Build your product with confidence. Our Cloud Cost Modelling Feasibility Studies provide clear, data-driven projections for hosting, bandwidth and autoscaling, helping founders, product teams and CFOs decide whether to proceed from MVP to scale.
We combine cloud-finance expertise, performance modelling and product strategy to give you a clear go/no-go recommendation, a cost-optimised scaling roadmap and the sensitivity analysis you need to manage risk.
What we deliver
- A detailed, line-item cost model (spreadsheet) covering compute, storage, bandwidth, CDN, managed services and licensing.
- Autoscaling projections tied to traffic and workload patterns, with estimated costs per scaling event.
- Multiple scenarios (MVP, Growth, Scale) plus a custom scenario if you have specific marketing or growth plans.
- Sensitivity analysis across traffic, pricing changes and reserve vs on-demand strategies.
- A one-page executive summary with a clear recommendation and risk score.
- A slide deck and a 45–60 minute walk-through call to align stakeholders.
Why a feasibility study matters
Every product claims to “scale,” but scaling cost-effectively requires modelling actual behaviour, not hope. A feasibility study lets you:
- Quantify monthly and annual cloud spend before committing to architecture or contracts.
- Identify cost drivers (eg. data egress, caching, long-lived instances, third-party services).
- Evaluate trade-offs: reserve instances vs on-demand, container orchestration vs serverless, edge CDN vs centralized hosting.
- Avoid costly surprises during launch or growth surges that can erode margins or sink investor confidence.
Our approach — rigorous, repeatable, transparent
We follow a structured methodology so you get reproducible, audit-ready results.
Step 1 — Data collection & grounding
We gather traffic forecasts, telemetry, product flows, user geography and third-party dependencies.
If you have historical metrics, we ingest them; if not, we build forecasts from comparable products and market benchmarks.
Step 2 — Modelling & toolchain
We model costs using cloud-provider pricing APIs, capacity planners and load-testing outputs.
Models cover compute (VMs, containers, serverless), storage tiers, bandwidth/egress, CDN, database IOPS and managed services.
Step 3 — Scenarios & autoscaling logic
We create scenario-driven projections with autoscaling triggers, queue/backpressure behaviour and cooldowns.
Each scenario includes best-case, expected and worst-case cost paths.
Step 4 — Sensitivity & recommendation
We stress-test the model against pricing shocks, traffic spikes and reserve strategy changes.
You receive a clear recommendation and an action plan to de-risk the product launch and scale phases.
Hosting & architecture comparison
| Hosting model | Cost predictability | Scalability | Typical use case |
|---|---|---|---|
| Virtual Machines (VMs) | Medium | Manual/Autoscaling groups | Predictable workloads with steady baseline |
| Managed Containers (EKS/AKS/GKE) | Medium-High | High with orchestration | Microservices and moderate bursts |
| Serverless (Lambda/FaaS) | Low start-up cost, higher per-request | Excellent for spiky traffic | Event-driven APIs and unpredictable bursts |
| Managed PaaS (App Services) | High predictability | Good but limited control | Fast time-to-market SaaS MVPs |
Use this table to match product needs against cost and operational trade-offs. We model each option against your traffic profile so you can pick the right fit.
Example scenario projections (illustrative)
| Scenario | Monthly active users | Hosting cost | Bandwidth cost | Autoscaling events | Estimated monthly total |
|---|---|---|---|---|---|
| MVP (low traffic) | 2,500 | Moderate | Low | 10–50 | Scenario-specific model supplied |
| Growth (marketing push) | 50,000 | Higher (scale-out containers) | Medium-High | 200–800 | Scenario-specific model supplied |
| Scale (national) | 250,000+ | Significant (multi-region) | High | 1,000+ | Scenario-specific model supplied |
We deliver your own spreadsheet version of the above with live formulas so you can test assumptions.
Key outputs & decision metrics
- Monthly and annual cost curves for each scenario.
- Break-even analysis showing cost per active user and cost per transaction.
- Threshold alerts: traffic or spend triggers where architecture must change.
- Reserve vs spot recommendation with savings estimates.
- Actionable roadmap: immediate changes to reduce spend and a 12–24 month scaling plan.
Who should commission this study
- Founders deciding whether to build or pivot an idea into an MVP.
- Product managers planning a paid acquisition campaign or geographic expansion.
- CTOs evaluating new architecture before major refactors.
- CFOs and investors needing a defensible cloud spend forecast for budgeting or term sheets.
Typical engagement & timeline
- Rapid Feasibility (2 weeks): Quick-turn cost model, recommended architecture, executive summary and a short walkthrough. Ideal for investor pitches or sprint planning.
- Standard Feasibility (3–4 weeks): Full scenario modelling, sensitivity analysis and a stakeholder workshop. Best for MVP planning and initial scaling.
- Comprehensive Feasibility (6–8 weeks): Deep-dive with load-testing, multi-region modelling, and a 12–24 month optimisation roadmap. Recommended for planned national or enterprise scale-ups.
Each engagement includes a walkthrough meeting and delivery of all model files and documentation.
Why MzansiWriters.co.za?
MzansiWriters.co.za blends technical cloud cost expertise with clear, persuasive documentation tailored to decision-makers. Our team has experience producing feasibility studies that combine:
- Cloud cost modelling and performance projections for SaaS products.
- Product-market fit and MVP staging that tie costs to business outcomes.
- Investor-ready executive briefs and technical appendices for engineering teams.
We present work in an accessible format so non-technical stakeholders can make fast, confident decisions.
Confidentiality & collaboration
We treat your data and projections as strictly confidential. We work under NDAs and provide source files so your engineering and finance teams can continue iterating the model.
Ready to decide with confidence?
Get a feasibility study that turns uncertainty into a clear decision. Contact us using the contact form on the right bar or by clicking the WhatsApp icon to start a conversation. Share basic product details or metrics and we’ll respond with a recommended engagement and next steps.