of new skills your team must immediately master.
• Post-migration, consider an AWS Well-Architected Review or support plan to get feedback on how your environment is configured and ensure best practices. This kind of review can highlight if there are any misconfigurations (security or performance) after the move, which your team can learn from and adjust.

6. “What if something goes wrong? Is there a fallback?” – It’s wise to have a rollback plan. In many Azure-to-AWS migrations, the Azure environment is left intact until the AWS environment is confirmed to be running smoothly. If a critical issue arises on AWS, you can temporarily revert traffic back to Azure while you resolve it. Using infrastructure-as-code (IaC) to set up AWS can also help – because if you need to tweak something, you can adjust the code and redeploy rather than clicking around. Back up all data before migrating and consider keeping data in sync until cutover (especially for databases). The goal is that if AWS has a problem, you haven’t burned the ships behind you. In practice though, with proper testing, full rollbacks are rarely needed; more common is to fix forward on AWS for any minor post-migration issues.

By anticipating these common questions and challenges, you can address them proactively in your migration plan. Every cloud migration has hurdles, but thousands of companies have successfully transitioned from Azure to AWS by carefully managing downtime, securing data transfer, controlling costs, ensuring compatibility, and preparing their teams. In the next section, we’ll outline the concrete steps to execute the migration, building on the planning and preparation we’ve discussed.

Step-by-Step Azure to AWS Migration Process

Once you’ve prepared and planned, it’s time to execute the migration. Below is a step-by-step process for migrating from Azure to AWS, covering the major phases and actions:

1. Make a Detailed Migration Plan – Planning Phase

Begin with the plan you’ve crafted. Clearly define which workloads are moving and in what order. Set success criteria for each (e.g., “Application X should run on AWS with response time Y and all data migrated”). Choose the migration strategies (rehost, replatform, etc.) for each workload. It’s also important to identify stakeholders and communication channels – for instance, who will communicate status to leadership, and how you’ll coordinate the Azure and AWS teams. Address potential risks here: decide on maintenance windows for cutovers, and have a rollback plan documented (as discussed above). Use AWS Migration Hub or a project management tool to track progress on each component. Essentially, this step sets the stage and ensures everyone knows the game plan before touching any live systems.

2. Set Up Your AWS Environment (Accounts & Landing Zone) – Preparation Phase

If you haven’t already, create your AWS account(s). Large organizations might use multiple AWS accounts for isolation (via AWS Organizations), whereas smaller ones may use a single account with multiple VPCs. Configure the foundational things: IAM users/roles, network topology (set up your VPCs and subnets analogous to your Azure Virtual Networks), security groups (analogous to Azure NSGs), and basic monitoring. AWS offers a concept called a Landing Zone – a pre-configured, secure baseline environment for new workloads. You can use AWS Control Tower to automate the setup of a landing zone with best practices (for example, it can create separate accounts for dev/test/prod, set up guardrails, etc.). Establish connectivity: if you need a VPN or Direct Connect between your datacenter (or Azure) and AWS, set that up now. This will be useful for migrating data and for hybrid operation during transition. Essentially, this step is about getting AWS ready to receive your workloads in a well-governed manner (think of it as laying the foundation and building the empty rooms where your servers and data will live).

3. Transfer Data from Azure to AWS – Migration Phase: Data

Data migration is often the first tangible migration activity, since you’ll want databases and storage moved over before switching the apps. Depending on the volume and requirements, choose a data transfer method:

• Use AWS DataSync to copy data from Azure Blob or Files into Amazon S3 or EFS. DataSync is ideal for automating and accelerating transfers; you deploy an agent in Azure and it handles one-way syncs.
• For databases, consider the AWS Database Migration Service (DMS). DMS can connect to an Azure SQL Database or other database engines and migrate them into the AWS equivalent (e.g., Amazon RDS for SQL Server or Aurora for PostgreSQL/MySQL). DMS even supports ongoing replication to minimize downtime for cutover.
• If migrating a large amount of storage with slow connectivity, use AWS Snowball as discussed (export from Azure, import to AWS).
• Establish a Direct Connect link for high-throughput, low-latency transfer if available.
• Manually export/import smaller datasets where applicable (for example, take a backup of an Azure SQL DB and restore it to SQL Server on an EC2 or RDS in AWS).
• Validate data integrity after transfer. Verify file counts, run checksums or sample records in databases to ensure nothing is missing or corrupted during transit.

