Get alignment early to build AI apps and agents and sell on Marketplace
Frontier firms are pulling ahead. The data is clear why. According to Microsoft research of Frontier firms: 71% of leaders say their company is thriving, compared to just 39% of workers globally, 93% are optimistic about future work opportunities, 55% say they’re able to take on more work, versus 25% globally. But the difference isn’t experimentation with AI. It’s execution. Work Trend Index Annual Report, 2025 How getting business and technical alignment with AI development helps Frontier firms are succeeding because they align business intent, technical design, and security expectations before building AI apps and agents. They don’t treat alignment as a workshop or a slide deck. They treat it as a prerequisite to building agents that actually work, scale, and earn trust. Microsoft helps you adopt this same approach through structured guidance in App Advisor, AI envisioning resources, and practical checklists designed to keep teams aligned from design through deployment. Why alignment separates Frontier firms from the rest AI apps and agents increasingly operate inside critical business workflows. That raises the bar. When alignment is missing, teams often ship agents that technically function but fail in production due to security gaps, unclear ownership, or mismatched expectations around outcomes. Teams that align early are better positioned to: Move faster through build by eliminating ambiguity, Build agents that reliably perform the job they’re designed to do, Embed security, governance, and trust by design, not as an afterthought, Reduce redesign cycles caused by unclear requirements or late-stage constraints. This is where guidance-first approach from Microsoft plays a critical role. How App Advisor helps teams align before they build App Advisor is intentionally designed to help teams put an alignment framework together at the start. To move faster later. App Advisor gives you: Tools to help your business get an AI Center of Excellence, Systems, like Azure Essentials and Cloud Adoption Framework, Checklists for every step of the way, so that teams stay informed, Toolkits and services that build in answers to friction that your team can leverage. These shared starting points helps ensure what teams build reflects real business needs and can be deployed responsibly. Using AI envisioning sessions to align outcomes The Microsoft AI envisioning sessions complement App Advisor by helping teams translate strategy into execution. The Business–Technical Alignment Checklist for Microsoft Foundry helps teams stay synchronized as they build. It ensures architecture, cost, security, and delivery choices support a clear business outcome—not just technical success. This checklist reinforces practices like: Defining shared success metrics and KPIs, Setting joint budget guardrails and cost visibility, Establishing cross-functional cadence and governance, Planning for integration testing and real-world workflows, Using a shared project workspace as a single source of truth. This alignment reduces late-stage friction when you’re preparing to publish, co-sell, or scale. This translates into offers that are easier to describe on Marketplace, more likely to attract customers, and better for those customers to deploy. Moving from aligned design to confident build to sales growth After alignment is established, teams can move into build with momentum. App Advisor showcases development toolkits, SDKs, templates, and reference architectures that reflect the decisions already made during design. That continuity matters. It keeps teams focused on execution instead of re-litigating fundamentals mid-build. Alignment isn’t a meeting. It’s a system. Microsoft provides the structure to support it. Start aligning today to sell more tomorrow Get resources to help your teams align and keep in step in App Advisor.Build an AI app or agent faster to sell on Marketplace with App Advisor
Jump right to the step-by-step curated guidance for building a well-architected app in App Advisor The development of AI apps and agents is moving fast. The data backs it up: The AI platform of choice: 90% of Fortune 500 companies use Microsoft AI, Development lifecycles speed up: Teams see up to 46% faster development with Azure, Companies realize great ROI: AI apps and agents realize an average of 90% ROI. The opportunity is real, but speed alone isn’t enough. To turn momentum into a scalable, sellable solution, software companies need a clear path from idea to architecture to Microsoft Marketplace readiness. How to build an AI app or agent and sell it on Marketplace Microsoft Foundry provides the platform to build AI apps and agents. App Advisor provides the structure, guiding you through the decisions that matter early. So, you can move fast without creating rework later. When paired with focused build and alignment checklists, App Advisor helps you ship faster and prepare your solution for the Marketplace from day one. Here’s how App