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World desk5 min

Server Migration Audit: What to Record Before Making Changes

A practical pre-migration audit links each server to its workload, owners, dependencies, performance, data, recovery needs, security controls, and rollback plan.
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Before you migrate or modify a server, document what it runs, who depends on it, how it performs, and how the service can be recovered. A useful pre-migration audit is more than an asset list: it is an owner-validated baseline for choosing a migration approach, sizing the target, planning cutover, and deciding when to roll back.

Start with a record for each workload, not just each server

A server inventory tells you what exists; it does not necessarily show what business service it supports or what would break if it moved. Link every server to its application, business capability, data, owner, supporting infrastructure, and dependencies. Use a stable asset identifier so the record remains traceable if a hostname or location changes.

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  • Identity and ownership: asset ID, hostname, environment, physical or cloud location/account, business or application owner, technical contact, support team, and lifecycle status.
  • Business context: users served, service hours, peak periods, criticality, maintenance windows, change restrictions, and the desired outcome of the migration.
  • Disposition: whether the workload is expected to be rehosted, replatformed, refactored, replaced, or retired; record the rationale and the person accountable for that decision.

AWS’s detailed application assessment and Google Cloud’s workload assessment guidance both emphasize workload context and ownership as part of migration assessment.

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Capture the current technical and capacity baseline

Record enough about the existing environment to check compatibility and make an evidence-based target-sizing decision. Separate configured capacity from observed use: allocated CPU and memory do not show whether those resources are routinely needed, while a short observation window can miss a seasonal or month-end peak.

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  • Platform: operating system and release, processor architecture, physical or virtual context, hypervisor or hosting details, and server role or enabled features.
  • Compute and storage: CPU and memory allocation, disks and volumes, filesystem details, storage capacity, and any relevant IOPS or throughput requirements.
  • Network identity: NICs, IP addresses, DNS names, network segments, and load-balancer membership.
  • Software: installed applications, runtime and database versions, services, agents, scheduled tasks, and licensing constraints.
  • Observed behavior: CPU and memory utilization, disk IOPS and throughput, storage growth, and peak-use patterns. For each measurement, note its source and observation window.

Azure Migrate’s migration-planning guidance describes collecting server, disk, network, application, role, and performance information for assessment. The inventory fields are useful regardless of which platform or tooling you use.

Describe the data and storage that move with the workload

List each data source the application reads or writes, including databases, application data, file shares, virtual-machine disks, SAN or NAS volumes, archives, and backups. For each source, document:

  • Approximate volume, file or object count, directory structure, and expected growth or change rate.
  • Retention requirements, access frequency, and performance or latency needs.
  • Access method and protocol, such as SMB, NFS, object APIs, or block storage, plus the authentication method.
  • Special file characteristics that could affect transfer or compatibility, such as long paths, reserved names, or alternate data streams where relevant.
  • Which applications need the data before and after migration, and whether the move requires a final read-only period or synchronization step.

Microsoft’s storage migration assessment covers data size and hierarchy, access method, authentication, dependencies, protection, and performance requirements. Treat data inventory as part of application planning: a server can start successfully while its service remains unusable because a data source or permission did not move with it.

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Map dependencies and identify what must move together

Build a dependency map that covers runtime connections as well as supporting services. For each relationship, record its direction, protocol and port if known, data exchanged, owner, criticality, latency sensitivity, location, and whether it can tolerate the two sides running in separate environments during transition.

  • Application-to-server and server-to-server connections.
  • Shared databases, APIs, file paths, batch jobs, caches, and identity providers.
  • DNS, load balancers, network services, monitoring, backup systems, and external providers.
  • Reporting or business relationships that are important but are not direct runtime dependencies.

Mark components that must migrate together and those that must remain in place, with the reason and the temporary connectivity or data-flow arrangement for each split. Microsoft’s migration planning guidance recommends discovering and grouping dependencies and checking that supporting components such as DNS and load balancers are accounted for. Google Cloud’s migration execution guidance describes refining dependency mappings as execution proceeds.

Record availability, backup, and recovery requirements

For each workload, document its availability requirement or SLA, acceptable downtime, recovery point objective (RPO), and recovery time objective (RTO). Then compare those requirements with the recovery capability that has actually been tested.

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  • Current backup method or product, schedule, retention, encryption, and offsite or immutable-copy details where applicable.
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  • Date and outcome of the last restore or disaster-recovery exercise.
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These details affect migration sequencing, synchronization, cutover windows, and rollback decisions. Microsoft’s storage assessment calls for recovery and data-protection requirements; AWS’s application assessment also asks about backup, retention, recovery objectives, and the last disaster-recovery test.

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Document security, access, and compliance constraints

Capture the rules that determine where and how the workload and its data may run. Record data classification and sensitivity, applicable regulatory or contractual obligations, residency constraints, and approved target regions. Include identity and authentication methods, service accounts, permissions and ACLs, encryption in transit and at rest, certificate requirements and renewal owners, firewall ingress and egress rules, and audit or chain-of-custody needs.

State how permissions will be preserved or reapplied and who approves exceptions. Do not copy passwords, private keys, tokens, or other secret values into the audit; reference the controlled secret-management system instead. Microsoft’s storage guidance addresses permissions, secure transfer, residency, auditing, and end-of-life considerations, while AWS’s application assessment includes classification, encryption, authentication, certificates, and compliance.

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Turn the baseline into an executable migration and rollback plan

Once the workload, dependencies, and constraints are known, document the proposed migration treatment and its assumptions. There is no single right path for every server. Compare compatibility and supported versions, dependency coupling, data volume and change rate, downtime tolerance, performance and latency needs, security or residency limits, recovery requirements, operational skills, cost, and rollback feasibility. Record why the chosen approach fits this workload.

For each workload or wave, make the plan operational:

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  • Target assumptions, migration group, prerequisites, data-transfer method, and change window.
  • DNS and network changes, firewall rules, accountable roles, and dependencies on other teams or vendors.
  • Risks, mitigations, and measurable success criteria.
  • Functional, integration, security, and performance tests, including test data and approvers.
  • Cutover checks, explicit rollback triggers, ordered reversal or restoration steps, data reconciliation requirements, and post-rollback validation.

Google Cloud’s execution checklist includes a runbook, network and security rules, tests, risks, rollback plan, team roster, and governance. Microsoft’s workload preparation guidance recommends human-readable configuration and deployment records stored centrally with validation and recovery procedures.

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Validate the audit and keep it authoritative

Label each entry as an observed fact, owner-confirmed requirement, estimate, or unresolved assumption. Preserve the source and collection date for discovery output and stakeholder answers. Compare static records with programmatic discovery and interviews with workload owners; investigate contradictions before setting migration waves. AWS specifically advises validating static documentation and institutional knowledge against programmatic data where possible in its assessment guidance.

Store the records in a controlled central location that migration, operations, security, and support teams can access. Use version history, name an owner, show the last-updated date, and refresh the inventory as discovery and testing expose new dependencies. The audit should remain the working baseline, not a document that becomes stale as soon as planning begins.

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