The attributes behind your decision
- Decision input
- Measured workload
- Primary variables
- Capacity, control, operations
- Validation
- Representative testing
- Next step
- dedicated servers
Profile the workload before comparing hardware
Measure CPU utilization, memory working set, disk latency, throughput, network transfer and growth on the current environment. Record peak and sustained demand separately.
Compare processors using relevant work
Core count, clock speed and architecture affect workloads differently. Compile code, process application requests or run representative queries under controlled conditions instead of relying on a single synthetic score.
Design memory and storage together
Memory capacity affects caching and database working sets. Storage media, controller, RAID layout and queue depth affect latency and resilience. Reserve capacity for rebuilds, logs and growth.
Confirm network and operational access
Validate port rate, transfer allowance, address requirements, remote management, hardware replacement scope and monitoring. Document backup and recovery independently of disk redundancy.
Create a configuration brief for a database workload
For a database, begin with the active dataset, expected growth, query concurrency and latency target. Record memory usage and storage latency under real queries. A larger disk can solve a capacity problem without solving an I/O bottleneck; more CPU cores may not help a serial query.
Then specify processor requirements, usable storage after RAID, backup location, port capacity, transfer and remote console access. Ask how a failed disk is replaced and how the service is recovered after a full machine failure. Validate the proposed machine with a representative workload rather than an isolated synthetic score.