Advisor, paired with material developed from the popular AI Envisioning sessions, helps you build with speed and Marketplace readiness in mind. App Advisor gives you a clear starting point to build AI apps and agents App Advisor is tailored specifically to remove ambiguity. Instead of guessing where to begin, you’re guided through key build decisions, based on five critical pillars: Security Reliability Cost optimization Operational excellence Performance efficiency These pillars are more than theory. They help you and your team think through pricing models, identity and access, resiliency, scaling, and operational integration early: before code hardens and changes get expensive. By anchoring your build in these principles, you create a foundation that supports both rapid development and future Marketplace requirements. Design well, build fast: Create an Agent MVP in 30 days After your architecture is defined, the next challenge is execution speed. The Create an Agent MVP in 30 Days checklist turns Microsoft Foundry best practices into an actionable build plan. It’s organized around the same well-architected pillars, making it easy to move from design to implementation without losing alignment. This checklist helps you: Embed security controls like encryption, RBAC, and managed identity from day one, Design for reliability with stateless services, health checks, and graceful fallback, Right-size performance and compute so you don’t overbuild the MVP, Control costs early with monitoring, budgets, and automation, Set up DevOps and CI/CD to support fast iteration. The result is a working agent that’s intentionally scoped, production-aware, and easier to evolve into a commercial offering. Built to move fast, ready to be sold at scale Used together, App Advisor, the 30-day to an MVP checklist, and the AI Envisioning sessions give you a repeatable path: Start with architecture clarity, Build an MVP quickly and responsibly, Stay aligned on Marketplace outcomes. You’re not just shipping an AI app or agent. You’re building a solution designed to be deployed, sold, and supported for your target customer. And designing well with solid core principles can help build a solid foundation for your Marketplace success. Ready to build faster with Microsoft Foundry? Explore App Advisor for step-by-step guidance to quickly design well-architected apps. Want to get development templates to start designing in minutes? View the Quick-Start Development Toolkit library for AI apps and agents. See the difference when you build with the proven framework of Microsoft Foundry and selling well-architected apps and agents in Marketplace.Migrating your AWS offer to Microsoft Marketplace - AWS to Azure service comparisons
As an Independent Software Vendor (ISV), expanding your Marketplace offer's reach beyond AWS Marketplace by replicating to Microsoft Marketplace offers exciting opportunities to grow your customer base. With millions of customers across a global network of businesses and industries, Azure presents a thriving platform to enhance your app’s visibility and functionality. This post is part of a series on replicating apps from AWS to Azure. View all posts in this series. Boost your growth and access more customers by replicating your AWS app to Azure and selling through Microsoft Marketplace. This guide will compare commonly used AWS and Azure components, highlighting differences, to help you replicate your app quickly and easily to prepare it for publishing on Microsoft Marketplace. Future posts will dive deeper into each component area. To ensure a seamless app replication, start by reviewing the marketplace listing requirements. Understanding the key differences between AWS and Azure will help you transition and optimize performance on Azure while benefiting from its unique advantages. This guide will outline these differences, highlight similar services, and offer steps for a seamless replication or migration. You can also join ISV Success to get access to over $126K USD in cloud credits, AI services, developer tools, and 1:1 technical consults to help you replicate your app and publish to Marketplace. The benefits of replicating or migrating to Microsoft Marketplace Migrating to Marketplace unlocks a wealth of opportunities for ISVs. The Azure ecosystem offers several advantages, including: Global reach: Azure’s vast global network of data centers ensures high availability and low-latency access to your application for customers worldwide. Cost efficiency: Azure’s flexible pricing models and cost management tools allow ISVs to optimize their cloud spending. Scalability: With Azure’s powerful compute and storage options, you can scale your application effortlessly to accommodate growing demand. Security and compliance: Azure’s comprehensive security tools and certifications help you meet industry-specific compliance standards, ensuring that your application is secure and trusted. Meet where your customers are: Deploy into customer subscriptions, making your solution more