Amazon Web Services status: access issues and outage reports
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Amazon Web Services (AWS) offers a suite of cloud-computing services that make up an on-demand computing platform. They include Amazon Elastic Compute Cloud, also known as "EC2", and Amazon Simple Storage Service, also known as "S3".
Problems in the last 24 hours
The graph below depicts the number of Amazon Web Services reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.
At the moment, we haven't detected any problems at Amazon Web Services. Are you experiencing issues or an outage? Leave a message in the comments section!
Most Reported Problems
The following are the most recent problems reported by Amazon Web Services users through our website.
- Website Down (80%)
- Sign in (10%)
- Errors (10%)
Live Outage Map
The most recent Amazon Web Services outage reports came from the following cities:
| City | Problem Type | Report Time |
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Website Down | 8 days ago |
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Website Down | 11 days ago |
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Website Down | 1 month ago |
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Sign in | 2 months ago |
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Website Down | 2 months ago |
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Website Down | 3 months ago |
Community Discussion
Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.
Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.
Amazon Web Services Issues Reports
Latest outage, problems and issue reports in social media:
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mark seery (@140ismymax) reportedPeter DeSantis talking at #agenticaisummit There will NOT be one AI chip type. If multiple AI chips take multiple years to bring to market, you have to be making assumptions about model requirements in that time frame. It's a systems problem, including the network. Constraint drives innovation. Future is bright and built together. Peter DeSantis SVP, Foundational AI Models, Custom Silicon, Quantum Computing, Amazon @awscloud @amazon @BerkeleyRDI
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Certified AI Dev (@MisterPrashant) reportedThis solution to this problem is AI traffic monetization. If you are an owner of a platform that provides some valuable data, you can put the data behind a paywall for the AI traffic by charging the bot fraction of a penny for using your content. x402 Payment Required protocol tells the bot that the content requires payment and the bot settles the transaction quickly on a stable coin at which point the content becomes accessible. This way,people running their search bots does not require subscription to 10 different services and can easily access data from anywhere at a very minimal cost and the owners of the sites also win as the traffic count to their paywalled site will generate income. This is not a concept. The framework to build this is already available in @awscloud today.
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Mon (@mon73x) reported@asimrazax @AWSSupport I have the same problem. Did you fix it?
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Priyanshu (@iproductAI) reportedI requested @awscloud to increase my Opus 4.6 V1 limit and I’ve been chatting with the AWS support team for almost 4-5 days now. They’re telling me this. Is @awscloud a government company? I mean, you guys can’t just pass the problem from one department to another. I mean, WTF? Now I have to raise my query again to sales? Why can’t you just pass this query? You already have more context about what the issue is. I can’t believe how these big MNCs are working these days. Totally absurd service from @awscloud. One more thing, please educate your support. I mean, she didn’t even know what the TPD limit is in the service quota. She literally replied the first time saying there’s only a TPM limit and no separate TPD limit.
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Gerzson (@Gerzsononline) reported@slap__tjips @awscloud Gosh ai haters are so ******* dumb they just assume and blame it on ai for a funny error that didn’t result in any wrong
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Jaden Fix (@jadenfixxx) reportedAnyone at @googlecloud or @awscloud (or a neocloud) wanting to slide into my DMs and help me rip some free credits? Possibly leading to larger contracts down the road .. I just tried signing up for an @Azure free trial, and the experience felt like what I imagine the elders went through with dial-up internet. Solutions Architects or Account Managers HMU
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Matthew (@OneShotCaller) reported@CalebChamberla6 It’s an AWS billing error (see @awscloud)
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Prateek Gupta (@p_valuee) reportedAWS suspended my account for billing. I have zero due invoices and zero past-due invoices. Their own Amazon Q agent confirmed it in writing. P1 case 178635853400575, day 3, production still down. @AWSSupport what is the actual reason?
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Brian Porter (@kbporter) reported@amazon @awscloud @AmazonHelp why do I have to continually contact you on social media for issues with your service? Why is your customer service online “help” so bad? $5 credits for delayed orders for a service we pay for is horrible!
