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Where AWS fits
A deliberate selection of compute, database, storage and access services.
When to choose another approach
Capacity depends on architecture, quotas and budget. Begin with a small supportable system.
Worked example and evidence
Fictional order service: application compute → relational database → file storage, with logs and backups. Expand only after measuring bottlenecks.
What you need to supply
Request/data volumes, region, recovery needs, account access and budget assumptions.
What acceptance should demonstrate
Record load results, permissions, restore evidence and a cost estimate with assumptions.
Running costs and responsibilities
Track compute, database, storage, requests, transfer, logs, backups and support separately.
Technical scope to confirm
Instance families offer different resource profiles. Capacity planning must match the real workload.
A proposal should identify the systems and data, direction of sync, access feasibility, failure handling, named owners and included deliverables. Listing this technology does not imply a prebuilt connector, vendor partnership or included feature.
What operating cost changes as usage grows?
Processing, storage, transfer and retained logs grow differently. Review the actual bill against assumptions before scaling.