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The Morning Everything Stopped

I remember it clearly. October 20th. I was in my Ho Chi Minh office, coffee in hand, scrolling through Slack messages like any other morning. But something felt off. The notifications weren’t coming through like they usually do. Teammates in the US weren’t responding. Internal services were timing out. At first, I thought it was a personal issue—maybe my internet was acting up. But then the reality hit: it wasn’t just me. It was everyone.

That morning, I watched the internet slow down in real-time. Snapchat, Reddit, Coinbase, even our internal AWS-dependent tools—everything went quiet. And for about 15 hours, I learned what it feels like when a cloud giant stumbles.

What Actually Happened

Let me be honest: I’m not a AWS insider, and I don’t have access to their internal reports. But from piecing together what I observed and what the industry reported, here’s what I understand happened.

A faulty automation script inside AWS’s DNS management system removed critical DNS records for DynamoDB—one of their most fundamental services. DNS is like the phonebook of the internet. When those entries disappeared, systems couldn’t find the services they needed. It’s like if Google Maps suddenly forgot where every restaurant was. Everything still existed, but nobody could find anything.

What struck me was how a small automation bug cascaded into a global disaster. It wasn’t a hardware failure or a cyber attack. It was code that was supposed to help, but it broke instead. And because so many services depend on AWS, the domino effect was inevitable.

The Real Impact Nobody Talks About

Yes, Reddit went down. Yes, millions of people couldn’t access their favorite apps. But here’s what really bothered me: the uncertainty.

During those hours, nobody really knew when things would come back. AWS’s status page was updating, but there was a lag. People were panicking. Teams couldn’t coordinate because their communication tools were down. Some banking systems were affected, which meant people couldn’t access their money. That’s not just inconvenient—that’s terrifying.

I saw teams scrambling. Developers who had built their entire product on AWS realized they had no backup plan. Startups that couldn’t afford downtime watched their metrics crash. And honestly? I wasn’t immune to this feeling either. If my projects had been hosted entirely on AWS without redundancy, I would’ve been in the same boat.

That’s when it hit me: we’ve become too comfortable with the idea that the cloud is bulletproof. It’s not.

Why This Matters for You

Here’s the thing—whether you’re a solo developer, running a startup, or managing enterprise infrastructure, this outage should make you think. Most of us have bet our businesses on cloud infrastructure. AWS, Google Cloud, Azure—we trust these platforms because they have better uptime than we could ever build ourselves. And that’s probably still true.

But “better than we could build” doesn’t mean “will never fail.”

The AWS outage proved that even the most robust, heavily-invested infrastructure can break. And when it does, the impact is global. Your users don’t care that it’s AWS’s fault—they just know your service is down.

The Hard Truths I Learned

1. Single Region Deployments Are a Liability

I’ve worked with projects deployed only in US-EAST-1. It’s convenient, cheap, and fast. But it’s also a single point of failure. When that region went down, there was no fallback. No users in Europe could be routed elsewhere. No graceful degradation. Just a wall of 503 errors.

2. Multi-AZ Isn’t Enough Anymore

AWS has Availability Zones (AZs) within regions for redundancy. But the October outage showed that regional-level failures can take out multiple AZs at once. Having three AZs in the same region is like having three fire extinguishers in the same room—if the room is on fire, they don’t help much.

3. Automation Can Become Your Worst Enemy

The irony wasn’t lost on me: the code that was supposed to automatically fix problems ended up breaking everything. This taught me that automation is powerful, but it needs guardrails. Testing automation scripts in production is risky. You need staging environments. You need kill switches. You need humans who can actually understand what’s happening.

4. Your Backup Plan Needs a Backup Plan

If your disaster recovery strategy is “switch to another region on AWS,” you’re still betting on AWS. What if the entire platform has an issue? What if it takes longer than expected to switch? You need to think beyond your primary cloud provider.

5. Communication Matters as Much as Technology

During the outage, AWS’s communication was delayed. People didn’t know how long things would take to recover. Uncertainty caused panic. As a builder, I realized that having a solid technical foundation means nothing if you can’t tell people what’s happening.

What I Would Have Done Differently

If I could rewind and redesign systems with the knowledge I have now, here’s what I’d change:

Multi-Region from Day One

Not “we’ll add it later.” From the start. Yes, it costs more. Yes, it’s more complex. But the cost of an outage is usually much higher.

Invest in Multi-Cloud Strategy

I’m not saying abandon AWS. AWS is great for many things. But for critical services, having a portion of your infrastructure on Google Cloud or Azure as a fallback isn’t paranoid—it’s smart. When AWS goes down, you’re still operational.

Build Observability Into Everything

Before the outage, I didn’t fully appreciate how important monitoring and alerting are. I do now. You need to know when things start degrading before they completely fail. You need dashboards that show you the health of your infrastructure across regions and providers.

Test Failure Scenarios Regularly

This is something I used to skip. “We don’t have time for disaster drills.” But the AWS outage was a disaster drill that cost businesses millions. Netflix does this with something called Chaos Monkey—they deliberately break things in production to see what happens. I started thinking we should all do something similar.

