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 (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	5 days ago
Pottstown	Website Down	9 days ago
Iztacalco	Website Down	13 days ago
Boca da Mata	Errors	24 days ago
Township of Evan	Website Down	1 month ago
New York City	Website Down	1 month 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:

• 
  Gopal Goti (@gopal_goti) reported 4 minutes ago

  @AWSSupport @AWSSupport Thank you for the update, but 'high volume' cannot justify a support case sitting completely 'Unassigned' for over 4 days for a basic account verification issue. This is not a complex technical issue. it is a backend system error on the AWS verification form.

• 
  Dhananjay (@DhananjayKhark2) reported 4 minutes ago

  @AWSSupport Case open since Aug 13 — 15 days, no fix! AWS Glue blocked with AccessDeniedException (account-level) in ap-south-1. NOT an IAM issue. Needs backend account verification sync. Case: 178661799100381 Please escalate! 🙏 #AWS #AWSGlue @awscloud @AWSCloudIndia

• 
  Mohammed Nafees (@mnafees) reported 6 minutes ago

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

• 
  Lori-Colorado (@lori_colorado) reported 10 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! ”

• 
  Mr Sage (@GreatSage_0x) reported 11 minutes ago

  Custos makes verdicts on AI agent transactions. Problem: it had no memory. Every decision started from zero. Meet Anamnesis — I gave it a memory layer using CockroachDB. Built for the @CockroachDB x @awscloud Hackathon

• 
  ✨Neil Blumenthal (@MrKryptonBTC) reported 14 minutes ago

  @AWSSupport So you guys wont fix my issue anymore? Ghosting me? 7days gone? Dont say weekend or bla bla. Stop wasting people's time

• 
  Haresh Kukkreja (@HandbrakeHarry) reported 16 minutes ago

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

• 
  Nathan Den Herder (@natedenh) reported 17 minutes ago

  @xai @awscloud grok-4.6 on Bedrock us-east-1 is unusable today. 5-token prompt, maxTokens=16: claude-sonnet-4-5 → 3.0s us.xai.grok-4.6 → 150s timeout global.xai.grok-4.6 → 150s timeout Same account, region, creds. No throttle error, no 5xx — it just hangs.

• 
  Rami (@KingRomstar) reported 20 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.

• 
  Jacque Cousteau (@JacqueBenson15) reported 20 minutes ago

  @amazon @awscloud @nvidia Having trouble My account was flagged for suspicious activity. 3 fraud charges on credit card. Rep told me charges would be reversed. He told me to cancel credit card & Amazon account. Now I'm stuck with hundreds of dollars in fraud charges. I'm a senior.

• 
  Dan Lynch (@danlynch) reported 25 minutes ago

  @QuinnyPig @awscloud I need to sign in with LEGO 😎

• 
  Grynn-ai-bot (@Grynn) reported 27 minutes ago

  You can ask codex to make a plan to move your fleet from $AMZN (extremely overpriced) or $ORCL OCI to Hetzner or OVH, Vultr, DO etc. Save a ton. In theory this should hurt Amazon AWS margins. A lot. OTOH, I have been wrong about this for years. People keep paying Amazon when there are lower cost options that are so much better in every way except plausible deniability/CYA - no one gets fired for buying IBM kind of thing. @olesovhcom consider publishing a skill / api with a full list of ovh servers and pricing! Let agents decide what and how to repackage apps on bare metal at 1/5th the Amazon price. And fix your billing, so companies can buy.

• 
  WPBeginner (@wpbeginner) reported 29 minutes ago

  You built your WordPress site over months (or years). One bad plugin/theme update can wipe it all out overnight. 😱 Plugin conflicts. Malware. A botched migration. A hacked server. The disasters that take down WordPress sites usually happen without warning. And here's the mistake most site owners make: they think their hosting provider's backup is enough. It's NOT. If the server fails, you lose both your site and the backup. We share the complete step-by-step guide for backing up your WordPress site the right way. Here is what you will learn: ✅ Use a Backup Plugin (Best for Most People): @DuplicatorWP is what we use across our sites. Full-site backups, disaster recovery links, and restore without having the plugin pre-installed. Free version available, Pro has scheduled backups. ✅ Use Your Hosting Provider's Backup: SiteGround (where WPBeginner is hosted) includes manual and automated daily backups on all plans. Bluehost partners with CodeGuard and Jetpack for their built-in options. ✅ Manual Backup With cPanel or FTP: Use cPanel's Backup Wizard for a full backup, or connect via FileZilla FTP to download your wp-content, themes, plugins, and wp-config.php files directly. ✅ Send Backups to Cloud Storage: Duplicator and UpdraftPlus both connect natively to Google Drive, Dropbox, OneDrive, and Amazon S3. Never store backups on the same server as your website. If your host fails, both are gone. ✅ Set Up Automatic Scheduled Backups: Configure hourly, daily, weekly, or monthly backups in Duplicator based on how often you publish. eCommerce stores and busy blogs need daily. Slower-moving sites can get away with weekly. Ready to protect years of hard work with a proper WordPress backup system? Read the full ultimate step-by-step guide 👇 (Link is in the thread below)

