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You are formulating a target state migration plan to move an on-premises data processing environment to Google Cloud VMware Engine. The environment consists of interconnected data integration applications, large database servers, and several VMs with pending system updates.
You need to design a phased migration roadmap that minimizes downtime, avoids multiple power cycles for VMs, and mitigates the risk of resource contention in the target architecture.
Which strategy should you incorporate into your migration plan?
Group the VMs into a single migration wave to guarantee that application dependencies are preserved. Apply all pending system updates in the source environment prior to the migration to ensure consistency. Convert the database storage to physical Raw Device Mappings (RDMs) to maximize throughput in the target architecture.
Group the VMs into migration waves based on their maintenance schedules and application dependencies. Align the installation of pending system updates with the migration switchover reboots. Identify database servers with large memory requirements to prevent them from exceeding node specifications or causing contention.
Group the VMs into migration waves based on their storage capacity. Delay all system updates until the post-migration phase to avoid altering the source environment. Use multi-writer disks for the database servers to distribute the I/O load across multiple target nodes.
Group the VMs into migration waves based on their operating system types. Perform a live migration (vMotion) for all VMs with pending system updates to completely eliminate the need for power cycles. Configure the database servers to use DirectPath I/O to ensure they receive dedicated hardware resources.
Group the VMs into a single migration wave to guarantee that application dependencies are preserved. Apply all pending system updates in the source environment prior to the migration to ensure consistency. Convert the database storage to physical Raw Device Mappings (RDMs) to maximize throughput in the target architecture.
Group the VMs into migration waves based on their maintenance schedules and application dependencies. Align the installation of pending system updates with the migration switchover reboots. Identify database servers with large memory requirements to prevent them from exceeding node specifications or causing contention.
Migration wave planning is a strategic approach to moving workloads to the cloud in manageable phases rather than a single massive cutover. It involves analyzing the source environment to group virtual machines (VMs) logically based on their business function, technical requirements, and operational constraints.
This approach synthesizes operational constraints (maintenance schedules), technical requirements (system updates), and architectural limitations (node specifications) into a cohesive plan. Unlike approaches that ignore dependencies or attempt to migrate unsupported hardware configurations, this strategy ensures a smooth transition to the target architecture while strictly adhering to the stated requirements.
Group the VMs into migration waves based on their storage capacity. Delay all system updates until the post-migration phase to avoid altering the source environment. Use multi-writer disks for the database servers to distribute the I/O load across multiple target nodes.
Group the VMs into migration waves based on their operating system types. Perform a live migration (vMotion) for all VMs with pending system updates to completely eliminate the need for power cycles. Configure the database servers to use DirectPath I/O to ensure they receive dedicated hardware resources.
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