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 (78%)
• Sign in (11%)
• Errors (11%)

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	13 days ago
New York City	Website Down	16 days ago
Ciudad Jardín	Website Down	1 month ago
Kyiv	Sign in	3 months ago
Chennai	Website Down	3 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:

• 
  M (@mdw864) reported 2 minutes ago

  @awscloud can you PLEASE answer me? You’ve just turned off my Business because you will not help me. I need you to stop charging me. Do not tell me to login because I do not know the email address that was used to open the account. All I know is my bank account is being charged

• 
  Ondřej Flídr (@snipercze) reported 8 minutes ago

  Hello @AWSSupport, is there any problem with EBS subsystem in us-east-2 (Ohio region)? Cannot resize volume (ending with internal error, same for console and CloudFormation), new volume is created but stuck in "Attaching" to the EC2. Thanks for check

• 
  S (@cloudsurf3) reported 9 minutes ago

  @awscloud Take down that other tone-deaf tweet, pure mockery of your customers

• 
  Sudeep (@sudee1285) reported 11 minutes ago

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

• 
  Siddartha DevOps (@SiddarthaDevops) reported 12 minutes ago

  @AWSSupport link is not working

• 
  Matthew Joughin | 🏗️ Cross Platform Dev Tools (@mrwcjoughin) reported 13 minutes ago

  @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)

• 
  Keith (@happy_keith) reported 15 minutes ago

  @amazon @awscloud @AmazonUK What does it take to get you to respond to a serious problem DO NOT tell me to go to customers services AI as it is incapable of responding to the issue This is a complete farce !!!!!!

• 
  Aramis Official (@AramisToken) reported 17 minutes ago

  @NoaSanderskyo7 @F1 @awscloud He was slow af, actually

• 
  Omni (@omnishredder_) reported 20 minutes ago

  @AmazonUK @Twitch @awscloud sort yo ****, I'm getting tired of ironically the last two days unable to watch twitch without lag or buffering at random with no explanation, it's almost like the ******* AI training is the problem that nobody wanted! How about ******* remove it!

• 
  Edward Donner (@edwarddonner) reported 21 minutes ago

  @darkosubotica @awscloud @AWSSupport Thanks Darko. I'm keen to be involved. I'm aware there are challenges. A billing bug shouldn't cause a global outage or delete backups. I believe these are solvable. I don't want the possibility of financial ruin from a mistake or hack. Will DM.

• 
  Ashutosh Dubey (@_virusbug_) reported 21 minutes ago

  @AWSSupport I’ve already emailed the AWS Receivables team but haven’t received a reply yet, it’s been 3 days now. The support engineer only advised me to contact them about this issue.

• 
  Amine Zack 🇩🇿 (@AmineZacks) reported 26 minutes ago

  @awscloud Bro fix your servers

• 
  🦋Kieran🦋 💻 (@sir_divs_alot) reported 28 minutes ago

  🚨 @AWSSupport I've been unable to create a Kiro subscription for 2+ weeks, getting error"account is not authorized to make this call." I have an active account, valid billing, and correct IAM Identity Center Organization instance setup. Case #178567212700620 escalate urgently.

• 
  Okko Ojala @okko@mastodon.social (@okko) reported 29 minutes ago

  @edwarddonner @awscloud @AWSSupport Combine a bug like that and spending caps, and the services would have been taken down and caused major losses of services worldwide.

• 
  DeeDee Armstrong (@deedeeafton) reported 33 minutes ago

  @Gozieuk @awscloud You felt they were transparent? I got the anomaly detection email from AWS last night. Dashboard had an outrageous $$ number. Spun up devs to find out problem. And- then AWS posted a joke here on X, and still no email as a follow up to their first one. Doesn’t seem transparent

• 
  ❤️‍🔥ViBe GuY_PrinCe😉 (@777PrinceFreaky) reported 33 minutes ago

  Amazon has very poor service in Warranty and Claim Procedure To Customer fix this for me soon @amazonIN @awscloud @AmazonHelp

• 
  Mahadev Vyavahare (@mahadevkv) reported 34 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

• 
  Himanshu Singh (@hsnice16) reported 36 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.

• 
  Indrani Som (@indrani_som2004) reported 38 minutes ago

  @Anjishnu46 @AWSSupport @AWSSupport look into this issue

• 
  krrawn (@krrawn) reported 39 minutes ago

  I was wondering why @awscloud support was slow the other day

• 
  🔥 PHOENIXX🔥 (@AIPulse0) reported 39 minutes ago

  AMAZON AWS PAYS $127K/MO FOR CLOUD COMPUTING. SERGEY BOUGHT CHEAP SERVER RACK + CLAUDE AI. MAKES $318K Pause at 0:11 — rack with 40+ servers. Every indicator glows green. This is local computing. Zero latency. Zero cloud bills. Sergey, 35, Ukraine. Was AWS architect, $7,200/month. Understands: companies pay Amazon millions, but they can do same calculations locally. Bought used server rack for $4,800. Installed Claude AI for local processing. 78 companies pay $4,077/month each instead of $12K on AWS. Amazon offered $4,200,000. Sergey said: "You profit from dependency. I profit from freedom." Why — in video.

• 
  Luke Skywalker (@LSF4Life1981) reported 40 minutes ago

  @RinoTheBouncer Just like you can't be bothered to Google anything PSN issue was @awscloud which doesn't say anything either

• 
  M (@mdw864) reported 42 minutes ago

  @AWSSupport Five months of broken links & blocked support channels is unacceptable. You have more cut off core business services because you have refused to provide a person with disabilities a way to tell you that you are over billing me. Escalate to a senior rep to fix this before 9am cst

• 
  JJ Ferman (@jjferman) reported 45 minutes ago

  @awscloud the fix: if bill > 1 quadrillion: we have a problem...

• 
  barney (@Southclaws) reported 46 minutes ago

  @jonny_castles @awscloud I am seeing this too, ECR and S3 in eu-west-1, lots of "service unavailable" errors

• 
  TAPE Vector (@Tape_Vector) reported 47 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.

• 
  Joy | 🔥 (@JoyKingdomx) reported 50 minutes ago

  As we all know, cloud outages are not a new topic here. But what is changed is how many products now depend on the same infrastructure. A few years ago, an AWS outage mostly affected AWS customers. Where today one infrastructure issue can ripple across AI apps, APIs, developer tools, streaming platforms and payment services. That is the downside of concentration. We have seen @awscloud outages impact millions. We have also seen @OpenAI outages pause production apps because entire inference pipelines depended on a single provider. It is not the outage that matters - it is the dependency behind it. That is the reason why decentralized compute makes sense. Instead of relying on a single cloud or region, @ionet distributes compute across a global network of GPUs in 138+ countries. No infrastructure is immune to failure, the goal is to ensure one failure does not become everyone's failure.

• 
  Clem ent (@clement___10) reported 50 minutes ago

  Self hosting your email server is something that Is very tricky and I still can't grasp till today. The craziest part is not the setup but managing the email server reputation. I rather pay @Cloudflare or @awscloud.

• 
  Adam Peterson (@_adam_here_) reported 56 minutes ago

  is @AWSSupport down?

• 
  JoeFromSJersey (@JoeFromSJersey) reported 56 minutes ago

  @AWSSupport Good morning folks, I appreciate the help getting things working for me yesterday as I was able to use Kiro! I'm not unable to upgrade from free tier though and get an error that says unable to upgrade. I've a case for that too and was hoping you could also get eyes on that.