At this stage, you might run components in parallel: for example, set up your AWS database and keep it in sync with Azure until cutover day.

4. Migrate Applications and Servers – Migration Phase: Compute

With data in place, you can migrate the application servers and services. For a rehost (lift-and-shift) approach, this means copying Azure VMs over to AWS:

• AWS Application Migration Service (MGN): This service can streamline moving VMs. You install an agent on your Azure VM (or give it access), and AWS MGN will replicate the live server (OS, system state, and data) to AWS continuously. When ready, it can launch an EC2 instance from that replicated image. This approach automates a lot of the VM conversion process (handling differences between Azure and AWS hypervisors). It’s great for migrating dozens of VMs with minimal hassle.
• Manual VM Migration: Alternatively, you could export Azure VMs (e.g., as VHD images) and then import them into AWS (as AMIs or attached volumes for EC2). AWS has an import service for VM images as well. However, this is more manual and usually only used if MGN isn’t suitable.
• Platform-specific migrations: If you are replatforming, perform those changes now. For instance, if moving an Azure App Service web app, you might deploy it to AWS Elastic Beanstalk or as containers in Amazon ECS/EKS. If migrating Azure Functions to AWS Lambda, rewrite the function code accordingly and set up the triggers in AWS. These changes should be tested in advance.
• Switch out services: Redirect application dependencies to AWS resources. For example, point your application to the new database on AWS rather than the old Azure one, to the S3 bucket instead of Azure Blob, etc. Many migrations do a trial cutover where the app is run in AWS, connected to AWS data, in a staging environment to ensure everything works.
• Infrastructure as Code: Wherever possible, use IaC tools (CloudFormation, Terraform) to provision AWS resources for consistency and repeatability, especially for setting up multiple environments.

Tip: Start with less critical applications to validate your migration approach, then proceed to mission-critical ones. Also, ensure you migrate ancillary services like batch jobs, scheduled tasks, or monitoring scripts that might have been running in Azure.

5. Test and Validate in AWS – Post-Migration Verification

Once applications are running on AWS, test them thoroughly. This step is crucial to ensure the migration success:

• Test all application functionality as end-users would, to confirm it behaves the same as in Azure.
• Compare performance metrics (page load times, transaction speeds) against baseline; fine-tune AWS instance types or configurations if needed to meet performance benchmarks.
• Security testing: verify that security groups, IAM roles, and other settings are correctly limiting access. For instance, ensure that an EC2-based webserver on AWS isn’t open to the world on an unintended port (carry over equivalent of Azure NSG rules).
• Run AWS’s own auditing tools: services like AWS Inspector can scan EC2 instances for vulnerabilities, and AWS Security Hub can check your AWS environment against best practices. This might catch misconfigurations early (for example, an S3 bucket left public that shouldn’t be).
• Failover testing: if high availability is a concern, test that your multi-AZ or multi-region setups in AWS actually work (e.g., stop one instance to see if the load balancer correctly shifts traffic to another, etc.).
• If possible, run a load test to ensure the new environment can handle production load.

It’s a good idea to have a UAT (User Acceptance Testing) phase where some users or stakeholders try out the system on AWS and sign off that it’s working properly.

6. Cutover and Decommission Azure Resources – Cutover Phase

After successful testing, you can perform the final cutover. This usually involves updating DNS or switching connection endpoints so that users and systems start hitting the AWS environment instead of Azure. Plan this for a low-usage period if possible. Steps:

• Freeze changes on Azure (for example, put Azure databases in read-only or pause writes) to ensure no new data is written there just before cutover.
• Do a final incremental sync of any remaining data that changed since the last bulk transfer (for instance, use DMS to apply final delta of transactions to the AWS database, or an Rclone sync for the latest files).
• Update DNS records, load balancer targets, or application configuration to point to AWS endpoints/IPs.
• Closely monitor the AWS environment and application logs as users begin using the system on AWS.
• Once confident everything is running smoothly on AWS, you can start decommissioning your Azure environment. It’s often wise to do this in phases: maybe turn off (but not delete) Azure VMs for a few days while confirming all data is safely in AWS. After a grace period, you can delete the Azure resources to stop billing. Remember to cancel any Azure-specific services that might not be obvious (e.g., Azure ExpressRoute circuits, Azure Backup vaults, etc., if they’re not needed).
• Finally, close or downsize the Azure account as appropriate. If your organization no longer needs an Azure footprint, you might follow Azure’s process to formally close the account. (Be careful to download any billing reports or compliance data you might need from Azure before closing it.)

