Most early AWS problems are permissions and surprise bills, not scale. An early-stage review sets up the few things that are painful to change later: separate environments and accounts, least-privilege access, infrastructure as code and cost alerts, and checks that the product is ready for its first real traffic.
Best for: solo founders and pre-seed / seed startups · teams building trading or market-data systems · B2B AI vendors rolling out to enterprise sales teams.
Selected cases from these experts’ profiles.
A seed startup runs on AWS that grew by clicking in the console. The expert reviews accounts and environments, IAM, networking, data stores, deployment and cost.
A ranked list of risks (security, cost, reliability) and a target setup the team can move to step by step.
A solo founder built an MVP with AI coding tools and wants to put it in front of paying users on AWS. The expert checks secrets, auth, data storage, error handling, deployment and cost.
A fix list ranked by risk, and a minimal, repeatable deployment.
Cloud spend had grown without anyone owning it. One of our experts re-architected the AWS setup: consolidated serverless functions, optimized the database, scheduled non-production environments to shut down off-hours, and added observability. Outcome: cloud cost down about 30%.
The cloud bill grows faster than traffic.
Review node pools, autoscaling (including Karpenter), idle and non-production environments, data transfer and storage, and how capacity changes are managed.
A prioritized savings plan with the risk of each change to peak capacity spelled out.
— Invental · software studio · Montevideo, UY
Describe the system and the question. We match a lead expert from this page, or a better fit from the network, and confirm scope before anything starts.
A link or short description of the code or system, what you want checked, your stack, and when you need the answer. No repository access is needed until scope is agreed.