Cloud Playground
A scenario modelling environment for planning multi-cloud architectures, costed against live provider pricing with full provenance for every figure.
At a glance
| Route | /cloud-playground |
| Group | Analyze |
| Page permission | intelligence |
What it is
A scenario modelling environment for planning multi-cloud hosting architectures. You compose an architecture, receive recommendations, and simulate cost across providers using live pricing with full provenance for every figure.
Who it is for
Architects and platform engineers making hosting decisions, and finance teams who need those decisions costed before commitment.
How it works
The playground maintains a service catalogue and directory across AWS, Azure, GCP, and OCI, priced from each provider's live pricing API.
Seeding from your real estate
Scenarios can be seeded directly from your current workspace's actual estate — so a migration can be modelled from reality rather than from a blank page or an idealised diagram.
Pricing provenance
Provenance is carried through the simulation, so every figure can be traced to the pricing source that produced it. This is what makes the output usable in a procurement or architecture decision rather than merely indicative.
Features
- Multi-cloud service catalogue and service directory across four providers
- Scenario creation, editing, duplication, and deletion
- Seeding a scenario from the current workspace's real estate
- Architecture recommendation generation
- Cost simulation with live provider pricing
- Full pricing provenance for every figure
- Scenario export
- Workspace readiness assessment for scenario modelling
How to use it
Create a scenario
Either from scratch, or by seeding from your current estate — the latter is almost always more useful.
Compose the architecture
From the service directory, across the providers under consideration.
Request recommendations
To surface options that may not have been considered.
Run the simulation and compare total cost across providers
This is the comparison that is otherwise prohibitively slow to produce by hand.
Inspect pricing provenance on the figures that drive the decision
List price and effective price can differ substantially. Check the provenance on anything load-bearing before you commit to it.
Duplicate to model variants
Rather than overwriting your baseline.
Export the result
For the architecture or procurement decision record.
Why it matters
Hosting decisions are frequently made on intuition, or on list prices found in documentation — then discovered to be wrong once the bill arrives.
Modelling the architecture against live pricing before committing turns a guess into an analysis. And seeding from the real estate means migration modelling starts from what actually exists rather than an idealised diagram.
Connects to
- Pricing shared with PR Cost Review and Deploy & Migration
- Scenario seeding reads from Inventory and the spend ledger
- Computed within Intelligence
Predictive Analytics
Forecasting with two competing models and automatic selection, honest error metrics, risk scenario modelling, and change-impact simulation.
Deploy & Migration
Repository-to-cloud deployment planning — analyse a repo, compare deployment paths across clouds, generate infrastructure blueprints, and run the migration.