integrated to customer workload. AWS vs. Azure AWS and Azure are the top cloud platforms with diverse services for developers and businesses. Below, we will highlight key areas where AWS and Azure differ—and how to leverage Azure services—when moving your Marketplace offer from AWS to Microsoft Marketplace. Microsoft Marketplace capabilities In Azure, ISVs can leverage metered billing to charge customers based on actual usage, similar to AWS's pay-as-you-go model. This flexible pricing model is ideal for SaaS solutions. Partner Center offers tools for setting pricing models, tracking usage, and adjusting billing. It also provides anomaly detection to help partners identify unexpected usage and ensure transparent billing. When creating SaaS offers in Marketplace, ISVs can define plans with various pricing strategies, such as usage-based or flat-rate billing. These plans, or SKUs, can be customized through free trials, BYOL (Bring Your Own License), or vCPU-based pricing for virtual machines. Both Azure and AWS allow flexible, metered billing based on usage. Azure also provides the ability to set customer discounts or negotiated pricing. Using Partner Center, you can configure and manage these offerings, providing flexibility for customers and partners to scale as needed. Like AWS Control Tower, Azure Lighthouse enables service providers to manage multiple customer Azure environments securely and at scale, offering enhanced visibility, control, and automation. For usage-based monthly billing, you can choose from predefined or custom pricing options (using metered billing APIs). Predefined options like per core, per node, or per pod let Microsoft bill customers based on hourly usage, billing them monthly. Learn more about usage-based pricing here: Setting Plan Pricing. Mapping AWS services to Azure services Your Marketplace offer may use multiple AWS services, and you can build the same offer using Azure services. However, this requires careful mapping to ensure your application functions seamlessly in the Azure environment. Here’s a quick overview of how popular AWS services map to Azure:: Networking: AWS VPC → Azure Virtual Networks (VNets) Compute Services: AWS EC2 → Azure Virtual Machines (VMs), Azure App Services (for web apps) Storage: Amazon S3 → Azure Blob Storage, Azure Data Lake Storage (for big data) Identity Management: AWS IAM → Entra ID Containers: EKS and Elastic Beanstalk → AKS and Azure App Services Serverless: AWS Lambda → Azure Functions Databases: Amazon RDS → Azure SQL Database, Azure Cosmos DB (for NoSQL) Azure for AWS professionals provides you with a more comprehensive mapping of different services. Let's take a deeper look into each of these areas. Cloud architecture and networking One of the primary differences between AWS and Azure lies in their cloud architecture and networking models. AWS uses Virtual Private Clouds (VPCs) to create isolated networks, while Azure employs Virtual Networks (VNets). Both services perform similar functions, but they have different terminologies and setups. For instance, in Azure, you'll be working with VNet Peering, Network Security Groups (NSGs), and Azure VPNs for secure networking. The goal is to map your AWS VPC setup to Azure VNets with ease. AWS needs a Nat Gateway for egress access whereas Azure does not need a Nat Gateway for default egress. AWS Subnets are pinned to Availability Zones (AZs) whereas Azure Subnets span across the AZs. Compute services: EC2 vs. Virtual Machines (VMs) AWS EC2 instances are one of the most widely used compute services, allowing you to run applications on virtual servers. In Azure, the equivalent service is Azure Virtual Machines (VMs). While both offer scalable compute resources, the key differences are in the range of VM sizes, configurations, and the management interface. When migrating from AWS EC2 to Azure VMs, it's important to assess the appropriate Azure VM sizes and configurations that match the performance of your EC2 instances. Additionally, Azure VMs support Azure Resource Manager (ARM) templates, which provide more automation for resource management. For those who have utilized EC2's Auto Scaling feature, Azure provides similar functionality through Azure Scale Sets. Storage: S3 vs. Blob Storage For object storage, AWS uses Amazon S3, while Azure uses Azure Blob Storage. Both services serve the same purpose — storing large amounts of unstructured data — but the underlying configurations, security features, and cost structures differ. While migrating from S3 to Blob Storage, it’s important to review your storage needs and adjust your application accordingly. Azure Blob Storage offers Cool and Archive tiers, which can be a great way to optimize storage costs for infrequently accessed data, and Azure's data redundancy options ensure high availability and durability. The Azure Storage Explorer tool also makes it easier for ISVs to manage their data after migration. Identity and Access Management (IAM) & billing: IAM vs. Entra ID IAM services on AWS and Azure differ in how they manage roles and permissions. AWS uses IAM for users, roles, and policies, while Azure uses Entra ID for IAM across cloud services. AWS organizes accounts through AWS Organizations, with IAM used for role-based access control (RBAC) and policies for service access. Azure’s structure involves Subscriptions and Management Groups, with Entra ID managing identity and access. Azure uses RBAC to assign roles at various levels (Subscription, Resource Group, Resource) and Azure Policies for governance and compliance. Azure Entra ID integrates with Microsoft services, like Office 365, SharePoint, and Teams, supporting identity federation, multi-factor authentication, and RBAC for granular permissions. It enhances governance and security across platforms. Azure handles billing management via subscriptions providing access to resources and can be reassigned to new owners. It offers three classic subscription administrator roles for resource access and management for billing and resource access. Container management: Elastic Beanstalk vs. Azure App Services and EKS vs. AKS For containerized applications, AWS offers Elastic Beanstalk for easy application deployment and management. Azure’s equivalent services include Azure App Services for simple web application hosting and Azure Kubernetes Service (AKS) for container orchestration. While Azure App Services is more suitable for traditional web applications, AKS provides a robust and scalable solution for microservices and containerized applications, similar to AWS’s Elastic Kubernetes Service (EKS). ISVs who are accustomed to Elastic Beanstalk for deploying containerized applications will find Azure App Services or AKS a seamless alternative, with Azure offering rich integrations with DevOps pipelines, CI/CD workflows, and container registries. Serverless: AWS Lambda vs. Azure Functions Both AWS and Azure support serverless computing, which allows developers to run code without managing servers. AWS offers Lambda, while Azure offers Azure Functions. Both services allow you to trigger code in response to events, such as file uploads or API calls. The key difference is that Azure Functions integrates deeply with other Azure services, such as Azure Logic Apps and Azure Event Grid. If your application leverages AWS Lambda, you will find that Azure Functions can serve as an excellent equivalent. Azure also provides Durable Functions, which extend Azure Functions for stateful workflows. Migrating from AWS Lambda to Azure Functions typically requires mapping your event-driven functions and configuring their triggers in the Azure ecosystem. Databases: RDS vs. Azure SQL and Cosmos DB When it comes to databases, AWS offers Amazon RDS for relational databases, and Amazon DynamoDB for NoSQL. Azure provides several alternatives, including Azure SQL Database for relational storage and Azure Cosmos DB for NoSQL storage. Both platforms support database scalability, automated backups, and high availability. If you are using Amazon RDS with services like MySQL or PostgreSQL, you can migrate to Azure Database for MySQL or Azure Database for PostgreSQL. Similarly, if you are using AWS DynamoDB, Azure’s Cosmos DB offers a global, scalable NoSQL database with low-latency access. Messaging: AWS SQS vs. Azure Service Bus Messaging services are crucial when your application handles high-throughput, asynchronous communication between different components. AWS offers Simple Queue Service (SQS) for messaging and SNS for pub/sub notifications while Azure offers Azure Service Bus and Azure Event Grid. Azure Service Bus provides similar functionality to SQS but offers additional capabilities like advanced message routing, dead-lettering, and sessions for handling ordered messages. If your application relies on a queuing mechanism for inter-service communication, you’ll want to map AWS SQS to Azure Service Bus. For event-driven architectures, Azure Event Grid can connect different services and trigger actions across Azure services. Security: Protecting your application on Azure When migrating from AWS to Azure, security is paramount. Both platforms offer strong frameworks to protect data, apps, and infrastructure. Azure provides a suite of integrated security services to maintain high security while enabling cloud scalability. AWS offers AWS Shield and WAF for DDoS and web application firewalls, while Azure offers Azure DDoS Protection and Azure Firewall for similar threat prevention. Azure Security Center monitors your security posture, and Azure Sentinel provides cloud-native SIEM (Security Information and Event Management) for threat detection and response. Microsoft Defender for Identity and Azure Entra ID Identity Protection integrate with Entra ID, ensuring your app security is tightly linked to user identity and governance. Compliance: Meeting regulatory standards on Azure Ensuring compliance with industry standards and regulations is crucial for many ISVs. Azure provides a robust compliance framework that aligns with global standards