There’s a special kind of silence that hits a dev team when the internet goes down. Not your local Wi-Fi, not your ISP having a moment I mean when the actual fabric of the web suddenly decides it needs a long nap.
And for some reason, this past month felt like watching three raid bosses take turns unplugging the server.
First AWS stumbled. Then Azure tripped over its own identity layer. And now Cloudflare the company that literally markets itself as “the internet’s immune system” managed to yeet half the web off the map for a while. If you were online, you felt it. If you were on-call, my condolences. If you were an SRE… well, you probably already have the thousand-yard stare.
Somewhere out there, an SRE bingo card is now fully stamped.
Here’s the thing we don’t like admitting: these companies aren’t superheroes. They’re just incredibly large, incredibly complicated distributed systems held together by protocol glue, load balancers, and engineers who drink more coffee than any doctor recommends. When one fails, everything built on top of it fails… loudly.
And because we’ve shoved most of modern civilization onto the same three clouds, every outage feels like the world briefly forgot to save its progress.
TL;DR:
In the span of about thirty days, three of the biggest US infrastructure giants hit major outages. It’s not a coincidence, not incompetence, and not a sign the cloud is dying. It’s something deeper, messier, and honestly a little terrifying about how our internet is built. So let’s break down what happened, why it keeps happening, and what devs can actually do besides panic-refreshing status dashboards.
What actually happened this month
The funniest part of these outages is how every one of them started with the same collective reaction from devs worldwide: “Is it me? Did I break something?”
Spoiler: no. It was the internet again.
Let’s speedrun the carnage.
First up: AWS.
Every time AWS hiccups, half the SaaS ecosystem collapses like it was built out of wet cardboard. This time it was a cocktail of routing weirdness and service dependencies misbehaving. Not the dramatic “us-east-1 is fully on fire” type outage, but enough to break logins, dashboards, and anything leaning too hard on specific metadata paths. Classic AWS mood swings.
Then Azure took its turn.
Identity and auth issues rippled across apps like someone unplugged the wrong cable and whispered “good luck.”
You know it’s bad when your cloud provider’s login page becomes the boss fight. People couldn’t authenticate; services couldn’t verify tokens; entire orgs watched their SSO flows crumble in real time. Not a full meltdown, but the kind of outage that makes enterprise admins stare into the distance.
And finally: Cloudflare decided to surprise-drop its own expansion pack.
A config issue in the global network routing layer caused widespread disruption the kind that makes CDNs look like a single point of failure disguised as a performance miracle. Cloudflare’s backbone is absurdly fast, absurdly global, and absurdly interconnected… which is great until it isn’t. When one piece wobbles, the entire internet feels tipsy.
Put all three together and it’s basically the Chaos Dunk of outages.
DNS stuttered, CDNs blinked, auth flows died, dashboards cried, and every developer alive refreshed status.cloud.google.com just to be safe.
Watching these outages back-to-back wasn’t a coincidence it was a reminder that our entire digital world is a giant dependency graph built on top of a few companies who are one misconfigured routing rule away from global mayhem.
Why modern internet architecture is basically a chaos dungeon
Here’s the uncomfortable truth about the modern internet: it’s not a neat stack of well-behaved services politely handing packets to each other. It’s a sprawling labyrinth of proxies, queues, caches, containers, retries, rate limits, BGP announcements, feature flags, and “temporary” workarounds that somehow made it into production.
If Elden Ring had a zone called Distributed Systems, this would be it.
We like to pretend cloud architecture is elegant. Clean. Rational.
In reality? It’s a bunch of microservices duct-taped together with YAML and optimism. Things work most of the time, which tricks us into believing they work all the time.
Take Cloudflare’s incident as a microcosm: one routing change propagates across a globally distributed network, and suddenly millions of requests start bouncing around like they’re stuck inside a pinball machine. It’s not incompetence this is what happens when your infrastructure spans continents and your configuration changes have the blast radius of a miniature sun.
Or think about Kubernetes. I love K8s, but let’s be real:
One missing indentation in a YAML file and suddenly your entire deployment is cosplaying as Schrödinger’s Pod both healthy and very not healthy at the same time.