Have a Runbook Ready

If your system fails, what’s the first thing you do? How do you communicate with your team? How do you handle customer support? You need this documented. Not buried in Confluence somewhere. You need it accessible and updated regularly.

Practical Steps to Protect Yourself

Immediate Actions:

  1. Audit Your Current Setup

    • Where are your services hosted? Single region? Single cloud provider? Single data center?
    • What would happen if that became unavailable? Can you quantify the impact?

  2. Identify Your Critical Services

    • Not everything is equally important. Your authentication system is more critical than your blog. Your payment processing is more critical than your recommendation engine.
    • Rank them. Protect the critical ones first.

  3. Set Up Multi-Region Failover

    • This doesn’t have to mean running full replicas everywhere. But for critical services, have a secondary region ready.
    • Test that failover actually works. I can’t stress this enough.

Medium-Term Changes:

  1. Diversify Your Infrastructure

    • Consider running non-critical services on a different cloud provider. This gives you flexibility and teaches you how to manage multi-cloud environments.
    • Hybrid approaches are becoming more common. They’re not just for enterprise—they make sense for anyone running critical systems.

  2. Improve Your Monitoring

    • Set up alerts that notify you before systems completely fail. Know when error rates spike, when latency increases, when databases slow down.
    • Use tools like Datadog, New Relic, or even open-source solutions like Prometheus.

  3. Document and Rehearse Your Disaster Plan

    • Write down what you’d do if your primary region went down. Then actually practice it in a staging environment.
    • Make sure your team knows the plan. People panic less when they have clear steps to follow.

Long-Term Strategy:

  1. Build Cloud-Agnostic

    • Use containerization (Docker, Kubernetes) to make your services portable across cloud providers.
    • Avoid lock-in with proprietary services where possible. Use abstractions.

  2. Invest in Developer Education

    • Your team needs to understand cloud architecture, not just how to deploy to AWS.
    • Foster a culture where thinking about failure and resilience is normal, not paranoid.

The Bigger Picture

The AWS outage wasn’t really about AWS. Well, it was, but it’s also about something bigger: our dependence on centralized infrastructure.

We’ve built an internet where a single bug in a single company’s automation can affect millions of people globally. That’s not sustainable long-term. It’s not evil—it’s just how technology evolved. But it means we need to be smarter about how we build on top of it.

The irony is that cloud computing was supposed to make things more reliable. And in many ways, it has. But it also concentrated risk. The “cloud” is just someone else’s computers, and we’ve put a lot of eggs in relatively few baskets.

I’m not saying we should abandon the cloud. That ship sailed years ago. But I am saying we need to be more intentional about how we use it. Treat cloud providers as tools, not as guarantees. Plan for failure, not just success.

Today AWS, Tomorrow Anyone

Here’s the wake-up call nobody wants to hear but everyone needs to: if AWS can go down like this, so can Google Cloud. So can Azure. So can any cloud provider.

This wasn’t some freak accident or unprecedented disaster. It was a DNS bug triggered by faulty automation. If it can happen to the world’s largest cloud provider with billions in infrastructure investment, it can absolutely happen anywhere.

And that’s exactly why you need to act now.

Don’t wait for Google Cloud to have a similar incident. Don’t wait for Azure to experience a regional failure. Don’t convince yourself that “it won’t happen to us” or “we’ll deal with it when it happens.” By the time it happens, it’s too late. Your users are already gone. Your revenue is already bleeding. Your reputation is already damaged.

I’m not trying to scare you—I’m trying to save you from the same panic and scramble I witnessed during those 15 hours. The teams that survived the AWS outage with minimal damage were the ones who had already prepared. The ones who suffered the most were the ones who thought they didn’t need to worry.

So here’s my warning: Take your prevention measures now. Build redundancy into your systems. Test your disaster recovery plans. Diversify your infrastructure. Stop putting all your trust in a single provider, no matter how reliable they seem.

Because cloud providers are not infallible. They’re run by humans writing code that can break. And when it breaks, you don’t want to be the one scrambling to explain to your users, your investors, or your team why you weren’t prepared.

Don’t get caught with your infrastructure down.

Final Thoughts

The October 2025 AWS outage taught me more about system design than any course or book ever could. It forced me to confront assumptions I didn’t even know I was making.

Here’s what I’m taking away: reliability is hard. It’s not something that happens by accident. It requires planning, investment, and sometimes uncomfortable conversations with stakeholders about spending more money on infrastructure that hopefully never gets used.

But that’s exactly why it’s worth doing. Because the morning when things do go wrong—and they will—you’ll be glad you prepared for it.

If you’re building anything that matters, please don’t skip this. Test your failovers. Diversify your infrastructure. Think about what happens when things go wrong, not just when they go right.

Your users will thank you. Even if they never know you saved them from a disaster.

Let’s Connect

If this post resonated with you, I’d love to hear your thoughts and experiences! Have you been through a cloud outage? What’s your disaster recovery strategy? Drop a comment below or connect with me on LinkedIn for more insights on cloud architecture, DevOps, product management, and building resilient systems. Let’s learn and grow together.

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