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AntDracula (@ant_dracula) reported@kankerhoerrrrrr @marcelocantos @awscloud "skill issue" is a term only unironically used by losers and AI bots. I can take a guess at which one you are.
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Har (@duckboy1909) reported@awscloud fix your Alexa servers and fix your Bluetooth on app and devices! #alexadown #alexa #amazon
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golden gate bridge (@_ggbridge) reported@litteralyme0 this happens to me everytime Amazon AWS has an outage
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Harikrishna KP (@harikp2002) reported@AWSSupport Two days into migrating to AWS and both new accounts I created are locked out of every single service. S3, EC2, Lambda, DynamoDB, all of it. The accounts show as ACTIVE. Support confirmed it needs a manual fix from an internal team, then went quiet for 28 hours. Three open cases, one phone call, still completely blocked. Sitting on AWS credits I literally cannot spend. Do better please!
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Ben Newton ベン (@BenENewton) reported@awscloud Somewhere there's an IT guy lying on the ground next to his desk after opening the page with this error on it.
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TAPE Vector (@Tape_Vector) reportedJPP-KY $5284.TW is not an AI chip company. It makes the precision metal infrastructure that surrounds the chips, power systems and cooling hardware inside modern AI servers. That distinction matters. JPP Holding designs and manufactures precision metal mechanical parts, enclosures, cabinets and structural components. Its products are used across: AI server racks Server chassis Power supply housings Battery backup unit enclosures Liquid cooling components CDU and manifold structures Telecom equipment Aerospace avionics Aircraft structural and cabin parts Medical equipment Industrial systems The company is headquartered through a Cayman holding structure and listed in Taiwan, but much of the manufacturing engine sits in Thailand through Jinpao Precision Industry. That Thailand base is important. JPP is positioning itself between Taiwanese and global technology customers that increasingly want manufacturing capacity outside China. The operating model is high mix precision manufacturing rather than mass production of one standardized component. A customer brings JPP a mechanical design or performance requirement. JPP can then handle several steps internally: Engineering and design support Metal cutting Stamping CNC machining Sheet metal forming Welding Surface treatment Painting Assembly Inspection Final integration That means the company can take a customer from drawing to finished enclosure instead of supplying only one small step. For AI servers, this can include the physical rack or chassis holding compute hardware, power equipment and cooling systems. For aerospace, it can include avionics housings, structural parts and cabin components that require much tighter certification and process control. This combination is unusual. AI infrastructure gives JPP growth. Aerospace gives it another technically demanding end market with different cycles. The company describes this model as a mix of European engineering capability and Thai manufacturing. The phrase used by management has been: French brain. Thai heart. That comes from the European aerospace companies JPP acquired and integrated with its Thailand manufacturing base. The aerospace side matters because the qualification barriers are much higher than ordinary sheet metal fabrication. JPP has Nadcap certified processes and has worked within the European aerospace supply chain. Company materials and industry reporting have referenced customers and programs connected to Airbus, Thales and Safran. Those relationships do not automatically mean every JPP aerospace product goes directly into those companies. But they show that the manufacturing system has passed qualification standards far above normal commodity metal fabrication. Then AI arrived. This has changed the financial profile of the company very quickly. FY2024 revenue was approximately NT$2.39 billion. FY2025 revenue jumped to about NT$3.73 billion. That is roughly 56% growth. Net income reached approximately NT$618 million. EPS reached NT$12.05. Gross margin stayed around 37.8%. That margin is one of the numbers I find most interesting. JPP did not double its business by becoming a low margin commodity manufacturer. The company expanded rapidly while keeping gross margin in the high 30% range. That suggests the current product mix still carries meaningful engineering and manufacturing value. Q1 2026 continued the trend. Revenue reached approximately NT$1.17 billion. That was about 45% higher year over year. Gross margin remained around 37.5%. So the 2025 acceleration did not immediately reverse once the calendar changed. This is now a real operating ramp. The AI server side has become the main growth engine. JPP manufactures server racks, chassis, power