Habib KaghasIf you've ever inherited an AWS account, you know the feeling. You open the console, click around a...
If you've ever inherited an AWS account, you know the feeling.
You open the console, click around a few services, and realise pretty quickly that you have no idea what's actually running. EC2 instances nobody recognises.
Security groups with ports open that shouldn't be. S3 buckets from three projects ago. RDS instances that might still be in use β or might not.
Itβs nobodyβs fault. AWS sprawl happens when a team moves quickly over time.
The problem is, most of the solutions people reach for don't actually solve it.
π Spreadsheets. Someone on the team volunteers to document everything
manually. It takes a week, and by the time it's done, it's already out of date.
AWS moves faster than any spreadsheet.
βοΈ AWS Config. Powerful, but complex to set up, expensive at scale, and it gives you raw data β not insight. You still have to do all the interpretation yourself.
π±οΈ Clicking through the console. This is what most people actually do.
Service by service, region by region. It works until you have 10+ services and multiple regions, at which point it becomes a full-time job.
π The script someone wrote that one time. You know the one. It's in a private repo, untouched for 18 months, and three people have contributed to it without informing each other.
None of these gives you a complete, accurate, up-to-date picture of your infrastructure. And without that picture, everything else β compliance, security reviews, cost optimisation, incident response β becomes harder than it needs to be.
Earlier this year, we built InfraMind to solve exactly this problem.
The idea was simple: connect it to your AWS account, and get a complete map of everything running β automatically, in under a minute, without writing a single line of code.
Here's what actually happens when you run it:
EC2, RDS, Lambda, S3, VPC, EKS, ECS, IAM, CloudFront, Route53, and 45 more.
Every resource, every region, pulled in one pass.
Not just listing resources β actually understanding them. It identifies misconfigurations, unused resources, security gaps, and relationships between services. The kind of analysis that would take a senior engineer hours to do manually.
Overview, network topology, security, database layer, serverless, and storage.
Auto-generated, always in sync with your actual infrastructure. No Lucidchart.
No draw.io. No manual updates.
This one is huge if you're trying to get your infra under version control.
InfraMind generates production-ready Terraform for what's already running β so you can start managing existing resources as code without writing it all from scratch.
CIS Benchmarks Β· PCI DSS Β· HIPAA Β· SOC 2 Β· ISO 27001 Β· GDPR Β· NIST SP
800-53 Β· FedRAMP
One click, full report, no consultants required.
When we started testing it internally, we thought the Terraform export would be the most-used feature.
It wasn't. The thing people kept coming back to was the architecture diagram β specifically the moment when they saw their actual infrastructure mapped out visually for the first time.
For some teams, that was a "oh that's what we have" moment. For others, it was more like "wait, why is that connected to that?" Either way, it's information they didn't have before, and it changes how the team talks about the
infrastructure.
One last thing worth mentioning: InfraMind doesn't just give you a one-time snapshot. It monitors your infrastructure for changes and sends alerts to Slack when something shifts.
| Event | Alert |
|---|---|
| New resource spun up | β Slack and email notifications |
| Security group modified | β Slack and email notifications |
| Resource deleted | β Slack and email notifications |
| Compliance status changed | β Slack and email notifications |
There's a free plan at app.solidstack.ae β no credit card needed. Connect your AWS account, and you'll have a full map of your infrastructure in under a minute.
If you're managing AWS at any scale and you've ever felt like you're flying blind, it's worth 60 seconds to find out what's actually there.
Questions or feedback welcome in the comments β especially if you've dealt
with AWS sprawl differently. Always curious how other teams handle it.