Dribbble
Moving away from Amazon Web Services is a massive operational headache. You have petabytes of data locked in specific storage tiers. Your engineering team spent years writing custom CloudFormation scripts. Unplugging all of that and moving it to Microsoft requires serious financial justification.
We operate as a software development company helping enterprises untangle these massive infrastructure knots. Microsoft usually wins these contracts through aggressive enterprise licensing agreements. If your company already pays heavily for Office 365 and Windows Server licenses, Azure suddenly becomes incredibly cheap. You get massive discounts that Amazon simply will not match.
You still have to pay the exit tax. AWS charges you data egress fees to pull your files out of their data centers. You have to calculate that exact penalty before you sign any new vendor contracts. Moving ten terabytes over the public internet costs real money.
You need a clear technical blueprint to survive the move. A blind lift-and-shift approach will destroy your budget.
The Core Compute Layer Translation
An accurate AWS to Azure service mapping starts with the servers. You map AWS EC2 to Azure Virtual Machines. The marketing names change, but the physical reality remains exactly the same. You rent CPU cycles on someone else’s hardware.
You cannot just match an AWS t3.medium directly to an Azure B-series VM and expect identical performance. AWS uses the Nitro system for virtualization. Azure uses a heavily modified Hyper-V architecture. They handle memory swapping and network bursts differently.
You must run synthetic load tests on the new Azure instances. Your team needs to verify that your specific application code runs efficiently on the new hypervisor.
Serverless architectures require a different mindset. You map AWS Lambda to Azure Functions. Both platforms execute code in response to events. Both charge you strictly by the millisecond of active compute time. Azure Functions integrate deeply with the rest of the Microsoft ecosystem, giving you native bindings to storage accounts and message queues. You write less boilerplate code to move data around.
Managing The Storage Transition Safely
Storage looks cheap until you try to move it. You map AWS S3 to Azure Blob Storage. Both services offer hot, cool, and archive storage tiers.
You need to audit your AWS S3 buckets before you start copying files. Most companies hoard useless log files and old database backups for years. You burn cash if you migrate garbage data. Delete the dead files on AWS first.
Once your buckets are clean, you map your access policies. AWS uses IAM policies attached to S3 buckets. Azure uses Shared Access Signatures and Role-Based Access Control on Blob containers. Your developers must rewrite the authentication code inside your applications to generate these new security tokens.
For block storage attached to your servers, you map AWS Elastic Block Store (EBS) to Azure Managed Disks. Pay close attention to the IOPS ratings. An under-provisioned Azure Managed Disk will throttle your database read speeds and bring your application to a halt.
Mapping The Database Infrastructure
Database migration kills most projects. A direct AWS services to Azure services comparison shows fundamentally different billing and scaling models.
You map AWS RDS to Azure SQL Database for standard relational workloads. Microsoft owns the SQL Server engine. Running it on Azure costs significantly less than running it on AWS because of the Azure Hybrid Benefit. You apply your existing on-premises licenses directly to your cloud instances.
For highly available, auto-scaling relational clusters, you map AWS Aurora to Azure SQL Database. Specifically, you use the Azure SQL Hyperscale tier. It separates the compute nodes from the storage layer, allowing your database to grow to 100 terabytes rapidly.
Moving NoSQL databases requires careful planning. You map AWS DynamoDB to Azure Cosmos DB. They both handle massive horizontal scale and global distribution.
Cosmos DB bills using Request Units. DynamoDB uses Read and Write Capacity Units. If your developers write bad JSON queries in Cosmos DB, your Request Unit consumption spikes wildly. You will drain your IT budget in a single weekend. Your team must pick high-cardinality partition keys to keep those query costs flat.
If you are dealing with heavily outdated infrastructure alongside these databases, you should read our specific guide on migrating a lagacy windows application to modern .net. Upgrading the application framework at the same time often simplifies the database transition.
Rebuilding The Network Perimeter
Your virtual network dictates your security posture. You map AWS Virtual Private Cloud (VPC) to Azure Virtual Network (VNet).
AWS uses Security Groups applied directly to network interfaces. Azure uses Network Security Groups (NSGs) applied to either subnets or individual network interfaces. You should apply your NSGs at the subnet level. It keeps your routing rules clean and prevents configuration drift.
Traffic routing requires a strict AWS and Azure service comparison. You map AWS Route 53 to Azure DNS. You map AWS CloudFront to Azure Front Door.
Front Door acts as your global load balancer and content delivery network. It catches user traffic at the edge of Microsoft’s global network and routes it privately to your application servers. It stops DDoS attacks before they ever reach your core infrastructure.