enclosures and increasingly components associated with liquid cooling. That last category matters. AI servers are becoming more difficult to cool. Higher power GPUs produce more heat. More compute density means more thermal load inside each rack. That is pushing the data center industry toward larger cooling distribution systems, manifolds, cold plates and liquid cooling infrastructure. JPP does not manufacture the GPU or the cooling technology itself. It manufactures some of the metal structures and precision components that allow those systems to be installed inside the rack. That places the company several layers beneath the visible AI names. $NVDA and $AMD create demand for increasingly powerful accelerators. Those accelerators require more complex server systems. $DELL and $SMCI integrate servers and racks around those accelerators. $VRT and $ETN operate in the power and cooling infrastructure around the data center. JPP sits further inside the physical manufacturing chain. It produces some of the metal cabinets, chassis, housings and structural components required by this infrastructure. These are ecosystem comparisons. They are not all disclosed customer relationships. The most interesting potential US connection is the company's major cloud customer. Management commentary and Taiwan reporting have repeatedly described a major US cloud service provider as one of JPP's largest AI customers. That customer has widely been reported as Amazon AWS. If correct, that creates an indirect connection to $AMZN. But I would keep the wording disciplined. JPP has not provided enough English primary disclosure for me to treat the identity and exact revenue contribution as completely settled. The important hard fact is that a major US CSP has become a very large customer. Recent commentary has indicated that this customer may account for roughly 30% of revenue during parts of the AI ramp. That is both the opportunity and the risk. A customer that large can transform a small supplier. It can also transform the income statement in the opposite direction if orders slow. Another major relationship is in Thailand. JPP has been expanding production around a large power and server customer widely identified as Delta Electronics Thailand. That customer makes power supplies, thermal systems, data center equipment and related electronics. The geographical relationship matters because both companies operate major production facilities in Thailand. Shorter logistics. Faster delivery. Closer engineering cooperation. Just in time production. Dedicated manufacturing capacity. Those factors can make a supplier harder to replace once a large program is running. But they also deepen customer concentration. JPP is effectively investing ahead of these customers. The company has been adding production capacity in Thailand. One important bottleneck has been painting and surface treatment. JPP is expanding automated paint capacity. It is also investing in larger stamping capacity and dedicated production areas for AI server and power related products. The logic is simple. More AI server racks require more metal structures. More power density requires more sophisticated power housings. Liquid cooling adds additional structural parts. If JPP remains qualified inside those programs, each generation of AI infrastructure can increase the content opportunity per rack. That is the bull side. The risk is that the company adds capacity for demand that later slows. AI infrastructure spending is strong now. It will not grow in a straight line forever. A hyperscaler can change server architecture. An ODM can move a program. A customer can dual source. A competitor can cut price. If one large customer represents 25% to 30% or more of revenue, those decisions matter immediately. That is why I want the exact customer concentration table from the latest annual report. The aerospace business gives JPP some diversification. Before the AI acceleration, aerospace represented a much larger part of the company. That business went through a difficult period around the pandemic and the following aerospace supply chain disruption. It has been recovering. The company has continued obtaining certifications and expanding its European aerospace capabilities. That creates a useful second engine. AI server demand is fast and capital intensive. Aerospace is slower, qualification heavy and built around longer product cycles. The two businesses have different risks. Together they can potentially produce a more balanced manufacturing platform. But right now AI is clearly driving the growth rate. The financial question from here is not whether revenue can grow. It already has. The question is whether the current margins survive the next stage of scale. High 30% gross margins are strong for a precision metal manufacturer. I want to know how much of that comes from: AI server racks Power enclosures Liquid cooling components Aerospace Specialty low volume work New customer programs I also want the operating cash flow behind the reported earnings. Fast manufacturing growth consumes