to meet the most stringent requirements. Whether your application deals with sensitive data or operates in highly regulated industries, Azure’s comprehensive compliance offerings can help you achieve the necessary certifications. Azure complies with key standards such as: GDPR HIPAA SOC 1, 2, and 3 ISO 27001 and other ISO standards FedRAMP Azure provides tools like Azure Policy for governance and Azure Blueprints for complex regulatory requirements. It offers a similar set of compliance certifications to AWS, with a stronger integration into Microsoft enterprise tools, easing compliance for businesses in regulated sectors. For apps handling sensitive data, use Azure Security and Compliance Blueprint to ensure regulatory adherence. Azure’s Compliance Manager helps track and manage compliance, simplifying the process of meeting industry standards. Key resources SaaS Workloads - Microsoft Azure Well-Architected Framework | Microsoft Learn Metered billing for SaaS offers in Partner Center Create plans for a SaaS offer in Azure Marketplace Metered billing with Azure Managed Applications Set plan pricing and availability for an Azure Container offer in Microsoft commercial marketplace - Marketplace publisher Configure pricing and availability for a virtual machine offer in Partner Center - Marketplace publisher Overview - CSP marketplace - Partner Center Azure for AWS professionals - Azure Architecture Center Azure networking documentation Microsoft Entra ID documentation - Microsoft Entra ID Azure security documentation Azure compliance documentation Azure Storage Documentation Hub Microsoft Azure container services documentation Azure serverless - Azure Logic Apps Migration examples Get over $126K USD in benefits and technical consultations to help you replicate and publish your app with ISV Success Maximize your momentum with step-by-step guidance to publish and grow your app with App AdvisorMigrating your AWS offer to Microsoft Marketplace - Storage services
For software development companies looking to expand or replicate their marketplace offerings from AWS to Microsoft Azure, one of the most critical steps in replicating your solution is selecting the right Azure storage services. While both AWS and Azure provide robust cloud storage options, their architecture, service availability, and design approaches vary. To deliver reliable performance, scale globally, and meet operational requirements, it’s essential to understand how Azure storage works—and how it compares to AWS—before you replicate your app. Broaden your customer base and enhance your app’s exposure by bringing your AWS-based solution to Azure and listing it on Microsoft Marketplace. This guide will walk you through how Azure storage services compare to those on AWS—spotlighting important differences in architecture, scalability, and feature sets—so you can make confident choices when replicating your app’s storage layer to Azure. This post is part of a series on replicating apps from AWS to Azure. View all posts in this series AWS to Azure storage mapping When replicating your app from AWS to Azure, start by mapping your existing storage services to the closest Azure equivalents. Both clouds offer robust object, file, and block storage, but they differ in architecture, features, and integration points. Choosing the right Azure service helps keep your app performant, secure, and manageable—and aligns with Microsoft Marketplace requirements for an Azure‑native deployment. AWS Service Azure Equivalent Recommended use cases & key differences Amazon S3 Azure Blob Storage (enable ADLS Gen2 for hierarchical namespace + POSIX ACLs) Object storage with strong consistency and tiering (Hot/Cool/Archive). Blob is part of an Azure Storage account; ADLS Gen2 unlocks data‑lake/analytics features. Amazon EFS Azure Files (SMB/NFS) General‑purpose shared file systems and lift‑and‑shift app shares. Azure Files supports full-featured SMB and fully POSIX compatible NFS shared filesystems on Linux. Amazon FSx for Windows File Server Azure Files (SMB) Windows workloads that need full NTFS semantics, ACLs, and directory integration. Use Premium for low‑latency shares. Amazon FSx for NetApp ONTAP Azure NetApp Files Enterprise file storage with predictable throughput/latency, multiprotocol (SMB/NFS), and advanced data management. Amazon EBS Azure Managed Disks (Premium SSD v2 or Ultra Disk for top performance) Low‑latency block storage for VMs/DBs with provisioned IOPS/MBps; choose Premium SSD v2/Ultra for tighter SLOs. Local NVMe on EKS Azure Container Storage Extreme performance for Kubernetes workloads with a familiar cloud-native developer experience Many EBS volumes (fleet scale) Azure Elastic SAN (VMs & AKS only) Pooled, large‑scale block for Azure VMs via iSCSI or AKS via Azure Container Storage; simplifies fleet provisioning and management. Tip: Some AWS services map to multiple Azure options. For example, EFS → Azure Files for straightforward SMB/NFS shares, or → Azure NetApp Files when you need stricter latency