Identity And Access Management
Security roles do not translate perfectly between clouds. You map AWS Identity and Access Management (IAM) to Microsoft Entra ID.
AWS IAM uses highly granular, JSON-based policy documents. Entra ID relies heavily on predefined roles and groups. You assign a user to a group, and that group gets specific permissions across your Azure subscriptions.
Do not try to recreate every single custom AWS IAM policy in Azure. Start fresh. Audit your engineering team and assign them the absolute minimum permissions required to do their jobs. Entra ID Conditional Access lets you block logins based on location or device compliance, adding a massive layer of security that AWS struggles to match natively.
The DevOps And Pipeline Transition
Your deployment pipelines must move before your application code moves. Your engineers cannot ship updates if their tools live in the wrong cloud.
You map AWS CodePipeline and CodeBuild to Azure DevOps or GitHub Actions. Microsoft owns both of those platforms. They integrate perfectly with Azure App Service and Azure Kubernetes Service.
Building these pipelines requires deep platform knowledge. You should hire a dedicated aws migration agency to construct your deployment tracks. Do not let your internal team guess at the YAML syntax. A badly configured pipeline will deploy broken code to your production environment.
We frequently provide AWS consulting to audit existing CI/CD setups. We identify the bottlenecks in your AWS build process and eliminate them entirely when writing the new Azure pipelines.
The Step By Step Execution Process
A successful cloud migration follows a rigid operational script. You never move everything at once.
Phase one: Discovery and assessment
Install the Azure Migrate appliance inside your AWS environment. Let it run quietly for thirty days. It tracks every inbound and outbound network connection across your EC2 instances.
It builds a complete AWS Azure migration service map. It tells you exactly which servers talk to each other. This data dictates your migration waves. You group highly connected servers together so you do not accidentally introduce massive network latency by splitting them across two different cloud providers.
Phase two: The landing zone
You build your Azure foundation before moving a single byte of data. You set up your management groups, configure your Entra ID tenant, and deploy your hub-and-spoke virtual networks.
This landing zone acts as the secure perimeter for your incoming applications. You configure Azure Policy to enforce strict geographical rules. If your compliance team mandates that user data must stay in Europe, Azure Policy physically blocks developers from spinning up databases in American data centers.
Phase three: Data replication and cutover
You establish a private VPN or ExpressRoute connection between AWS and Azure. You use Azure Site Recovery to continuously sync your EC2 virtual machines over to Azure.
Your application stays online in AWS while the data copies in the background. On the night of the cutover, you put your AWS application into read-only mode. You let the final data sync complete. You update your DNS records to point to the new Azure endpoints.
You turn the Azure environment live.
Modernizing Client Endpoints Post Migration
Moving your backend infrastructure to Azure gives you a stable, highly scalable foundation. Once that foundation is secure, you overhaul your client-facing applications.
Your web interfaces and mobile tools need to connect cleanly to your new Azure APIs. We handle complete mobile app development for enterprise teams. We build fast, responsive clients that consume data directly from your new Azure Cosmos DB and SQL instances.
You can lower your engineering costs by using a multiplatform mobile app development strategy. You write a single React Native or Flutter codebase that deploys natively to both iOS and Android. Your new Azure backend only has to serve one unified API endpoint.
You can also start wiring up advanced intelligence features. Moving to Microsoft gives you direct access to Azure OpenAI. We track closely how ai improving mobile applications changes consumer expectations. You can feed your migrated corporate data into secure language models to give your users instant, intelligent search results right on their phones.
Finalizing Your Cloud Architecture
Your AWS Azure product mapping dictates your long-term operational costs. If you just copy your messy AWS architecture directly into Azure, you will pay exactly the same massive monthly bills.
You migrate to clean up technical debt. You rip out expensive virtual machines and replace them with cheap serverless functions. You drop overpriced databases for managed Azure alternatives.
Keeping your backend completely decoupled from your frontend protects your investment. Following the future of web development means building strict API boundaries. If Microsoft changes their hosting models in five years, your client applications will never even notice the difference.
Cloud migrations break companies that guess at the details. Map your dependencies carefully. Calculate your AWS egress fees down to the dollar. Test your new Azure database queries under heavy synthetic loads before you ever change your DNS records.
Estatic Infotech builds cloud systems that scale cleanly and respect your profit margins. Reach out to our engineering team today to audit your AWS infrastructure and build a mathematically sound migration path to Microsoft Azure.
Apple will reject your app if you force users to create an account before showing them any value. Google will reject your app if your privacy policy is missing a specific legal clause.
Managing these rejections takes time. When you use a unified codebase, you push a single fix for a compliance issue and submit it to both stores simultaneously. You avoid coordinating two separate release branches.