• 
  Webdesign29 Création de sites internet Brest⛓️🕸️ (@Webdesign29B) reported 29 minutes ago

  @AWSSupport I tried every possible combination to get phone support. I think it either just doesn't exist or it is down. Someone did get back to me in chat in another ticket tho.

• 
  Matthew Joughin | 🏗️ Cross Platform Dev Tools (@mrwcjoughin) reported 31 minutes ago

  @ivanburazin Why are you still using windows server ? It’s less than 10 minutes to fire up a @awscloud ECS cluster running free Linux

• 
  TAPE Vector (@Tape_Vector) reported 32 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.

• 
  Milan Jovanović (@mjovanovictech) reported 34 minutes ago

  @mrwcjoughin @awscloud @Azure I doubt this is a compute issue, looks like a bottleneck from past choices coming to bite you

• 
  mark seery (@140ismymax) reported 35 minutes ago

  Peter 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 #AI

• 
  Joy | 🔥 (@JoyKingdomx) reported 37 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.

• 
  krrawn (@krrawn) reported 39 minutes ago

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

• 
  Bob Tong (@bob80924) reported 40 minutes 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

• 
  OneTradeWex (@OneTradeWex) reported 45 minutes ago

  $CBRS is trying to challenge $NVDA indirectly, here’s how: While $NVDA focuses on incredibly small and powerful chips, $CBRS has built a massive, highly specialized AI scaling semiconductor. This greatly decreases the amount of cloud tokens needed to process a large language model, effectively saving AI companies millions of dollars in the long run. Think of $NVDA racks as an industrial kitchen and $CBRS chips as a microwave, when all you need to do is cook a hot pocket you want the microwave for efficiency. $CBRS announced that core revenue more than doubled year-over-year to $210 million in its Q2 earnings report while its cloud business nearly quadrupled. The company also raised its 2026 revenue guidance to between $880 million and $890 million. If $CBRS can successfully fulfill their contracts with @OpenAI and @awscloud on time and at scale we will see even more growth, if not them only having two primary customers will be their down fall. Looking at the technical setup we see $CBRS is coming down into its months long support channel. If it holds the $180-$160 level I see no reason for it not to bounce back to $215 to $230.

• 
  Somers (@jake__somers) reported 46 minutes ago

  AWS keeps charging me 1000x what it should be for inference I try to use the new "generally available" Grok 4.6 Prompt caching doesn't work at all I spend $1.9 worth of inference testing caching I see my AWS bill is now $3400 This was an issue months ago as well. @AWSSupport

• 
  Prateek Gupta (@p_valuee) reported 47 minutes ago

  @AWSSupport My entire production is down since 3 days, I believe this is a P1 and should be treated like one @AWSSupport. Please help me with an ETA

• 
  Jaimin Vaghani (@jaiminvaghani) reported 48 minutes ago

  @AWSSupport 5+ days, Case 178738643800497. Production down, customers impacted. Same scripted answer daily: no ETA, no updates, just "check back in a couple of hours." This needs real escalation. Please have someone with authority look at this.

• 
  Jaimin Vaghani (@jaiminvaghani) reported 50 minutes ago

  @AWSSupport 5+ days, Case 178738643800497. Production down, customers impacted. Same scripted answer daily: no ETA, no updates, just "check back in a couple of hours." This needs real escalation. Please have someone with authority look at this.

• 
  Mahadev Vyavahare (@mahadevkv) reported 52 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

• 
  mail box (@mailbox28564784) reported 54 minutes ago

  @amazonIN @amazon @awscloud But in my personal experience, this response has never led to a real solution. They keep asking for the same details again and again, yet my issue remains unresolved. My ₹1,400 refund is still pending, and I have neither received a replacement nor-2

• 
  Rohit Dhawan (@rohitdhawan26) reported 55 minutes ago

  @AWSSupport @awscloud I send a DM on 17th july with same issue but no one responded to that.

• 
  ゆーー𓂀🦊京のそちこち(暑いので液化した🫠) (@Hikari_644) reported 59 minutes ago

  @ishanxtwt Simply DNS server problem never take down an entire website. Except, like amazon AWS, are using domain and dynamic name resolve to working correctly between multiple servers and services.