Cloud Assessments in Cloud Migration

This curriculum spans the technical, financial, and governance dimensions of cloud assessments with a depth comparable to a multi-workshop advisory engagement, addressing real-world complexities like shadow IT inclusion, regulatory constraints, and cross-system dependency mapping.

Module 1: Defining Scope and Objectives for Cloud Assessments

• Selecting business-critical workloads for initial assessment based on technical debt, operational cost, and strategic alignment.
• Determining assessment depth—lightweight discovery vs. full technical and financial analysis—based on migration urgency and stakeholder risk tolerance.
• Establishing ownership boundaries between business units, IT, and cloud providers during scope definition to prevent accountability gaps.
• Identifying regulatory constraints (e.g., data residency, PII handling) that limit cloud eligibility for specific applications.
• Deciding whether to include shadow IT in the assessment scope, balancing completeness against political sensitivities.
• Setting measurable success criteria for the assessment phase, such as % of applications profiled or TCO variance thresholds.

Module 2: Discovery and Inventory of On-Premises Environments

• Choosing between agent-based and agentless discovery tools based on security policies and OS diversity.
• Resolving discrepancies between CMDB records and actual running workloads due to configuration drift.
• Handling legacy systems without instrumentation or monitoring by using manual data collection protocols.
• Mapping application dependencies across hybrid environments using network flow analysis or synthetic transactions.
• Normalizing hardware and software inventory data from heterogeneous sources into a standardized schema.
• Validating discovered data with system owners to correct misclassifications before analysis.

Module 3: Performance and Utilization Analysis

• Selecting appropriate performance baselines (e.g., 95th percentile vs. peak vs. average) for sizing cloud instances.
• Identifying underutilized resources that may be candidates for rightsizing or retirement.
• Accounting for seasonal workloads (e.g., month-end processing) in performance trend analysis.
• Correlating CPU, memory, disk I/O, and network metrics to detect resource contention bottlenecks.
• Determining sampling frequency for performance data to balance accuracy with storage overhead.
• Handling systems with inconsistent monitoring coverage by interpolating missing data with proxy metrics.

Module 4: TCO and Financial Modeling

• Converting on-premises depreciation schedules into equivalent cloud operational expenditure models.
• Factoring in reserved instance or savings plan commitments when projecting 3-year cloud costs.
• Estimating data egress fees for workloads with high outbound traffic patterns.
• Allocating shared costs (e.g., networking, security) across business units using fair-use models.
• Modeling cost impact of disaster recovery requirements in multi-region cloud deployments.
• Adjusting financial models for variable cloud pricing across regions and provider SKUs.

Module 5: Technical Fit and Migration Readiness Evaluation

• Assessing database compatibility with managed cloud services (e.g., Oracle to Amazon RDS limitations).
• Determining refactoring effort for applications dependent on on-premises middleware or APIs.
• Evaluating latency sensitivity of real-time applications for feasibility in public cloud regions.
• Identifying applications requiring GPU, FPGA, or specialized hardware not available in target cloud.
• Reviewing application statefulness and session persistence mechanisms for cloud-native adaptation.
• Validating support lifecycle alignment between legacy applications and cloud platform versions.

Module 6: Risk, Compliance, and Security Assessment

• Mapping existing on-premises controls to cloud provider shared responsibility model gaps.
• Identifying workloads subject to industry-specific regulations (e.g., HIPAA, PCI-DSS) requiring specific cloud configurations.
• Assessing encryption key management strategies (BYOK vs. provider-managed) for data at rest.
• Reviewing identity federation requirements between on-prem AD and cloud IAM systems.
• Evaluating network segmentation needs and translating VLANs to cloud VPC designs.
• Documenting audit trail requirements and ensuring cloud logging services meet retention policies.

Module 7: Prioritization and Migration Sequencing

• Applying scoring models to rank applications based on business value, technical risk, and cost savings.
• Grouping interdependent applications into migration waves to minimize cross-wave downtime.
• Deferring migration of high-risk applications until proof-of-concept validation is complete.
• Sequencing migrations to align with fiscal budget cycles and contract renewal dates.
• Balancing quick-win migrations with foundational platform work (e.g., landing zone setup).
• Coordinating migration timelines with application modernization or end-of-life plans.

Module 8: Reporting, Governance, and Continuous Assessment

• Designing executive dashboards that highlight migration progress, cost trends, and risk exposure.
• Establishing change control processes for reassessment after major infrastructure modifications.
• Defining thresholds for re-triggering assessments due to workload performance or cost deviations.
• Integrating assessment findings into enterprise architecture repositories for long-term tracking.
• Assigning data stewards to maintain accuracy of cloud readiness inventories post-migration.
• Implementing feedback loops from migration teams to refine assessment methodologies over time.