SLOs and multiprotocol at scale. Match your use case After mapping AWS services to Azure equivalents, the next step is selecting the right service for your workload. Start by considering the access pattern, object, file, or block, and then factor in performance, protocol, and scale. Object storage & analytics: Use Azure Blob Storage for unstructured data like images, logs, and backups. If you need hierarchical namespace and POSIX ACLs, enable Azure Data Lake Storage Gen2 on top of Blob. General file sharing / SMB apps: Choose Azure Files (SMB) for lift‑and‑shift scenarios and Windows workloads. Integrate with Entra ID for NTFS ACL parity, and select the Premium tier for low‑latency performance. NFS or multiprotocol file workloads: Start with Azure Files (NFS) for basic needs, or move to Azure NetApp Files for predictable throughput, multiprotocol support, and enterprise‑grade SLAs. High‑performance POSIX workloads: For HPC or analytics pipelines requiring massive throughput, use Azure Managed Lustre. Persistent storage for containers: Azure’s CSI drivers brings Kubernetes support for most Azure disk, files, and blob offerings. Azure Container Storage brings Kubernetes support for unique disk backends that are unsupported by the Azure Disks CSI driver, such as local NVMe. Block storage for VMs and databases: Use Azure Managed Disks for most scenarios, with Premium SSD v2 or Ultra Disk for provisioned IOPS and sub‑millisecond latency. For large fleets or shared performance pools, choose Azure Elastic SAN (VMs & AKS only). Quick tip: Start simple—Blob for object, Azure Files for SMB and NFS, Managed Disks for block—and scale up to NetApp Files, Elastic SAN, or Managed Lustre when performance or compliance demands it. Factor in security and compliance Encryption: Confirm default encryption meets your compliance requirements; enable customer‑managed keys (CMK) if needed. Access control: Apply Azure RBAC for role‑based permissions and ACLs for granular control at the container or file share level. Network isolation: Use Private Endpoints to keep traffic off the public internet and connect storage to your VNet. Identity integration: Prefer Managed Identities or SAS tokens over account keys for secure access. Compliance checks: Verify your chosen service meets certifications like GDPR, HIPAA, or industry‑specific standards. Optimize for cost Tiering: Use Hot, Cool, and Archive tiers in Blob Storage based on access frequency; apply Premium tiers only where low latency is critical. Lifecycle management: Automate data movement and deletion with lifecycle policies to avoid paying for stale data. Reserved capacity: Commit to 1–3 years of capacity for predictable workloads to unlock discounts. Right‑sizing: Choose the smallest disk, volume, or file share that meets your needs; scale up only when required. Monitoring: Set up cost alerts and review usage regularly to catch anomalies early; use Azure Cost Management for insights. Avoid hidden costs: Co‑locate compute and storage to prevent cross‑region egress charges. Data migration from AWS to Azure Migrating your data from AWS to Azure is a key step in replicating your app’s storage layer for Marketplace. The goal is a one‑time transfer—after migration, your app runs fully on Azure. Azure Storage Mover: A managed service that automates and orchestrates large‑scale data transfers from AWS S3, EFS, or on‑premises sources to Azure Blob Storage, Azure Files, or Azure NetApp Files. Ideal for bulk migrations with minimal downtime. AzCopy: A command‑line tool for fast, reliable copying of data from AWS S3 to Azure Blob Storage. Great for smaller datasets or scripted migrations. Azure Data Factory: Built‑in connectors to move data from AWS storage services to Azure, with options for scheduling and transformation. Azure Data Box: For very large datasets, provides a physical device to securely transfer data from AWS to Azure offline. Final readiness before marketplace listing Validate performance under load: Benchmark with real data and confirm your chosen SKUs deliver the IOPS and latency your app needs. Lock down security: Ensure RBAC roles are applied correctly, Private Endpoints are in place, and encryption meets compliance requirements. Control costs: Verify lifecycle policies, reserved capacity, and cost alerts are active to prevent surprises. Enable monitoring: Set up dashboards and alerts for throughput, latency, and capacity so you can catch issues before customers do. Key Resources SaaS Workloads - Microsoft Azure Well-Architected Framework | Microsoft Learn Metered billing for SaaS offers in Partner Center Create plans for a SaaS offer in Microsoft Marketplace Get over $126K USD in benefits and technical consultations to help you replicate and publish your app with ISV Success Maximize your momentum with step-by-step guidance to publish and grow your app with App Advisor
Migrating your AWS offer to Microsoft Marketplace - Database services