I still remember deploying a tiny update to a “non-critical” service years ago. One tiny change. One. Yet somehow it triggered cascading failures that took down three unrelated services and two cron jobs. That moment taught me more about distributed systems than any textbook: complexity punishes confidence.
And that’s the thing as internet architecture grows more distributed, each failure mode gets weirder. Less obvious. More creative.
If your personal side project can collapse because Redis got moody, imagine a global CDN with thousands of points of presence, each juggling routing, caching, TLS termination, load balancing, and firewall rules.
The internet isn’t fragile because engineers are bad at their jobs.
It’s fragile because we built a monster so big and interconnected that sometimes it forgets how its own limbs work.
The fragility multiplier: everything depends on everything else now
Here’s the plot twist about modern cloud outages:
Half the time, it’s not even the cloud itself that fails it’s everything built on top of it collapsing like a Jenga tower made of API calls.
We’ve accidentally engineered a world where one misbehaving service can domino through half the internet. And honestly? It makes perfect sense. A “simple” modern app now depends on:
- A DNS provider
- A CDN like Cloudflare
- An auth layer (Auth0, Cognito, Supabase, take your pick)
- A database (Postgres, Mongo, Dynamo)
- A queue (SQS, Rabbit, NATS)
- A storage bucket
- A deployment platform (Vercel, Fly.io, Render, Netlify)
- CI/CD pipelines
- Monitoring
- Logging
- Third-party APIs sprinkled everywhere for “DX”
Your average startup is basically a very expensive glue project.
This is why Cloudflare outages feel like boss battles. Even if your app is hosted on AWS or Azure, you still probably rely on Cloudflare for DNS resolution, caching, firewalling, bot protection, or speed boosts. When Cloudflare sneezes, your login page catches a cold.
There was a legendary outage years ago where one S3 region went down and half the internet folded instantly. Not because S3 was the only storage layer in town but because everyone used it at the same time.
The problem isn’t just complexity, it’s centralization.
We’ve clustered our infrastructure around a few mega-providers because they’re fast, cheap-ish, global, and convenient. And honestly? They work incredibly well until they don’t.
I had a deployment blocked once because GitHub Actions had an outage. Nothing was technically wrong with my service, but CI/CD was the single point of failure I pretended didn’t exist. The pipeline was down, so my entire release plan evaporated.
When you zoom out, you start seeing the real issue:
We traded simplicity for speed, resiliency for convenience, and control for scalability.
And now everything is so interconnected that one outage feels like a multiplayer wipe.
Are outages actually becoming more common… or just louder?
Every time a big provider goes down, Twitter sorry, “X” lights up like someone dropped a Mentos into a gallon of Red Bull. Outage memes, graphs, theories, corporate statements, angry customers, your uncle asking if “the hackers got in”… it becomes a whole cultural event.
So it’s fair to ask:
Are these outages happening more often, or are we just hearing about them more?
Honestly? It’s both, but not in the way you think.
First, the internet is bigger than it’s ever been. Not in a poetic sense literally. More apps, more workloads, more users, more dependency chains, more traffic, more everything. Even tiny performance hiccups now cascade into full-blown outages because scale amplifies weirdness. A routing loop that used to annoy 5% of requests now slams millions.
Second, the stakes are higher.
We moved critical infrastructure online that used to be offline: banking flows, supply chains, work apps, healthcare systems, logistics, identity, authentication. When Azure’s identity platform stumbles, you don’t just break logins you break entire companies.
Third, social media acts like a global alarm system.
The second something flinches, someone screenshots a failed request and posts it. Status pages get refreshed like it’s a mobile gacha game. Reddit threads explode. Hacker News collectively panics and starts debating DNS propagation like it’s a spectator sport.
It creates the illusion that outages are exploding, when really what’s exploding is visibility.
Cloudflare publishes incredibly detailed transparency logs. AWS posts event summaries. Azure documents every blip. That’s great for accountability… but it also turns every regional issue into breaking news.
Here’s the interesting twist: statistically, these services are more reliable than ever. But our tolerance is lower because our dependency is higher.
When everything in your stack relies on someone else’s stack, even a tiny wobble feels like a system-wide catastrophe.
