Home/Data center & cloud/Capacity Planning & Infrastructure Enhancement

Grow the platformbefore it hurts.

Six months of utilisation data, your growth plan and the vendor roadmaps — turned into a capacity model, a bottleneck list and a phased upgrade with a bill of materials. No over-buying, no surprise outage.

UtilisationCPU · RAM · IOPS · linksGrowthbusiness planModelheadroom · N+1 · trendsBottlenecksrankedPhased planBoM · tenderOutputs: capacity report · BoM · quarterly reviewSuzu Technology · Capacity Planning & Infrastructure Enhancement · sheet 47not to scale
Fig. 47 — Capacity modelUtilisation → Growth → Model → Bottlenecks
Data center & cloud

What we do

Capacity problems announce themselves months in advance — in IOPS latency, in memory ballooning, in a 10G uplink at 80%. We read those signals from your monitoring and turn them into a plan with dates.

Enhancement is not always more hardware: storage tiering, overcommit tuning, moving backups off production storage and fixing a noisy neighbour often buy a year.

Included
  • Data collectionZabbix/Prometheus/vCenter/Proxmox metrics, storage and switch counters
  • Capacity modelHeadroom per resource, N+1 impact, growth scenarios
  • Bottleneck reportRanked findings with quick wins and structural fixes
  • Enhancement planPhased BoM (servers, SSD/NVMe, switches, GPUs, backup), budgets, lead times
  • Procurement supportVendor-neutral specs, quote comparison, acceptance testing
How it runs

The engagement, step by step

01

Audit

We inventory what you run — hardware, hypervisors, storage, backups, network — and document the risks.

02

Blueprint

HLD/LLD with architecture, bill of materials, migration plan, budget and timeline, within 48 hours of the audit.

03

Build

Change-controlled implementation with MOPs, rehearsed cutovers and as-built drawings.

04

Operate

Monitoring, AMC or managed operations with monthly reports and quarterly reviews.

Commitments

What we put in writing

Written into the blueprint before work starts. If a number is not here, ask for it — we put it in writing.

Vendor-neutralWe do not resell hardware; specs favour you
Quarterly reviewModel refreshed every quarter under managed service
AcceptanceBurn-in and performance tests before sign-off
DocumentationUpdated HLD and inventory
FAQ

Questions we get asked

Can you size GPU capacity for AI workloads?
Yes — inference vs training, VRAM per model, utilisation targets and power/cooling impact per rack.
We have no monitoring data.
We deploy collectors for 4–6 weeks first; a plan without data is a guess.
Do you work with our existing vendor?
Yes; we write specs they can quote against and we check the quotes.

Send us your rack list or hypervisor inventory. The blueprint comes back in 48 hours.

Free audit call, written HLD, fixed-price proposal.