Lesson 1Data cataloging and normalisation: building spreadsheets or CMDB entries, tagging strategy for migration prioritisationGet into how to catalogue servers, apps, and data into organised inventories or CMDBs. Learn about normalising, naming, and tagging approaches that back migration phases, tracking ownership, and handling governance after the shift to AWS.
Designing inventory spreadsheets and CMDB fieldsNormalising application and system namingDefining ownership, criticality, and SLA attributesCreating AWS-aligned tagging taxonomiesTagging for migration waves and prioritisationLesson 2Two discovery tools examined: AWS Application Discovery Service and VMware vRealize Network Insight — how to use each for inventory, dependency mapping, and export formatsDive into AWS Application Discovery Service and VMware Aria Operations for Networks. Learn setup, data gathering, dependency mapping, and export options to feed into AWS Migration Hub and other planning tools.
Configuring AWS Application Discovery ServiceCollecting agentless and agent-based ADS dataSetting up VMware Aria Operations for NetworksBuilding dependency maps and flow visualisationsExporting inventories to AWS Migration HubLesson 3Interview guide for stakeholders: app owners, DBAs, network, security, operations, business stakeholdersPut together a structured interview guide for tech and business folks. Learn the right questions to ask app owners, DBAs, network, security, and ops teams to uncover hidden links and migration hurdles.
Identifying key technical and business stakeholdersPreparing role-specific interview question setsRunning effective discovery workshops and sessionsValidating findings with follow-up interviewsDocumenting decisions, risks, and open issuesLesson 4Storage and I/O characteristics: datastore types, IOPS, throughput, shares, deduplication, backup schedulesGrasp storage and I/O traits that shape AWS designs. Learn to record datastore types, performance profiles, deduplication, and backup timetables to pick fitting EBS, EFS, or FSx choices and policies.
Classifying datastore and array types in useMeasuring IOPS, throughput, and latency profilesIdentifying storage tiers, QoS, and share settingsDocumenting snapshots, backups, and retentionMapping storage needs to AWS storage servicesLesson 5Collecting server and VM inventory: CPU, memory, storage, OS versions, VM tools, snapshotsLearn how to gather detailed server and VM info from VMware and guest OSs. Capture CPU, memory, storage, OS versions, tools, and snapshots to aid right-sizing, compatibility checks, and planning the move to AWS.
Gathering CPU, memory, and NUMA informationCapturing disk layout, datastore, and capacity dataRecording OS versions, editions, and patch levelsIdentifying VMware Tools status and versionsDetecting snapshots and orphaned VM artefactsLesson 6Application and tier dependencies: web, app, DB processes, inter-host ports, service mapsLearn to spot and document app tiers and their links across web, application, and database layers. Understand ports, protocols, and service maps needed to safely re-platform workloads into AWS.
Identifying web, app, and database tiersDocumenting inter-tier ports and protocolsBuilding end-to-end service dependency mapsDetecting hidden batch jobs and background tasksCapturing external third-party service callsLesson 7Operational procedures and runbooks: backup/restore, patching, deployment, escalation pathsGo over current operational procedures and runbooks that keep on-premises workloads ticking. Translate backup, patching, deployment, and escalation habits into needs and limits for AWS landing zones and ops.
Cataloguing backup and restore proceduresDocumenting patching and maintenance workflowsCapturing deployment and release processesUnderstanding monitoring and alerting runbooksMapping escalation paths and on-call rotationsLesson 8Network topology and connectivity: VLANs, subnets, routing, firewalls, NAT, load balancersGet how to document your current network setup, including VLANs, subnets, routing, and security layers. Learn how this info shapes AWS VPC design, connectivity picks, and security group and NACL strategies.
Mapping VLANs, subnets, and IP address rangesDocumenting routing, VRFs, and default gatewaysCapturing firewall, NAT, and ACL configurationsIdentifying load balancers and VIP dependenciesRelating on-prem networks to AWS VPC designLesson 9Assumptions to state explicitly when gaps exist: sample load, unavailable metrics, maintenance windows, licensing constraintsLearn to document and share assumptions when discovery data's incomplete. Capture sample loads, missing metrics, maintenance windows, and licensing limits to handle risks and set stakeholder expectations.
Identifying missing or unreliable data areasDefining traffic and load sampling assumptionsStating maintenance and outage window limitsCapturing licensing and support constraintsRecording risks and validation follow-upsLesson 10Scripts and manual techniques: PowerCLI, govc, vSphere API calls, Linux/Windows commands to collect configurationLearn scripts and hands-on methods to pull VMware and OS configs when tools are thin on the ground. Use PowerCLI, govc, vSphere APIs, and OS commands to build solid inventories and check automated results.
Using PowerCLI to export VM configurationLeveraging govc and vSphere REST APIsRunning Linux commands for system inventoryRunning Windows commands for system inventoryValidating manual data against tool outputsLesson 11Database specifics: engine, version, schema size, transaction rates, replication, maintenance windowsZero in on database-specific discovery across engines and platforms. Capture engine type, version, schema size, transaction rates, and replication to guide AWS database service picks and migration plans.
Cataloguing database engines and versionsMeasuring schema size and growth trendsCapturing transaction and query rate metricsDocumenting replication and HA configurationsIdentifying maintenance and backup windowsLesson 12Usage and performance metrics: CPU/memory utilisation, latency, throughput, peak patterns, retention windowsLearn to collect and make sense of usage and performance metrics for VMware workloads. Use CPU, memory, I/O, and latency data to right-size AWS instances, plan storage performance, and spot peak and seasonal patterns.
Identifying authoritative metric data sourcesCapturing CPU and memory utilisation baselinesMeasuring disk IOPS, throughput, and latencyAnalysing network throughput and connection countsDetecting peaks, seasonality, and retention needsLesson 13Third-party tool options overview: Cloudamize and Turbonomic use cases for TCO, sizing, and migration prioritisationCheck out third-party discovery and optimisation tools like Cloudamize and Turbonomic. Get their strengths for TCO analysis, sizing, and migration prioritisation, and how to weave their outputs into AWS plans.
Cloudamize capabilities and data collectionTurbonomic workload optimisation featuresComparing sizing recommendations across toolsUsing tools for TCO and cost modellingExporting results into migration backlogsLesson 14Security and compliance artefacts: ACLs, firewall rules, encryption, logs, audit trails, identity storesFind out how to inventory security and compliance bits that impact migration. Document ACLs, firewall rules, encryption, logging, and identity stores to design secure AWS landing zones and control mappings.
Cataloguing firewall rules and security zonesDocumenting ACLs, security groups, and NACLsIdentifying encryption methods and key custodyReviewing logging, SIEM, and audit requirementsMapping identity stores and access modelsLesson 15Discovery methods and evidence sources: agentless queries, hypervisor APIs, SNMP, syslogs, perf counters, interviewsExplore discovery methods and evidence sources for VMware setups. Compare agentless scans, hypervisor APIs, SNMP, logs, and interviews, and learn to blend them into a repeatable, checkable discovery process.
Using vCenter and hypervisor API integrationsLeveraging agentless OS and network scansCollecting SNMP, syslog, and perf counter dataCorrelating logs with configuration evidenceCombining automated discovery with interviews
