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Modernize infrastructure one workload at a time: start with its business outcome, technical condition, dependencies and operating constraints, then choose the least disruptive change that meets the need. Replatforming, refactoring, rearchitecting and different hosting environments are options—not mandatory stages on a universal migration path.
Start with the workload and the outcome
Infrastructure modernization is a portfolio decision, not a requirement to move every application to the same platform or architecture. For each candidate, identify the business result the change is meant to deliver, such as meeting a support deadline, improving availability, enabling a new capability or addressing a technical constraint. Then weigh that value against delivery risk, cost, operating needs and the organization’s technical standards. Microsoft’s application modernization planning guidance recommends assessing applications against organizational needs rather than assuming one target fits all.
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Build a workload picture before selecting a destination. Record the application’s condition, dependencies, data location, security and compliance requirements, operating constraints, and the team’s readiness to change and run it. Outdated technology and approaching support deadlines can be useful prioritization triggers, but no universal scoring formula can rank workloads without this context. Microsoft’s preparation guidance also emphasizes organizational readiness and skills; where expertise is missing, outside help may be appropriate.
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Stabilize fragile workloads first
A workload that is unreliable, poorly understood or entangled with critical dependencies may not be ready for a large architectural change. Stabilize it, clarify its dependencies and establish a safe way to test changes before committing to a more ambitious target. This reduces the risk of layering a complex migration onto an already fragile service.
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Choose the degree of change for each application
Modernization paths sit on a continuum. A larger architectural change may create more opportunity to improve scalability or make use of cloud capabilities, but it generally demands more design, testing, time and delivery capacity. A smaller change can preserve familiarity and limit disruption, while leaving more of the existing application’s constraints in place. Microsoft’s planning guidance treats modernization approaches as choices that can be combined, not mutually exclusive labels for an entire portfolio.
| Path | What changes | When it may fit | Key tradeoff |
|---|---|---|---|
| Rehosting | Move the workload with limited changes to its architecture. | When relocation is the immediate need and a deeper redesign is not yet justified or feasible. | Can limit near-term change, but does not by itself resolve architectural constraints. |
| Replatforming | Make targeted changes to use a different or managed platform while retaining much of the application. | When a workload can benefit from a platform capability without a full redesign. | Requires adapting and validating the application, while preserving many existing design choices. |
| Refactoring | Change application components or code to improve how the workload is built or operated. | When specific technical limitations block a desired outcome and the team can manage focused changes. | Introduces testing and delivery work; scope needs to stay aligned with the intended benefit. |
| Rearchitecting | Make a broader change to the application’s structure or design. | When the business case warrants substantial change to meet requirements that smaller adjustments cannot address. | Offers more potential for architectural improvement, with greater cost, time, testing and execution risk. |
| Retaining or retiring | Keep a workload as it is for now, or remove it from the portfolio. | When modernization is not the best current use of resources, or the workload no longer needs to run. | Retention leaves the current operating model in place; retirement requires a safe plan for users, data and dependencies. |
A single application may need different approaches for different components, and a phased effort may combine them. Decide by component, available skills and time frame—not by adopting the most ambitious label for its own sake.
Compare hosting environments by operating responsibility
Choose an environment according to what the workload needs and what the organization can reliably operate. Control, management effort, workload fit, performance and resilience goals, security responsibilities, portability and operational complexity all matter. The available guidance does not establish one provider or deployment model as best for every organization.
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| Environment | Potential fit | Operating consideration |
|---|---|---|
| Infrastructure as a service (IaaS) | Workloads where infrastructure control and a familiar operating model matter. | The organization remains responsible for more system and application management. |
| Platform as a service (PaaS) | Workloads where reducing platform-management effort and using managed capabilities are priorities. | Confirm that the platform’s capabilities and constraints suit the application and its operating requirements. |
| Hybrid | Workloads that need to combine existing datacenter investments with cloud services. | Integration, orchestration and governance must work across environments. |
| Multicloud or cross-cloud | Workloads whose requirements call for provider choice or distribution across providers. | Interoperability, monitoring, governance and day-to-day operations become more complex. |
| Edge or hybrid edge | Use cases that depend on where services and workloads need to operate. | Evaluate the specific use case and service capabilities, and test workloads before settling on a design. |
Microsoft’s strategy guidance discusses target choices in terms of return, operating model and technical requirements. For hybrid and multicloud planning, Google Cloud’s strategy guidance highlights the need to account for the added planning and operating work across environments. AWS’s hybrid cloud best practices recommend assessing use cases and testing workloads when considering hybrid edge services.
Use emerging capabilities only when the workload calls for them
Containers, serverless technologies, modern databases, microservices and AI or machine-learning capabilities can help address particular workload needs. They are building blocks, not a checklist every modernization project should adopt. The right fit depends on requirements such as latency, data location, existing investments, team skills, governance and the application’s design.
Containers and microservices
Consider containers or a move toward microservices when the application’s deployment or component structure is an obstacle to a defined outcome. They add design and operating considerations of their own; adopting them does not automatically make an application easier to run or less costly.
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Serverless and managed platforms
Serverless or managed platform capabilities may suit workloads where reducing infrastructure management is valuable and the service fits the application’s requirements. Assess the operating model and workload behavior rather than treating a managed service as an automatic upgrade.
Modern data and AI capabilities
Modern databases and AI or machine-learning services may support new application capabilities, including cases that draw on existing on-premises data. Decide where processing and data should reside by weighing latency, data location, governance and existing infrastructure. Microsoft’s Azure app modernization guidance covers containers, microservices, data infrastructure and AI integration; AWS’s modernization strategy describes containers, serverless and modern databases as ways to support emerging technologies. Google Cloud’s hybrid and multicloud planning guidance also treats AI-enabled use of existing on-premises data as one possible placement consideration.
Treat application and infrastructure as one change
Changing infrastructure without accounting for the application can undermine the service the organization is trying to improve. AWS Prescriptive Guidance puts it directly: “Applications and infrastructure are inseparable when it comes to business process quality, availability, and agility.” The statement appears in its phased approach to modernizing applications, whose document history is dated May 2023.
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For each modernization effort, connect the infrastructure target to the application’s dependencies, deployment process, data flows and operational ownership. A change that appears isolated at the infrastructure layer may affect availability or business processes through those connections.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Deliver in phases and control deployment risk
Break complex changes into manageable phases. Define governance, security and compliance checks, testing, deployment strategy and ownership before production changes begin. Microsoft’s execution guidance calls for controlled deployment, reusable infrastructure and a stabilization period; test changes outside production before relying on them in a live service.
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For a mission-critical change where downtime must be minimized, running the new and existing deployments in parallel can provide a fallback path. That protection comes with added infrastructure cost and the complexity of synchronizing data between deployments. Consider whether the workload can support that approach and how the team will verify results and handle a return to the prior deployment.
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Make stabilization part of the plan
After deployment, allow time to validate service behavior and resolve issues before treating the change as complete. The duration and checks should reflect the workload’s requirements and risk; the cited guidance does not prescribe one universal schedule.
Optimize against evidence after deployment
Cutover is not the end of modernization. Review actual usage and performance, then revisit whether the chosen platform and operating practices still fit. Microsoft’s optimization guidance identifies serverless, API-first design, containers and DevOps among practices that teams may revisit for cost efficiency, scalability and security. Treat each as an option to evaluate, not a guaranteed source of savings: measure the workload before making a cost or performance claim.
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