working capital. More orders require more raw material. More capacity requires more equipment. More inventory sits between production and customer delivery. Receivables rise. So a company can report excellent earnings while cash is being absorbed into expansion. That is not automatically bad. But the return on that capital has to remain high. JPP ended 2025 with roughly NT$7.4 billion in assets and around NT$3.7 billion in equity. The balance sheet does not currently look distressed. There is no obvious heavy dilution story. The primary capital allocation issue is expansion. Paint lines. Stamping equipment. Factory capacity. Dedicated customer production. Those investments are being made because demand already exists. Now they need to earn acceptable returns. For US market context, I see several useful layers. $NVDA and $AMD are demand drivers. More accelerator shipments can mean more server racks, more power density and more cooling hardware. $DELL and $SMCI represent the server integration layer. They assemble computing systems around GPUs, networking, storage and power. $VRT and $ETN represent the data center power and thermal infrastructure layer. $ANET sits in the networking layer connecting increasingly large AI clusters. $AMZN is relevant because AWS is widely reported as the major US CSP associated with JPP's AI server business. Again, I would treat that specific customer identity as reported rather than fully disclosed until the primary customer note confirms it. The aerospace familiarity is different. $BA is the obvious US listed aerospace reference. JPP is not primarily a Boeing supplier story. Its known aerospace footprint is more European. But the same qualification logic applies. Aircraft components require traceability, process control and long certification cycles. That experience can strengthen the overall manufacturing discipline of the company even when the fastest growth is coming from AI infrastructure. This is what makes $5284.TW more interesting than a generic sheet metal company. The metal itself is not scarce. The capability stack can be. A customer needs a supplier that can: Meet tolerances. Pass qualification. Build tooling. Handle design changes. Scale capacity. Deliver consistently. Maintain surface quality. Control welding and assembly. Locate production close to the customer. And do it without disrupting a multibillion dollar server or aerospace program. That creates switching friction. It does not create an unbreakable moat. Large customers still have enormous negotiating power. The company remains small relative to the customers it serves. That means the power relationship still favors the customer. The current strengths are clear. 2025 revenue grew about 56%. EPS reached NT$12.05. Gross margin remained near 38%. Q1 2026 revenue grew another 45%. AI server exposure is already producing real revenue. Liquid cooling adds another content opportunity. Thailand capacity is expanding. Aerospace is recovering. The balance sheet is supporting expansion without obvious distressed financing. The risks are also clear. Customer concentration is high. The largest AI programs are project driven. Formal long term volume commitments are not well disclosed. The company is investing heavily into capacity during an AI spending boom. Margins could compress as volume rises. Aerospace recovery could stall. And the current growth rate depends heavily on continued data center capital spending. For me, the next proof is not another monthly revenue record. I want to see: Exact top customer concentration. How much revenue now comes from AI server products. How much comes from liquid cooling. Whether the major CSP relationship is widening into additional products. Whether the large Thai power customer is gaining share of revenue. Utilization of the new painting and stamping capacity. Operating cash flow after expansion capex. Return on invested capital from the Thailand buildout. Aerospace revenue and margin recovery. Whether gross margin can remain above the mid 30% range as the company scales. Real manufacturing. Real AI infrastructure exposure. Real earnings growth. Real high margin execution so far. But also real concentration risk. jpp-KY $5284.TW does not need to invent the next GPU. It needs to remain the qualified company manufacturing the physical structures around the companies that do. If AI racks become larger, hotter and more complex while JPP keeps winning more content per system, the opportunity can grow much faster than the underlying server unit count. The question now is whether that position is durable enough to survive the inevitable cooling of the AI capital spending cycle. That is what I want to understand next. My investing journal, not financial advice.
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Gabe Fletcher (@gabefletcher) reported@marcelocantos @awscloud bro... touch some ******* grass. OF COURSE IT WAS AN ERROR. WHO REALLY THINKS THEY LOOK AT THEIR AWS BILL FOR A TRILLION DOLLARS AND SAYS "OH THATS DEFINITELY REAL" stop. go **** off to some VPS's or some ****.
