On november 18, 2025, a major global outage impacted Cloudflare and AWS, causing widespread downtime.
High-profile services affected included OpenAI, X (formerly Twitter), Valorant, and many other popular platforms.
The outage affected major cities in india like Mumbai, Delhi, Bengaluru, and Chennai, according to Downdetector.
Even platforms used to track outages, like Downdetector itself, experienced temporary disruptions.
This follows a similar AWS outage in october, highlighting the vulnerability of major cloud infrastructures.
How DeepLearningAI Avoided the Outage
DeepLearning AI managed to stay online despite the Cloudflare collapse.
Founder Andrew Ng shared on facebook how their team leveraged AI coding to tackle the situation.
The team quickly implemented a clone of basic Cloudflare functionalities using AI, keeping the website operational.
Andrew Ng praised the team: “Really proud of the DeepLearningAI team…we came back up long before even major websites!”
Essentially, AI helped replicate essential Cloudflare capabilities, allowing the site to function while others struggled.
This incident showcases how AI can be used responsibly to solve critical infrastructure problems in real time.
The Scale of the Outage & industry Reactions
The outage caused global disruption, impacting tech giants, gaming platforms, and popular apps.
Even social media platforms like X were affected, with downtime reported worldwide.
In comparison, during the october AWS outage, Elon Musk publicly highlighted that X stayed online while competitors like Snapchat and Roblox faced downtime.
This time, Musk has not released any statements, even though X also experienced downtime.
The event sparks conversations about cloud dependency, infrastructure resilience, and AI as a proactive solution for unforeseen technical failures.
Key Takeaways
AI can be used effectively in crises, not just for automation or analytics.
Cloud infrastructure remains vulnerable, even for tech giants.
Proactive AI solutions like DeepLearningAI’s Cloudflare clone could be a model for future disaster recovery strategies.
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