Your phone buzzes at 3 AM. It’s an email from AWS. Your stomach drops before you even open it. “Your bill for this month: $78,000.” You usually pay $200.
These AWS billing nightmares show how one misconfiguration can cost more than a luxury car, and forgetting to turn something off can literally bankrupt your startup. These are real disasters from real people who posted their nightmares on Reddit, Medium, and tech forums. I’ve included links after each story so you can read the full trauma yourself.
Cloud computing promises ‘pay only for what you use’ and ‘scale on demand.’ But without proper configuration of billing alerts and spending limits, you can scale to costs you cannot afford – and the cloud provider won’t stop you.
In this post I’m not criticizing AWS in any way. On the contrary, in some cases – as you will see – AWS customer support actually just canceled the bill. In addition, what happened in these stories can happen with any other cloud provider.
The $10,000 Infinite Loop That Wouldn’t Die
A startup founder shared their descent into madness on Medium, watching their AWS bill climb from $50 per month to $7,500, then to $10,000. This wasn’t a hack—this was pure self-sabotage.
Here’s what happened: They configured a Lambda function to trigger from CloudWatch Events using S3/CloudTrail. So far, so good. But then came the fatal mistake: they configured CloudTrail to log S3 events for ALL buckets—including the bucket where CloudTrail writes its own logs.
Let me paint the disaster: CloudTrail writes a log to S3, which triggers Lambda, which writes to S3, which triggers Lambda again, which writes to S3. It’s an infinite loop that keeps going. Like pointing two mirrors at each other, except instead of infinite reflections, you get infinite AWS charges.
The founder frantically disabled the triggers. But the bill kept climbing. Why? AWS had queued all those throttled Lambda invocations and was replaying them. They finally had to set concurrent execution limits to zero on every Lambda function before the bleeding stopped. They described being in “panic mode”—startup-speak for “I haven’t slept in 48 hours and I’m watching my bank account drain in real-time.”
The $14,000 Testing Mistake
A developer got hired to automate AWS Comprehend-Medical processing. Sounds straightforward: process some medical data, get paid and go home happy. Two fatal mistakes turned this into a $14,000 nightmare.
First mistake: During testing, they underestimated how many JSON files would trigger the automation. By “underestimated,” I mean they were off by orders of magnitude. Second mistake: they didn’t realize Comprehend-Medical costs twenty times more than regular Comprehend. Not twice as much, not five times. but twenty times.
The automation kicked off, files processed like crazy, and the billing meter went wild. By the time they caught it: $14,000 in their personal account that usually costs $50/month. This was supposed to be a test environment.
The developer’s advice? “AWS will not alert you to dramatic increases unless they bypass $15K.” That’s not a billing alert—that’s a bankruptcy notification that arrives after your credit card is maxed out.
The $45,000 Weekend Mining Operation
You’re enjoying your weekend when your phone rings. It’s AWS. Your bill is $45,000. Your normal spend? Basically pocket change.
What happened? Your AWS credentials got exposed on GitHub. Maybe you committed them at 2 AM when you were tired. Maybe you deleted them the next morning. But the internet never forgets—even deleted commits stay in Git history forever.
Bots scan GitHub 24/7 looking for exposed AWS keys. The moment you push that commit, you’ve got maybe five minutes before someone’s in your account. Within hours, hackers spun up GPU instances across multiple regions and mined cryptocurrency.
The scoreboard: Hacker’s profit was about $800. Your bill? $45,000. The economics make zero sense, but that’s not the hacker’s problem—it’s yours.
The $61,000 “I Forgot” Database
A Reddit user set up an AWS RDS database for a website project. Everything was running beautifully. Then they got pulled into another task and completely forgot about it. For three months.
The bills started arriving like a horror trilogy. Month one: $5,000. Month two: $32,000. Month three: $24,000. Total damage: $61,000.
That’s a down payment on a house. That’s a year of college tuition. All because they forgot to click “terminate instance.” AWS doesn’t auto-delete anything—your instances keep charging you forever, long after you’ve forgotten they exist.
The happy ending? AWS customer service refunded it. But imagine if they hadn’t. That’s instant financial devastation from a simple mistake.
The $500,000 Surprise
A SaaS startup’s CFO opened the AWS bill: $500,000. They usually paid $250,000. Doubling your cloud bill in one month causes actual heart problems.
What went wrong? Everything at once. Zombie resources everywhere – idle VMs, unattached storage, forgotten backups. Forgotten reserved instances paying for unused capacity. Over-provisioning. Zero monitoring. No alerts. Misaligned workloads on expensive instances.
The company’s budgets were shredded. Investor confidence tanked. Internal tensions hit top levels. Studies show 35% of cloud spend is wasted – this startup proved it the expensive way.
They eventually got control with proper tagging, monitoring, and automation. But not before that bill nearly killed the company.
The $2.3 Million Data Breach
In 2017, someone misconfigured an S3 bucket. Massive data breach. Sensitive customer data exposed to the world.
AWS didn’t say “oh no, you got hacked, our condolences.” They said “wow, look at all that data transfer! Here’s your bill: $2.3 million.” That’s right—the company got charged $2.3 million for data egress during their own security breach.
When your S3 bucket is publicly accessible and someone scrapes your data, AWS doesn’t give you a discount. They charge you for every byte that leaves their servers.
The $3.2 Million Annual Bill
Basecamp (now 37signals) looked at their 2022 AWS bill: $3.2 million annually. Just for S3 storage alone: $907,838. Plus another $66,742 for CloudFront data transfer.
Their CTO – the guy who created Ruby on Rails – did the math. They could buy Dell servers for $700K and save millions. So they did exactly that.
They migrated everything off AWS. By 2024, they’d saved $2 million. AWS even waived $250,000 in egress fees just to let them leave. That’s how expensive it is to exit AWS – they charge you six figures to download your own data.
Their next phase is exiting S3 completely, which will save another $1.3 million annually. Total projected savings: over $2 million per year.
How to avoid cloud billing disasters
There are several measures to put in place to avoid becoming another AWS billing nightmare.
Set billing alerts immediately. Not tomorrow. Now. Create CloudWatch alarms at multiple thresholds—$200, $500, $1,000. Costs can accelerate fast, so you need early warnings.
Enable AWS Budgets with actions. Configure automatic shutdowns when hitting spending limits. Yes, it might break your app. But bankruptcy also breaks your app – permanently.
Check Cost Explorer weekly. Look for unusual spikes. If you normally spend $50/day and suddenly it’s $500/day, you have hours before disaster strikes.
Tag everything. Every resource needs tags – project name, owner, environment. Without tags, you’re flying blind. With tags, you can hunt down mystery charges.
Set Lambda concurrency limits. Lambda scales infinitely by design. Set reserved concurrency limits so functions can’t spin up thousands of instances overnight.
Hunt zombie resources monthly. First of every month: delete orphaned EBS volumes, forgotten snapshots, unattached Elastic IPs, old AMIs, abandoned load balancers. These ghosts haunt your bill forever.
Never commit credentials to Git. Use IAM roles, Secrets Manager, environment variables—anything but hardcoded keys. If you screw up, rotate credentials immediately. GIT keeps a history of all changes, so just deleting the credentials isn’t enough – they’re still sitting in your commit history.
Understand data transfer costs. Within the same region: usually cheap. Between regions: expensive. To the internet: very expensive. Moving terabytes? You need to understand AWS egress pricing.
The Bottom Line
You can accumulate life-changing debt on the cloud in days. Unlike code bugs, this one can’t be rolled back. Most of the cloud provider’s Terms of Service are essentially a blank check with your signature.
These aren’t rare edge cases – they’re common mistakes made by students, developers, startups, and even experienced engineers who got distracted for one weekend. The only thing standing between you and a six-figure bill is constant vigilance.
Set your alerts. Check your costs. Delete what you’re not using. Stay paranoid. Because you won’t be warned until it’s too late. You will just receive a bill with a smile and a 30-day payment reminder.