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Ritesh Roushan (@devXritesh) reportedA good architecture starts by separating document storage, signing, identity verification, and notifications into independent services. 1. API Gateway All requests (upload, sign, download, share) pass through the API Gateway. It handles authentication, rate limiting, request validation, and routing. 2. Document Service Contracts are uploaded directly to object storage (Amazon S3/GCS/Azure Blob). Metadata such as owner, participants, document status, and version history is stored in PostgreSQL. Large files never pass through application servers. 3. Identity Verification Service Before signing, users verify their identity using email OTP, SMS OTP, OAuth, or KYC providers depending on compliance requirements. A verified identity token is issued before allowing signatures. 4. Signing Service Each signature request creates an immutable signing event. Documents are locked while applying a signature to prevent conflicts when multiple users sign simultaneously. Optimistic locking or version numbers help resolve concurrent updates. 5. Audit Log Service Every action upload, view, download, sign, reject, revoke is published to Kafka. Events are stored in an append-only audit database with timestamps, signer identity, IP address, and device information, creating a tamper-resistant audit trail. 6. Notification Service Kafka events trigger email, SMS, and push notifications asynchronously so users are notified instantly without slowing down API responses. 7. Security • Encrypt files at rest (AES-256) • TLS for data in transit • Short-lived signed URLs for downloads • RBAC for document access • Hash every signed document (SHA-256) to detect tampering • Store digital certificates securely using a KMS/HSM 8. Scalability Deploy services independently behind load balancers. Use Redis for caching document metadata and sessions. Object storage handles millions of documents, while Kafka decouples services and absorbs traffic spikes. Read replicas improve download performance, and multi-region replication ensures disaster recovery. This architecture provides secure storage, concurrent signing, legal compliance, high availability, and scales to millions of contracts worldwide.
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✨Neil Blumenthal (@MrKryptonBTC) reported@AWSSupport So you guys wont fix my issue anymore? Ghosting me? 7days gone? Dont say weekend or bla bla. Stop wasting people's time
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Md Jaoyad (@JaoyadCode) reported@awscloud you should fix it otherwise people will become sick after watching the bill!
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Nil (@slowalgorithm) reported@awscloud How are you planning to compensate all your customers who panicked and started deleting resources since the email was legit and there was not a second email notifying of the issue. Your support bot itself claimed the expenses were legit.
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Matthew Joughin | 🏗️ Cross Platform Dev Tools (@mrwcjoughin) reported@jeffdafo @ivanburazin @awscloud Even aspnetcore can run on Linux now - there is no excuse to have (and pay through the nose) for Windows server licenses)
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Kish_lloyd (@kish_lloyd) reported@AWSSupport Why does this feel like a stage for subscriptions hikes on other hosting providers. Previously human error was deemed the highest risk for error but if humans made AI 🤔
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Samrat Singh (Sam) (@isamrats) reported@KahlonGurshaan @Rushike32313211 Yes its down , but no official confirmation posted by @awscloud yet
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Ajith (@iamarulajith) reported@F1 @awscloud Actually surprised to see the good start by Max. I thought he would bog down again but not this time.
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Guilherme Lage (@ItsEasypop) reportedAnother OG goes down. I remember people calling Storj the next Amazon S3 back in 2018
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Jim Osman (@EdgeCGroup) reported@awscloud Real innovation starts with people solving real problems.
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Gabriel (@doktorgphd) reported@awscloud wow really??? i had to search x for the reason?? not even an email?? I saw the email sent yesterday about the cost alert and I spend the last hour trying to work out what is going on because it looks very legit and I only find out it was an error on x! Just had to send an email!!
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Anjishnu Ganguly (@Anjishnu46) reportedI posted again that day because the same issue was blocking our AWS Activate application too. @AWSSupport said it had been passed along again. Another public reply, same unusable account.
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* (@BunnnyRAM18) reported@amazonIN @awscloud The same issue happened twice for these product
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TeeBeeCTO (@TeeBeeCTO) reportedSetting up a new AWS account @awscloud … and get non stop errors on set up. Looks like their vibe coding dystopia worked… were all going to die because SkyNet will have error pages that end up giving us all death by error page. Amazing work… @JeffBezos !!