Cloud Architects and Infrastructure Engineers
Designing a cloud migration strategy for enterprise batch processing and big data clusters
The Compute Resource Selection mind map template provides a technical framework for architects and DevOps engineers to optimize cloud infrastructure costs and performance. This 43-node resource Selection cheat sheet covers three primary pillars: Custom machine type, Preemptible VMs, and Specialized workload categories. It details specific configuration methods via Console, gcloud and API configuration while highlighting financial benefits such as 57% committed use discounts and sustained use discounts for long-running workloads. By mapping out the technical constraints of short-lived instances, such as the 24 hours max runtime for preemptible nodes, this template serves as a decision-making guide for selecting the right compute engine for diverse enterprise needs.
使用條款Designing a cloud migration strategy for enterprise batch processing and big data clusters
Conducting a quarterly cloud spend review to identify opportunities for committed use discounts
Selecting the appropriate instance types for a new high-performance computing (HPC) project
Download the .xmind file and open it in Xmind desktop or the web app to view the full resource Selection tree.
Replace the generic 'Specialized workload' nodes with your actual project names to see which machine type fits best.
Use the Export function to share the finalized compute strategy as a PDF or PNG during infrastructure planning meetings.
This template includes a structured breakdown of cloud computing options, specifically focusing on custom machine configurations, preemptible instance limitations, and specialized hardware profiles for tasks like machine learning or SAP HANA.
You can use the template to compare 'Sustained use discounts' against 'Preemptible VMs' pricing. It helps identify which workloads can tolerate the 30-second shutdown warning in exchange for 80% cost savings.
Yes, the template is fully editable. You can customize the specific discount percentages, add your own cloud provider's API commands, or expand the 'Specialized workload' branches to include local server specs.
The 'Specialized workload' branch is best used for mapping high-performance needs, such as 'Electronic Design Automation' under Compute-Optimized or 'In-memory analytics' under the Memory-Optimized category.
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