Amazon Web Services status: access issues and outage reports

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.

Most Reported Problems

The following are the most recent problems reported by Amazon Web Services users through our website.

• Website Down (82%)
• Sign in (9%)
• Errors (9%)

Live Outage Map

The most recent Amazon Web Services outage reports came from the following cities:

City	Problem Type	Report Time
Township of Evan	Website Down	5 days ago
New York City	Website Down	8 days ago
Ciudad Jardín	Website Down	1 month ago
Kyiv	Sign in	2 months ago
Chennai	Website Down	2 months ago
Point Pleasant Beach	Website Down	3 months ago

Full Outage Map

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:

• 
  Keith Townsend (@CTOAdvisor) reported 3 minutes ago

  I spent over $120 in @awscloud so far this month. Most of it has been on GPU instances and Xeon 6. This is the most I've spent since I've had a long-running VM as a web app server a few years ago.

• 
  Matthew (@OneShotCaller) reported 3 minutes ago

  @CalebChamberla6 It’s an AWS billing error (see @awscloud)

• 
  hansi flick enjoyer (@sambarvadaii) reported 8 minutes ago

  @santhoshv @AWSSupport @awscloud I had an s3 bucket with some data in worth 2-3 mb at max. At first I thought someone hacked into my account. I raised a billing inquiry, after which I realised that this was an ongoing issue.

• 
  Ignacio Cassinelli (@igncass) reported 9 minutes ago

  @awscloud What a terrible response

• 
  Mahadev Vyavahare (@mahadevkv) reported 9 minutes ago

  @SarvamAI should learn from American companies on how to and what to document on internet Documentation and visibility is broken compared on sarvam website. Learn from @OpenAI and @awscloud

• 
  Jack Stone (@c0XhHxvylL) reported 13 minutes ago

  @AWSSupport be honest, how much of this problem was due to ai and/or vibecoding

• 
  Armando J. Perez-Carreno (@perezcarreno) reported 19 minutes ago

  @ngriffin_uk @awscloud The problem wasn’t only the billing page. Many people received billing usage alerts with tremendous spend. In our case, it was additionally frustrating because we couldn’t log in due to an MFA bug while we were about to board a ten hour flight. Some of us do care.

• 
  Jonny Castles (@jonny_castles) reported 20 minutes ago

  Not seeing much on here, but seems like a massive outage across platforms? Looks like all AWS linked? @awscloud

• 
  kyun anon (Gobhi ka fool ) (@anondis1122) reported 20 minutes ago

  @AWSSupport @ashu_sharma17 Yeah. Why tf not send an email.. that there is an issue. I have a medical condition. It put my life in danger

• 
  Corey Quinn (@QuinnyPig) reported 22 minutes ago

  Kinda funny that nobody's even making observations like this about @awscloud, if you want to go a level deeper down the irrelevance well.

• 
  Gerzson (@Gerzsononline) reported 22 minutes ago

  @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

• 
  Har (@duckboy1909) reported 23 minutes ago

  @awscloud fix your Alexa servers and fix your Bluetooth on app and devices! #alexadown #alexa #amazon

• 
  Mr. Honkitude (@Mr_Honkitude) reported 25 minutes ago

  @St0ner1995 @AWSSupport When you owe someone $10k, you have a serious problem. When you owe someone $110 billion, they are the one with a serious problem.

• 
  banhchung (@banhchugxanh) reported 26 minutes ago

  @POTATOCHEAPGAM1 @trythreews @awscloud i'm so down for cloud gaming, but 5gb internet feels like a stretch

• 
  paige s. (@PaigeSully88) reported 34 minutes ago

  @awscloud Your AI sucks and costs more than humans. This sure is not a human error

• 
  Nilesh (@nile3h) reported 35 minutes ago

  Reached out to @awscloud team yesterday related to billing issues wrt AWS partners, no replies Can anyone help?

• 
  Anjishnu Ganguly (@Anjishnu46) reported 36 minutes ago

  Hey @AWSSupport, Our Case 178452910500907 is still not resolved, and we've been left waiting without any meaningful update. Because of this, we're also unable to apply for AWS Activate, which is directly impacting our business operations and slowing down our workflow. This delay is becoming unacceptable. Please look into this urgently and help resolve it as soon as possible.

• 
  GettingMyGlitchOff (@GettingMyGlitch) reported 36 minutes ago

  @AWSSupport Again there is a mass wave of suspensions like in May, I'm assuming in error as I've been on this platform for over 10 years and this seems to be happening more frequently. Emails from mturk-noreply havent worked in a long time so any updates on this situation?

• 
  Ritesh Roushan (@devXritesh) reported 37 minutes ago

  A 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.

• 
  Matthew Feinberg (@thewebbie) reported 38 minutes ago

  @infoscav @awscloud 28 Billion! AWS has acknowledged there is a problem with the billing console.

• 
  Sudeep (@sudee1285) reported 39 minutes ago

  I need assistance to access existing APN account...it's getting error.. please help me. @awscloud

• 
  GettingMyGlitchOff (@GettingMyGlitch) reported 42 minutes ago

  @AWSSupport Yeah its just getting automated responses to everyone saying "Your account will not be re-opened. We regret that we have not been able to address your concerns to your satisfaction." so can you send the mturk team a message to review the error since its more then just me its

• 
  Toastie (@hightoastie) reported 45 minutes ago

  @marcelocantos @awscloud How would forfieting a chess tournament fix the problem though?

• 
  kakafa.btc (@kakafa_btc) reported 47 minutes ago

  @AWSSupport Still NO resolution after 7 days! Case ID: 17849863000462 Account hold cleared days ago, but CloudFront is STILL locked due to a backend flag sync issue. @AWSSupport keeps passing the buck. Assign a supervisor to clear this flag NOW! @awscloud #AWS #CloudFront #AWSCloud

• 
  TAPE Vector (@Tape_Vector) reported 49 minutes ago

  JPP-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.

• 
  Kish_lloyd (@kish_lloyd) reported 52 minutes ago

  @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 🤔

• 
  Certified AI Dev (@MisterPrashant) reported 55 minutes ago

  This 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.

• 
  Nil (@slowalgorithm) reported 56 minutes ago

  @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.

• 
  Gabe Fletcher (@gabefletcher) reported 58 minutes ago

  @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 ****.

• 
  Indrani Som (@indrani_som2004) reported 60 minutes ago

  @Anjishnu46 @AWSSupport @AWSSupport look into this issue