Launching today
Cloud World Model
Simulate AWS, GCP & DigitalOcean without paying the bill
34 followers
Simulate AWS, GCP & DigitalOcean without paying the bill
34 followers
Simulate AWS, GCP, Azure, OCI & DigitalOcean architectures to predict cost, performance, and resilience without provisioning real resources or paying a cloud bill. Built for learners practicing cloud skills and AI agents training on cloud optimization.
Cloud World Model
Hi everyone! I'm Kevin Brown, one of the makers of Cloud World Model.
Cloud World Model lets you model AWS, GCP, Azure, OCI, and DigitalOcean architectures and instantly see how they behave CPU, error rates, throughput, autoscaling, failure recovery, and cost without provisioning a single real resource.
A few things we're proud of:
A capacity-aware engine that models real per-provider performance profiles
Chaos engineering: inject zone outages, DB crashes, and network partitions, then get a resilience score
A multi-cloud explorer that compares provider combos on cost, latency, and vendor lock-in
A full RL training API so AI agents can learn cloud optimization in a safe, cost-free environment
Beginner mode with plain-English AI explanations and an interactive tutorial
Whether you're learning cloud skills or training agents to optimize infrastructure, I'd like to hear any of the following in the comments?
How do you typically test cloud architecture changes before putting them in production or any environment?
Do you think a mechanism to be able simulate a cloud architecture change would be useful?
Any experiences with cloud cost comparisons?
Cloud World Model
BTW, you can try us headless using any of the popular tools like @Claude Code , @Codex or @Grok Build. The API is fully documented.
Here is even a starter prompt you can try:
The chaos engineering part caught my eye, injecting a DB crash and getting a resilience score back seems really useful for catching weak spots before prod. Curious how close the cost estimates land to a real AWS bill in practice. Congrats on shipping!
Cloud World Model
@i_sanjay_gautam Thank you, Sanjay. Yes, chaos engineering goes along way towards determining what happens when something crashes. We believe we are 95 to 98 percent accurate to the cost estimates of a real AWS bill. We have an accuracy benchmark which describes it here. https://www.cloudworldmodel.ai/accuracy
the cost simulation is the part i need most. i blew $400 on an RDS instance i spun up for "testing" and forgot about for 11 days. nobody warned me.
how granular does the cost projection go? if i model a 3-tier app does it tell me i'm about to pay for an over-provisioned NAT gateway, or just give me a total bill estimate?
the value of cost tools breaks for me at the line item level. that's where i actually make decisions.
Cloud World Model
@thenameisarian Hi, this is the scenario we are built for so the $400 RDS instance story hits home. The engine prices every resource in your architecture independently. So a 3-tier app isn't one blended number, it's the sum of its parts, and you can see which part is bleeding money. We are also a simulation engine, intended to simulate most times even before you deploy the architecture. If you change the architecture, simulate again. Thanks for the question.
@mathsociety this is the answer. the "simulate again after every architecture change" workflow is what i don't have anywhere else. terraform plan tells me what's changing, not what it'll cost.
added to my list to try this week. one more quick one: does the simulation cover spot instance pricing or just on-demand? the cost-prediction wins i actually need are usually in the gap between "what i provisioned" and "what i'm paying for at 2am during a scale event."
cheers for the thoughtful answer.
Cloud World Model
@thenameisarian pricing is on-demand today, spot/preemptible isn't modeled yet. So I won't pretend it does.
But the second half of what you said is the part we actually nail: the "what am I paying at 2am during a scale event" gap. Cost isn't a static number off your provisioned config, it's recomputed every simulation step as autoscaling adds and removes instances. So when traffic spikes and the fleet scales from 2 to 9 nodes, you watch the cost/hour climb in real time, and Aurora Serverless v2 cost tracks live ACU rather than a flat rate. That's exactly the gap between "what I provisioned" and "what the scale event actually costs me" modeled step by step, just at on-demand rates.
Spot pricing is a fair ask though, and it's the natural next layer. Comments like these is the reason we did Product Hunt to get a sense of what customers want. We’ll add it to roadmap.