For software development companies looking to expand or replicate their marketplace offerings from AWS to Microsoft Azure, one of the most critical steps in replicating your solution is selecting the right Azure database services. While both AWS and Azure provide robust managed database options, their architecture, service availability, and design approaches vary. To deliver reliable performance, scale globally, and meet operational requirements, it’s essential to understand how Azure databases work—and how they compare to AWS—before you replicate your app. Broaden your customer base and enhance your app’s exposure by bringing your AWS-based solution to Azure and listing it on Microsoft Marketplace. This guide walks you through how Azure database services compare to those on AWS—spotlighting differences in architecture, scalability, and feature sets—so you can make confident choices when replicating your app’s data layer to Azure. This post is part of a series on replicating apps from AWS to Azure. View all posts in this series. AWS to Azure database mapping When replicating your app from AWS to Azure, start by mapping your existing database services to the closest Azure equivalents. Both clouds offer relational, NoSQL, and analytics databases, but they differ in architecture, features, and integration points. Choosing the right Azure service helps keep your app performant, secure, and manageable—and aligns with Azure Marketplace requirements for an Azure-native deployment. AWS Service Azure Equivalent Recommended Use Cases & Key Differences Amazon RDS (MySQL/PostgreSQL) Azure Database for MySQL / PostgreSQL Fully managed relational DB with built-in HA, scaling, and security. Building Generative AI apps. Amazon RDS (SQL Server) Azure SQL Database or Azure SQL Managed Instance Use Azure SQL Database for modern apps; choose Managed Instance for near 100% compatibility with on-prem SQL Server. SQL Server on EC2 SQL Server on Azure VMs Best for lift-and-shift scenarios requiring full OS-level control. Amazon RDS (Oracle) Oracle Database@Azure Managed Oracle workloads with Azure integration. Amazon Aurora (PostgreSQL/MySQL) Azure Database for PostgreSQL (Flexible Server) or Azure Database for MySQL Similar managed experience for large workloads, consider Azure HorizonDB (public preview)—built on PostgreSQL to compete with Aurora & AlloyDB. Learn more. Amazon DynamoDB Azure Cosmos DB (NoSQL API) Global distribution, multi-model support, and guaranteed SLAs for latency and throughput. Amazon Keyspaces (Cassandra) Azure Managed Instance for Apache Cassandra Managed Cassandra with elastic scaling and Azure-native security. Cassandra on EC2 Azure Managed Instance for Apache Cassandra Same as above; ideal for lift-and-shift Cassandra clusters. Amazon DocumentDB MongoDB Atlas MongoDB on EC2 Azure DocumentDB Azure DocumentDB Azure DocumentDB Drop-in compatibility for MongoDB workloads with global replication and vCore-based pricing. Amazon Redshift Azure Synapse Analytics Enterprise analytics with integrated data lake and Power BI connectivity. Amazon ElastiCache (Redis) Azure Cache for Redis Low-latency caching with clustering and persistence options. Match your use case After mapping AWS services to Azure equivalents, the next step is selecting the right service for your workload. Start by considering the data model (relational, document, key-value), then factor in performance, consistency, and global reach. Building AI apps: Generative AI, vector search, advanced analytics. Relational workloads: Use Azure SQL Database, Azure SQL Managed Instance, or Azure Database for MySQL/PostgreSQL for transactional apps; enable zone redundancy for HA. Review schema compatibility, stored procedures, triggers, and extensions. Inventory all databases, tables, indexes, users, and dependencies before migration. Document any required refactoring for Azure. NoSQL workloads: Choose Azure Cosmos DB for globally distributed apps; select the API (No SQL, MongoDB, Cassandra) that matches your existing schema. Validate data: Model mapping and test migration in a sandbox environment to ensure data integrity and application connectivity. Analytics: For large-scale queries and BI integration, Azure Synapse Analytics offers MPP architecture and tight integration with Azure Data Lake. Inventory all analytics assets, ETL pipelines, and dependencies. Plan for migration using Azure Data Factory or Synapse pipelines. Test performance benchmarks and optimize query plans post-migration. Caching: Azure Cache for Redis accelerates app performance with in-memory data and clustering. Update application connection strings and drivers to use Azure endpoints. Implement retry logic and connection pooling for reliability. Validate cache warm-up and failover strategies. Hybrid scenarios: Combine Cosmos DB with Synapse Link (for Synapse as target) or Fabric Mirroring (for Fabric as target) for real-time analytics without ETL overhead. Assess network isolation, security, and compliance requirements. Deploy Private Endpoints and configure RBAC as needed. Document integration points and monitor hybrid