7. Post-Migration Updates and Training – Transition to Operations

Migrating the tech is one thing; ensuring your team is fully up to speed in the new environment is equally important. After cutover:

• Update documentation: All runbooks, architecture diagrams, and application documentation should be revised to reflect AWS. This includes updating IP addresses, system descriptions, and troubleshooting guides. For example, if your wiki said “log in to the Azure portal to manage X,” it should now say how to do that in AWS.
• Train staff on AWS operations: Host knowledge-sharing sessions for the team to go over how to handle routine tasks on AWS (deploying a new build, checking logs in CloudWatch, etc.). Ensure your IT support or operations center knows about the new environment too.
• Implement AWS governance: Now that you’re live in AWS, put in place continuous governance. Use AWS Config and CloudTrail to monitor changes. Establish cost monitoring (maybe weekly cost reviews initially). Basically, treat it as a new production environment that needs its own maintenance schedule and oversight.
• Optimize continuously: There might be quick wins to optimize AWS now that you’re running. For instance, you can start using AWS Compute Optimizer recommendations for instance sizing, or convert some instances to spot instances if appropriate. Also consider scheduling non-production environments to shut down during off hours to save money – something you might script with AWS Lambda.
• Leverage AWS support and community: Engage with AWS support if any post-migration issues arise. Also, AWS solutions architects or your AWS account team (if you have one) can often do a post-migration review to suggest improvements. And as mentioned, you can conduct an AWS Well-Architected Review to benchmark your new setup against best practices.

Each of these steps brings you closer to a fully functioning AWS environment that mirrors (or improves upon) what you had in Azure. Depending on the complexity of your infrastructure, some steps may happen in parallel or in iterative waves, but at a high level this covers the journey.

Tools and Services to Simplify the Migration

Migrating between cloud platforms is much easier with the right tools. AWS and third-party vendors provide a range of services to assist with cloud-to-cloud migrations. Here are some essential tools and services for Azure to AWS migration, and how they can help you:

