Modernize
Cloud modernization is the practice of improving existing cloud-based workloads to better meet business needs. It aligns workloads with cloud best practices, without adding new features.
Prepare organization for cloud modernization
Define modernization for your organization. Establish a common definition that focuses on improving existing workloads through replatforming, refactoring, and rearchitecting within the cloud, excluding net-new features or complete rewrites. Communicate this definition across all teams and stakeholders to prevent misalignment. Create shared responsibility between development, operations, security, and architecture teams with clear roles and cross-team coordination.
Assess modernization readiness and skills. Evaluate your team's capabilities in cloud services knowledge, DevOps/CI/CD maturity, modern architecture patterns, and monitoring/automation tools. Identify skills gaps and create plans to address them through training, certifications, new hires, or external expertise from Microsoft or partners to ensure smooth modernization execution.
Prioritize what workloads to modernize. Assess business value by rating workloads based on their importance to revenue, customer experience, compliance, and internal dependencies. Evaluate technical risk by examining technical debt, outdated technology, maintenance effort, performance issues, and scalability limitations. Combine these assessments into a priority matrix to determine which workloads to modernize first.
Understand how to modernize. Use the Azure Well-Architected Framework to conduct reviews that identify gaps and generate modernization roadmaps across five pillars: Reliability, Security, Cost Optimization, Operational Excellence, and Performance Efficiency. Enable workload teams to make modernization decisions by providing business context and decision-making authority within defined boundaries while maintaining regular check-ins for organizational alignment.
Plan your cloud modernization
Choose a modernization strategy. Select from three primary approaches based on your specific needs: replatform for quick wins with minimal code changes (IaaS to PaaS), refactor to modify existing code for improved structure and cloud optimization while maintaining functionality, or rearchitect to redesign application architecture using cloud-native patterns like microservices and serverless. Match the strategy to each component's requirements considering goals, timeline, and resources. Avoid over-modernization by grounding every decision in business value.
Plan modernizations in phases. Break complex workloads into logical phases to deliver incremental value and reduce risk by tackling manageable chunks. Divide work by component/layer, priority/complexity, or business function, starting with low-risk, high-value changes for early wins. Sequence remaining phases by value and dependencies. Define clear success criteria for each phase including technical goals and quality gates, and adapt plans based on results and lessons learned from completed phases.
Plan for modernization governance. Establish formal change approval workflows integrated with existing Change Advisory Boards or create dedicated modernization review boards. Implement change freezes before and during major deployments to stabilize environments. Control scope creep by requiring evaluation and approval for any proposed changes while maintaining a backlog of deferred nice-to-have ideas.
Define your deployment strategy. Choose between in-place deployment for low-risk, reversible changes that can be implemented during maintenance windows, or parallel deployment for complex, high-risk changes requiring minimal downtime by running new environments alongside existing workloads. Use progressive deployment techniques like canary releases when possible, starting with small user percentages and gradually increasing based on monitoring results.
Plan to mitigate modernization risks. Create detailed rollback procedures for every major change with step-by-step instructions, responsible parties, and timeframes. Automate rollbacks where possible using infrastructure-as-code tools and blue-green deployments. Ensure support teams are on standby during and after deployments with extended hypercare periods for monitoring.
Secure stakeholder approval. Tailor value propositions to different audiences (operational efficiency for technical teams, business outcomes for leaders) and document structured plans with clear milestones and timelines. Quantify modernization value with specific metrics like 20-40% cost reduction and 50-80% productivity gains. Address project risks transparently with mitigation strategies and maintain regular communication to report progress and gather feedback.
Execute modernizations in the cloud
Prepare stakeholders for modernization. Announce deployment schedules well in advance to all affected parties including key dates like change freeze start and go-live windows. Implement change freezes on source and dependent workloads with clearly defined start and end times. Communicate final user actions and post-deployment changes including new access URLs and authentication requirements. Coordinate support staffing for deployment with extended hours and escalation procedures. Define fallback procedures for critical workloads with manual workarounds and contingency plans.
Develop modernizations in a nonproduction environment. Follow Well-Architected Framework principles during implementation using Azure Advisor recommendations and architectural review processes to validate design decisions. Create nonproduction environments that mirror production using the same Azure services at smaller scales or lower performance tiers. Implement changes incrementally with source control and CI/CD using Git for all code changes and infrastructure as code scripts with continuous integration builds.