data flows. Factor in security and compliance Encryption: Confirm default encryption meets compliance requirements; enable customer-managed keys (CMK) if needed. Enable Transparent Data Encryption (TDE) and review encryption for backups and in-transit data. Access control: Apply Azure RBAC and database-level roles for granular permissions. Audit user roles and permissions regularly to ensure least privilege. Network isolation: Use Private Endpoints within a virtual network to keep traffic off the public internet. Configure Network Security Groups (NSGs) and firewalls for additional protection. Identity integration: Prefer Managed Identities for secure access to databases. Integrate with Azure Active Directory for centralized identity management. Compliance checks: Verify certifications like GDPR, HIPAA, or industry-specific standards. Use Azure Policy and Compliance Manager to automate compliance validation Audit logging and threat detection: Enable audit logging and advanced threat detection with Microsoft Defender for all database services. Review logs and alerts regularly. Optimize for cost Compute tiers: Choose General Purpose for balanced workloads; Business Critical for low-latency and high IOPS. Review workload sizing and adjust tiers as needed for cost efficiency. Autoscaling: Enable autoscale for Cosmos DB and flexible servers to avoid overprovisioning. Monitor scaling events and set thresholds to control spend. Reserved capacity: Commit to 1–3 years for predictable workloads to unlock discounts. Evaluate usage patterns before committing to reservations. Serverless: Use serverless compute for workloads with completely ad hoc usage and low frequency of access. This eliminates the need for pre-provisioned resources and reduces costs for unpredictable workloads. Monitoring: Use Azure Cost Management and query performance insights to optimize spend. Set up budget alerts and analyze cost trends monthly. Include basic resource monitoring to detect adverse usage patterns early. Storage and backup costs: Review storage costs, backup retention policies, and configure lifecycle management for backups and archives. Data migration from AWS to Azure Migrating your data from AWS to Azure is a key step in replicating your app’s database layer for Azure Marketplace. The goal is a one-time transfer—after migration, your app runs fully on Azure. Azure Database Migration Service (DMS): Automates migration from RDS, Aurora, or on-prem to Azure Database, Azure SQL Managed Instance, Azure Database for MySQL/PostgreSQL, and SQL Server on Azure VM (for MySQL/PostgreSQL/SQL Server). Supports online and offline migrations; run pre-migration assessments and schema validation. Azure Data Factory: Orchestrates data movement from DynamoDB, Redshift, or S3 to Azure Cosmos DB or Synapse. Use mapping data flows for transformations and data cleansing. MongoDB migrations: Use the online migration utility designed for medium to large-scale migrations to Azure DocumentDB. Ensure schema compatibility and validate performance benchmarks before cutover. Cassandra migrations: Use Cassandra hybrid cluster or dual write proxy for Azure Managed Instance for Apache Cassandra. Validate schema compatibility and test migration in a sandbox environment. Offline transfers: For very large datasets, use Azure Data Box for secure physical migration. Plan logistics and security for device handling. Migration best practices: Schedule migration during a maintenance window, validate data integrity post-migration, and perform cutover only after successful data validation & verifications. Final readiness before marketplace listing Validate performance: Benchmark with real data and confirm chosen SKUs deliver required throughput and latency. Test application functionality under expected load and validate query performance for all critical scenarios. Lock down security: Ensure RBAC roles, Private Endpoints, and encryption meet compliance requirements. Review audit logs, enable threat detection, and verify access controls for all database and storage resources. Control costs: Verify autoscaling, reserved capacity, and cost alerts are active. Review storage and backup policies, and set up budget alerts for ongoing cost control. Enable monitoring: Set up dashboards for query performance, latency, and capacity. Configure alerts for failures, anomalies, and capacity thresholds. Monitor with Azure Monitor and Log Analytics for real-time operational insights. Documentation and support: Update migration runbooks, operational guides, troubleshooting documentation, and escalation contacts for post-migration support. Key Resources SaaS Workloads - Microsoft Azure Well-Architected Framework | Microsoft Learn Metered billing for SaaS offers in Partner Center Create plans for a SaaS offer in Microsoft Marketplace Get over $126K USD in benefits and technical consultations to help you replicate and publish your app with ISV Success Maximize your momentum with step-by-step guidance to publish and grow your app with App Advisor