• AWS Application Migration Service (MGN): As mentioned, AWS MGN is a primary tool for automating lift-and-shift migrations. It handles replication of live servers (whether they are physical, VMware, or cloud-based like Azure VMs) into AWS with minimal fuss. If your goal is to rehost with near-zero downtime, MGN is likely your best friend. It supports Windows and Linux machines and orchestrates the conversion to AWS-native formats. Using MGN can save a lot of manual effort and reduce errors compared to doing everything manually.
• AWS Database Migration Service (DMS): DMS helps migrate databases from virtually any platform to AWS. For an Azure to AWS move, it can take an Azure SQL Database or Azure MySQL/PostgreSQL and replicate it into the equivalent Amazon RDS database (or even a target running on EC2). DMS supports continuous replication, so you can keep your source and target DB in sync until cutover. It also can do transformations on the fly (with the SCT – Schema Conversion Tool – if moving between different DB engines). This is extremely useful if you want to migrate with minimal downtime and ensure data consistency.
• AWS DataSync: DataSync is ideal for transferring large files or object storage contents between Azure and AWS. Suppose you have terabytes of data in Azure Blob Storage; DataSync can move that to an Amazon S3 bucket efficiently, handling multipart transfers, retries, and verification. You deploy the DataSync agent in Azure, connect it to your storage account, and then the service copies data over a network connection to AWS. It’s typically faster and easier than writing your own scripts or using generic tools because it’s optimized for these kinds of transfers. DataSync also supports NFS/SMB (useful if you have file shares to migrate).
• AWS Snowball (Edge): For offline data transfer, AWS Snowball devices can be a game-changer. If you have, say, 50 TB of archival data in Azure that would take too long to upload, you can download it to local storage and then copy to a Snowball device. AWS will load that data into S3 for you after shipping. This can be part of your strategy if network bandwidth is a limiting factor. Snowball can also bring compute capabilities (Snowball Edge can run EC2 instances or Lambda functions on-premise) which is sometimes used to pre-process or encrypt data before import.
• Azure Migrate Toolset: It may sound counterintuitive, but Azure’s own migration tooling can be repurposed to some extent. The Azure Migrate hub primarily targets Azure as a destination, but it can perform discovery of your on-prem or other environments. Some companies have used Azure Migrate’s assessment tool to get a report on their workloads (like sizing and usage data), then use that info to plan moves to AWS. Additionally, Azure’s tool for database migration could be used to export a database which you then import to AWS. So, if you’ve already invested in Azure’s migration tools, you might extract whatever data and analysis you can from them to inform your AWS migration.
• Third-Party Migration Tools: Aside from cloud-native tools, there are vendors like CloudEndure (now part of AWS) which historically provided migration services similar to AWS MGN, Corent SurPaaS, Racemi, etc. Some of these tools can facilitate cross-cloud migration by automating VM image conversions, network setup, etc. For example, CloudEndure (prior to AWS acquisition) was used to migrate VMs from any infrastructure to any cloud. Now AWS MGN has replaced CloudEndure for most uses under the AWS umbrella. Still, if you have a unique scenario, exploring third-party solutions might fill a gap.
• Infrastructure as Code (IaC): Tools like Terraform or AWS CloudFormation don’t move things for you, but they are invaluable in setting up the target environment. During migration, you can use Terraform (which has providers for Azure and AWS) to systematically replicate resources. For instance, you could write a Terraform script that reads some settings from your Azure deployment (like the list of VMs, their specs) and then spins up analogous EC2 instances on AWS. This can ensure consistency and save time, especially if you need to repeatedly test the migration in dev/test environments before doing production.
• Monitoring and Logging Tools: When operating across Azure and AWS during migration, having a unified view helps. Services like Datadog or New Relic can ingest metrics and logs from both clouds, so you can monitor the Azure environment and AWS environment side by side. This can be useful to compare performance or to catch issues early (e.g., if after migration, an app on AWS is throwing more errors, you’d see it in one dashboard). While not a migration tool per se, it’s part of the toolset to ensure a smooth transition.

In summary, you have a robust toolkit at your disposal for cloud migration. AWS’s native migration services cover most needs for moving servers, databases, and data with minimal disruption. By leveraging these migration tools, you significantly reduce the manual labor involved in reconfiguring machines or moving files. They also add reliability – knowing that your data transfer is verified, or your VM conversion is handled by proven software, provides peace of mind. Combine these tools with strong planning, and your Azure to AWS migration will be much more streamlined.

(For a more detailed look at specific migration tools and programs, you might read AWS’s official guide or check out Cloudvisor’s article on “AWS vs Azure: Decoding the Key Differences” which, among other things, touches on how each cloud approaches enterprise needs, or our guide on leveraging programs like AWS SMP for cost-effective migrations.)

Conclusion

Migrating from Azure to AWS is a journey that can unlock new efficiencies, but it requires strategic planning and execution. In this guide, we’ve explored the benefits of moving to AWS (from cost savings and global infrastructure to service breadth and security), outlined how to plan an Azure to AWS migration strategy step by step, addressed common concerns (downtime, cost, compatibility, and more), and walked through a detailed migration process with best practices at each stage. With the help of specialized AWS migration tools and services, you can greatly simplify the heavy lifting of transferring data and workloads.

The key to success lies in preparation: understand your current environment, set clear goals, involve the right people, and choose the right tools. Test thoroughly at each phase and don’t hesitate to take a phased approach. Many organizations have made this switch successfully – including those seeking improved performance and innovation by tapping into AWS’s capabilities. By following the strategies in this guide, you’ll be well-equipped to join them.

Ready to take the next step in your cloud journey? If you’re considering or actively planning an Azure to AWS migration, reach out to our team at Cloudvisor. We specialize in AWS migrations and can provide a personalized roadmap, hands-on assistance, or even free migration programs for eligible startups.