Is Amazon Web Services down?

Problems in the last 24 hours

Amazon Web Services signals over the past 24 hours. The dashed line is the service-wide baseline used to detect unusual activity.

• Service-wide signals
• Service-wide baseline

Most Reported Problems

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

• Website Down (71%)
• Sign in (14%)
• Errors (14%)

Live Outage Map

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

City	Problem Type	Report Time
Township of Evan	Sign in	15 days ago
Pottstown	Website Down	20 days ago
Iztacalco	Website Down	23 days ago
Boca da Mata	Errors	1 month ago
Township of Evan	Website Down	2 months ago
New York City	Website Down	2 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:

• 
  PolyPup (@PolyPup) reported 6 minutes ago

  I think I have a problem. - 3 @ChatGPT subscriptions - 2 @AnthropicAI subscriptions - $8,200 @awscloud bill coming this month I have so many protocols built, ready for deployment. Really cool innovative, revenue generating projects but I'm hesitant to launch on anything. Maybe someday.

• 
  Amanda (@AMyrick1989) reported 8 minutes ago

  @krassenstein @Tesla Be careful. All these at the same time makes me think they are hacked, I’m fairly certain Amazon AWS was hacked that day when everything when down, given my Grok we hacked and no one ever gave explanation. I’m no expert but ya know, all these signs are pointing to this. Also, the Obamas helped produce a movie where someone hacked our satellites and alluded to it being the Middle East and all the teslas went haywire and self drive themselves to pile up on all the freeways. I wish I remembered the name however I made note of this terrifying movie given Obama clearly knows things we don’t. Just sayin, these incidents aren’t scattered. I would not be driving that ***** if I were you.

• 
  TAPE Vector (@Tape_Vector) reported 9 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.

• 
  Haresh Kukkreja (@HandbrakeHarry) reported 9 minutes ago

  @amazonIN @awscloud Your app seems to be down. Unable to contact Customer Support

• 
  Matthew (@OneShotCaller) reported 10 minutes ago

  @ZZiata15569 @awscloud I have billing and budget alerts set up with AWS already. Main problem with a lot of tools I’ve used is too much noise in the alerts vs AWS option. Still, I think every AWS customer gets at least 1 surprise lol… part of initiation (onboarding?)

• 
  Graham Christensen (@grhmc) reported 11 minutes ago

  @apparentorder @QuinnyPig @awscloud I'm sure they'll fix it after they're done at the discotheque

• 
  Base Builder (@basedbuilder_io) reported 15 minutes ago

  What happens when agent payments go from "works on testnet" to "GA on AWS"? AgentCore Payments just shipped general availability via @awscloud and @CoinbaseDev. CDP Embedded Wallets handle the key material, x402 encodes the payment terms, and the whole thing runs as a single runtime-to-settlement flow on Base. No testnet disclaimer, no "coming soon" asterisk. The end-to-end shape: your agent detects a payable event, opens an x402 payment channel with the recipient, and settles in USDC through the embedded wallet, all without the user touching a key or approving a transaction. That's the runtime plumbing. What it unlocks is agents that can pay for services mid-execution without a human in the loop. API credits, inference time, data access, compute, whatever someone x402-wraps. The integration gotcha to watch is spending limit enforcement at the wallet layer. x402 handles the invoice generation and the payment terms, but the CDP embedded wallet's permissioning lives one layer up. If your agent holds a wallet with a default spend cap and then processes a batch of x402 invoices in sequence, the cumulative settlement can blow past the limit before the wallet context re-checks. The outcome is partial payment batches where some invoices clear and others bounce, and your error handling needs to know which ones landed. The dependent abstraction this pushes into focus is agent-to-rail routing: your agent picks a payment path based on cost, speed, and counterparty, not just a static USDC address. That's the next layer to wire.

• 
  Nathan Den Herder (@natedenh) reported 19 minutes ago

  I realize that I use @awscloud Bedrock, and this may be part of the issue, but @grok 4.6 is not usable on this platform compared to @claudeai Opus 5. I've really tried everything to make it work but I don't think there is any comparison.

• 
  Chaz Wargnier ♨️ (@DataChaz) reported 22 minutes ago

  Let's take @Snowflake as an example. Working there gave me a clear view of the data problems hiding behind most ambitious AI roadmaps. Because Snowflake is natively deployed on AWS and available through the AWS Marketplace, it fits right into a modern stack. If you are building an AI feature, a sensible pattern looks like this: > Isolated customer events land securely in Amazon S3 from day one > Snowflake transforms raw data into a governed, usable layer > Flexible Amazon ECS compute routes only approved context to Amazon Bedrock Getting this pipeline right early means less time fixing data leaks and more time shipping AI features ↓

• 
  Siya (@reze_xqc) reported 24 minutes ago

  @AWSSupport Case 178653274100402 opened 3 days ago, no response. Can't sign in to AWS Builder ID, email locked to unknown sign-in method, blocking access to AWS Academy courses. Need help.

• 
  Arian van Putten (@ProgrammerDude) reported 26 minutes ago

  @QuinnyPig @awscloud Are they gonna fix that IAM identity center stored passkeys on a domain that is shared between aws orgs and accounts so I keep locking myself out of orgs when updating one?