Validate modernization changes with testing. Execute unit and integration tests on all modified components using CI pipelines and regression testing to avoid breaking existing functionality. Conduct end-to-end functional testing through manual QA or automated UI tests simulating real user workflows. Perform user acceptance testing with stakeholders to capture feedback on usability and functionality. Validate performance using load testing tools like Azure Load Testing at 150% expected load. Execute security validation and compliance checks using vulnerability scans and Microsoft Defender for Cloud. Resolve all critical issues before production deployment.
Create reusable infrastructure. Build infrastructure as code templates that can be used for future deployments and environments, ensuring consistency and reducing manual configuration errors across different deployment scenarios.
Create deployment documentation. Document all deployment procedures, rollback steps, and validation processes to ensure consistent execution and enable team members to perform deployments safely and reliably.
Deploy modernization. For in-place deployments, schedule maintenance windows, use CI/CD pipelines for consistent deployment, and implement progressive traffic routing through canary deployments using Azure App Service slots or Container Apps traffic splitting. Gradually increase to full traffic while monitoring metrics and maintain data consistency during deployment. For parallel deployments, create the parallel production environment using IaC templates, establish database replication with continuous data synchronization, copy unstructured data and files using Azure migration tools, complete final data synchronization with zero data loss, gradually cut over user traffic using weighted routing starting at 1% and increasing incrementally. Perform the final switch to 100% through DNS cutover or load balancer configuration. Immediately verify post-cutover functionality and keep the old environment as hot standby for 24-72 hours.
Validate modernization success. Confirm successful user access and workload performance by monitoring access patterns, performance metrics, and error rates during the initial post-migration period. Announce migration success only after thorough validation and confirmation from workload owners, testers, and business stakeholders that all requirements are met.
Support workload during stabilization. Establish enhanced support coverage during the stabilization period with experienced IT staff providing shorter SLAs than normal operations for the first few days or weeks. Update operational documentation and tools including runbooks, support docs, and monitoring configurations. Train operations teams on new procedures and ensure asset inventory reflects the new infrastructure while removing legacy components.
Optimize workloads after cloud modernization
Optimize configurations for the cloud. Apply Azure Advisor recommendations systematically by reviewing weekly and implementing critical changes first, filtering by workload or resource group. Tweak service-specific settings using Azure Well-Architected Framework service guides to align configurations with best practices. Address security configuration gaps immediately using Microsoft Defender for Cloud to resolve critical and high-severity findings within 48 hours while configuring continuous assessment.
Validate operational readiness. Verify monitoring coverage and accuracy by ensuring Azure Monitor collects all necessary logs, metrics, and traces for new components. Test alert rules through chaos testing and update dashboards to reflect the new architecture. Establish cost monitoring and controls using Microsoft Cost Management to track spending patterns, set budget alerts and spending limits, and review resource utilization weekly for rightsizing opportunities. Test backup and recovery procedures by performing test restores using Azure Backup or database point-in-time restore. Document achieved RTO and RPO metrics and ensure all critical data is included in backup policies.
Collect user feedback and measure outcomes. Gather structured user feedback regularly through surveys, feedback forms, and support ticket analysis. Conduct retrospective meetings for internal teams. Track and resolve feedback systematically by documenting issues in Azure DevOps or GitHub Issues, categorizing by severity and business value, assigning ownership with resolution timelines, and communicating progress monthly. Measure actual outcomes versus goals by compiling success metrics and ROI projections. Communicate results to stakeholders to demonstrate value realized or identify shortfalls.
Establish continuous modernization practices. Schedule regular workload reviews every few months using Well-Architected reviews or health checks to identify new optimization opportunities as cloud services evolve and usage patterns change. Automate optimization wherever possible using Azure Policy to enforce best practices, implementing autoscaling rules for performance tuning, and setting up cost anomaly alerts through Cost Management. Share outcomes and best practices by documenting successful optimization patterns, creating playbooks for common scenarios, maintaining knowledge bases of lessons learned, and contributing insights to organizational cloud adoption practices.
For the detailed Cloud Adoption Framework guidance, see Modernize workloads in cloud.