So yes, outages feel worse. Because they are worse not in frequency, but in impact. The blast radius keeps getting bigger.
Which brings us to the real question: what can devs actually do about it?
What devs can actually do (besides panic-refreshing dashboards)
Let’s get something out of the way: you can’t “prevent” AWS from wobbling, Azure from forgetting who you are, or Cloudflare from deploying a config that sends half the internet into the Shadow Realm. That’s above our paygrade.
But you can do a lot to make sure your app doesn’t instantly melt the moment one of the Big Three has a bad day.
Here’s the real, practical, engineer-to-engineer checklist no corporate fantasy talk, no “just go multi-cloud!” nonsense.
1. Build graceful degradation like you actually expect things to break.
Static fallback pages. Cached API responses. Limited functionality modes.
If your app’s login system collapses the minute Auth0/Cognito blinks, you’re basically speedrunning downtime. Caching and fallbacks are cheap life insurance.
2. Stop pretending you don’t have single points of failure.
Your DNS? SPOF.
Your CI/CD provider? SPOF.
Your database? Massive SPOF.
Your one weird third-party API you integrated on a Friday? The biggest SPOF of all.
Half of resilience engineering is admitting where you’re weak.
3. Use redundancy you’ll actually maintain.
Multi-region? Great.
Multi-cloud? Possibly great… if you enjoy pain and drama.
A hybrid approach works for most devs: deploy core assets in two regions, keep static assets mirrored, and use providers with good fallbacks (e.g., Cloudflare + Netlify + Fly.io for small apps).
4. Add automated checks, not vibes-based monitoring.
Status pages are fine, but they’re lagging indicators.
Use real tools:
- Uptime Kuma
- Pingdom
- Grafana Cloud
- Synthetic checks hitting real endpoints
- Heartbeat monitoring for background tasks
5. Fail loudly but informatively.
If users get a blank white screen, they assume you died.
If they get a “fallback mode: things might be slow,” they assume you’re a genius who planned ahead.
I once shipped a “read-only mode” feature that felt pointless… until the provider hosting our write layer had an outage. That tiny fallback saved an entire release cycle.
You don’t need to build bunker-grade infra. You just need to build something resilient enough that a single provider outage doesn’t delete your whole weekend.
Now let’s wrap this up with the bigger picture the part nobody likes admitting.
Conclusion: maybe the cloud isn’t broken… maybe it’s just grown too big to feel stable
After watching AWS, Azure, and Cloudflare wobble back-to-back, it’s tempting to declare that “the cloud is falling apart.” It’s not. What’s actually happening is way more boring, way more predictable, and way more honest: we’ve built an internet so massive, so interconnected, and so dependency-loaded that perfect reliability is mathematically impossible.
That’s not a failure it’s physics.
When your infrastructure spans countries, continents, fiber routes, autonomous systems, authentication chains, edge caches, TLS termination layers, and thousands of microservices, stability isn’t a guarantee… it’s a rolling probability check. And occasionally, the dice come up snake eyes.
What feels new is the impact. Outages used to break a few sites. Now they break workflows, businesses, pipelines, SSO, content delivery, and sometimes the entire weekday vibe. We’re not just building blogs anymore; we’re running whole companies in the cloud.
And maybe that’s the perspective shift:
The cloud didn’t get less stable. We got more dependent.
Here’s the part I think matters most: none of this is going to slow down. We’re pushing more workloads to the edge. More compute into serverless. More AI-assisted everything. More global, distributed, fantastically powerful infrastructure. And with every new connection, we introduce new failure modes.
But that’s okay. Reliability doesn’t come from eliminating outages it comes from designing systems (and expectations) that survive them.
So keep your fallbacks ready, your dashboards bookmarked, and your status pages refreshed. The cloud isn’t dying.
It’s just reminding us that we’re building something far bigger than we ever planned for.
And honestly? It’s kind of amazing we keep it running at all.
Helpful resources
- Cloudflare incident reports: https://www.cloudflarestatus.com/
- Azure status history: https://status.azure.com/en-us/status
- GitHub: Uptime Kuma (great for self-hosted monitoring): https://github.com/louislam/uptime-kuma
- Reddit r/devops outage discussions: https://reddit.com/r/devops
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