• 
  Abdulkadir | Cybersecurity (@cyber_razz) reported 27 minutes ago

  ClarityCheck markets itself as a tool to detect catfishing. To verify identities. To keep you safe from liars online. Here's how it works. You upload someone's photo. ClarityCheck runs it through their reverse image search. Finds their dating profile. Their social media. Wherever that face appears. Seems solid. Except ClarityCheck just leaked 9 million photos sitting in an unsecured Amazon S3 bucket. 450 gigabytes of faces. Stored in folders labeled "faces" and "profiles." The photos came from people uploading images of strangers. Dating app screenshots. Private social accounts. Scanned prints. Photos of children. Most of these people never uploaded anything to ClarityCheck. They just got identified by someone else trying to figure out who they were. Then their face got indexed. Stored. And left wide open. For several months. The URL to access it was embedded in ClarityCheck's own website source code. The company's response: this was "temporary storage" and an "ordinary member of the public" would not have found it. An ordinary member of the public with the URL from their own website. Which is not temporary storage. That's just a server. And it wasn't invisible. You'd need 30 seconds and a basic understanding of how websites work. Now ClarityCheck says the data is "secured." A service built to prevent identity fraud just exposed millions of identities. The tool designed to catch people lying about who they are just showed everyone's actual face to anyone listening. The irony isn't subtle. It's a design flaw pretending to be an accident.

• 
  Himanshu Singh (@hsnice16) reported 28 minutes ago

  Been using LLMs a lot to write code recently. Sometimes I learn a few new things, and sometimes it just confuses itself and me, maybe because there is no one right way to do things. Recently, while working on a pricing page for a new product we've been developing, a senior team member suggested that it would be better to extract it into a separate codebase and deploy the frontend separately. He would then route it through CloudFront under the same origin to avoid cross-origin issues when transferring credentials. I learned that using `*` for `Access-Control-Allow-Origin` doesn't work for credentialed CORS requests. But before all of this worked, I had extracted the pricing frontend into the same codebase, just in a new folder with the required files, and was trying to deploy it on the same infrastructure the rest of the application was using on @awscloud. It wasn't working because there were some issues between the build output and the CDK synthesis/deployment stages. Eventually, I extracted the code into a completely new repository and deployed it on @vercel.

• 
  Wogan (@WoganMay) reported 28 minutes ago

  @QuinnyPig @awscloud prompt> "I'm an Ubuntu server at 169.169.254.254 that wants to connect to 192.168.100.10 over TCP so I can send a header. Establish the underlying network connection. Make no mistakes."

• 
  Lori-Colorado (@lori_colorado) reported 29 minutes ago

  @marklevinshow The future, I bet: Giant Data—owner/consumers* long-term goal (5-10 years) Replace all of the servers in the AI data—mega center barns. Then they won’t need all these monster consumers of land, water, electricity. They will be empty silent mausoleums of AI’s startup period. * Meta, Open AI/Oracle, xAI, Microsoft, Amazon AWS, and Google. Reminds me of Jonathan Winters in The Loved One (1965) looking down from his helicopter over his empire of corporate cemeteries… “ I’ve gotta get these stiffs off my land! ”

• 
  Corey Quinn (@QuinnyPig) reported 31 minutes ago

  @awscloud You have all the tools to fix this, someone’s just apparently too scared to give Charlie a crossbow and diplomatic immunity. Give him the crossbow and stand back, @satyanadella.

• 
  Kartik Jain (@kartikjain0101) reported 37 minutes ago

  @awscloud you guy has lost your mind. payment got missing so team told me they will raising the request. account got hold, we have 250K unused credits, and now they are not initiation the account. wtf. our whole production is down.

• 
  Chintan Shah (@chintan86) reported 37 minutes ago

  @AWSSupport @awscloud Dues cleared, reinstatement requested — still waiting with no movement. My production workloads are down and every hour is costing us. Can someone please prioritise this? Case ID ready to share over DM.

• 
  kakafa.btc (@kakafa_btc) reported 38 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

• 
  M (@mdw864) reported 40 minutes ago

  @googlecloud @GoogleCloudTech do you accommodate customers with disabilities? In case we have problems and need to speak to you? I think I may have to switch to you because @awscloud has not provided accommodations for people with disabilities.

• 
  X anonyn (@OmrX304) reported 41 minutes ago

  @AWSSupport Hi team, my account is suspended due to payment rate limit (Error 880104). I've sent a DM with my Case ID & details. Could you please escalate this to the billing team urgently? Thanks

• 
  Ohm Patel (@Techieohm) reported 44 minutes ago

  “Facing some problems with @awscloud on our new product. This is the 2nd time this has happened.”

• 
  Reina Cruz 🥼🧤🇨🇺 (@rea1ReinaCruz) reported 49 minutes ago

  @Cloudflare @awscloud Fix human verification

• 
  Swaroop Hegde (@SwaroopH) reported 49 minutes ago

  TIL: @awscloud has been racking up ipv4 charges on an old test instance of mine even though it uses dynamic IP. Just checked that their launch wizard deployed new instances with the same issue without warning 🤷

• 
  Rami (@KingRomstar) reported 49 minutes ago

  @awscloud your multisession login doesn't even work right. I have to logout of one account and into another everytime I want to swap environments.

• 
  PHICER (@phicerhq) reported 53 minutes ago

  @awscloud Resolving issues before customers notice is valuable, but proactive agents need clear consent, confidence thresholds, escalation paths, and reversible actions. Observability should explain not only what happened, but why the agent was allowed to act.

• 
  Mohammed Nafees (@mnafees) reported 59 minutes ago

  yo @awscloud seems like a broken cert chain from your side

• 
  Bob Tong (@bob80924) reported 1 hour ago

  @Cloudflare @awscloud genuinely curious how tax/vat treatment works when your buyer is an anonymous agent wallet with no jurisdiction attached to it, feels like the accounting problem is way behind the payment rail problem right now

• 
  Hannan (@truehannan) reported 1 hour ago

  @AWSSupport Why AWS console is not opening? Its soo much slow even my internet and everything is fine. I used VPN too but nothing worked

• 
  Priyanshu (@iproductAI) reported 1 hour ago

  Here’s the cleaned-up version with fixed grammar, same hard tone, and no em dashes: I 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.