Amazon Outage Map

Community Discussion

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Amazon Issues Reports

Latest outage, problems and issue reports in social media:

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  Shreyasee Paul (@paul_shreyasee) reported 7 minutes ago

  @AmazonHelp @ajassy it appears that CS team does not wish to help me. I had asked for callback regarding the issue with my order, but your support team is absolutely useless and has provided email assistance which is not what I asked for. Will I get my callback now or am I not clear?

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  Martin Haggerston (@Haggerst1Martin) reported 10 minutes ago

  @jodyalexander81 We've got Amazon- Liverpool about 10 miles down the road, our biggest rivals about to open the chequebook with unlimited money, and your're talking about putting a right-back to left-back. Just about sums the United owners up.

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  wash your dishes (@KoshkaBaluga) reported 10 minutes ago

  @dogshittakes_ Find something off marketplace or whatever the Canadian equivalent is. Amazon furniture with those thin "planks" and generic wood vinyl pattern are all super cheap, terrible Chinese garbage. I have two nightstands and a bookshelf all from different sellers and theyre all probably from the exact same factory.

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  Accidental Martian (@Bz370708245542B) reported 10 minutes ago

  @SGTWipper1Each Buy a plug in interface on Amazon. $ 45 Download software to your phone. Bluetooth. Easy Peasy. Fix it yourself. Grow up.

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  Corey J. Gallon (@CoreyGallon) reported 11 minutes ago

  Prompts are suggestions, not constraints. A model reads a rule as text, not as logic it has to execute. That distinction runs through ". @lizfue's talk "Stop AI Agent Hallucinations: 5 Techniques + Production Patterns", on @aiDotEngineer's YouTube. Elizabeth is a Developer Advocate at AWS, and every technique she covers is a code change rather than a prompt change, demoed side by side on a travel agent built with Strands Agents. - Semantic tool selection. 29 tool schemas go into context on every call, roughly 3000 tokens before your message even starts. Filter with a vector search over a tool database and the model sees only the top three. - Swap tools between turns. In a conversation, tools accumulate in history. Strands lets you clear the tool registry inside the agent loop and add the new ones each invocation. - GraphRAG for questions RAG can't answer. "What is the average guest rating across all hotels in Paris?" gets estimated from three retrieved chunks. A Cypher query against Neo4j computes it across the whole dataset, and returns zero for hotels in Antarctica instead of hedging. - Multi-agent validation. A single agent that gets a tool error will rationalize it into a confident success. Strands' Swarm chains an executor, a validator, and a critic, so the user sees the failure. - Neurosymbolic guardrails. Put the rule in Python, not the prompt. A Strands hook on BeforeToolCallEvent cancels the call when parameters fail, so "max 10 guests per booking" actually holds. - Runtime steering for soft rules. Blocking leaves the user retrying. With agentcontrol, a 50 guest booking gets steered into a split across rooms and the task completes. Rules live on a server and update without redeploying the agent. - Then production. Amazon Bedrock AgentCore gives you gateway-managed tool selection, policies enforcing rules before tools run, steering rules in DynamoDB, memory, and observability. I'm working through the published talks from AI Engineer World's Fair sharing summaries and takeaways. Follow for more!

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  Yajaira Soto (@yayasoto52) reported 15 minutes ago

  @AmazonHelp I already spend 44 minutes in the phone 1st to India who only help was tell me to calm down. And then to the US, thank God for knowing Spanish. My account does not exist under my log in information anymore.

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  arpit agrawal (@arpit17agrawal) reported 15 minutes ago

  @AmazonHelp @amazonIN the glaring issue is app does not have option to either return the product or talk to customer care. Amazon is hell bent on cheating customers by not giving them option to talk to customer care executives. This is crime and must be punished

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  Em8 (@ErikMar10267647) reported 17 minutes ago

  @foxenflask @Jason_Jorjani Bro amazon prime is going to have issues getting there

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  Dallin D. (@SellersCounsel) reported 19 minutes ago

  @Rjudicata @cheri_pimath Let me break it down for your lawyer *** brain Scenario 1 Fake teacher posts a link to an Amazon list You click on said link and it redirects to a site that isn’t Amazon but looks like Amazon and prompts you to sign in You’ve know innocently given your Amazon login to a stranger Scenario 2 Fake teacher posts an Amazon list with items worth $500 in value. Everything comes with a gift receipt. They return all of it for $500 in cash Easy enough for you to understand?

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  Ro86 (@Shrey86ro) reported 23 minutes ago

  @Flipkart @flipkartsupport now I know the reason why Amazon is better than Flipkart! I have ordered a mouse 7 days ago which was not delivered on the date then they called it is not deliverd cause of unexpected error then I have order again and they are saying the same issue😡

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  William Estoque (@westoque) reported 24 minutes ago

  password auth for agents is still broken imo. i'm designing a better way for agents to get access to your passwords and function more securely and still have autonomous behavior. been working and thinking about this a lot and i think this is the best way to go about it. it introduces a few concepts: 1. trusted broker - has access to your password manager: 1password, bitwarden, lastpass, vaultwarden. 2. dedicated browser profiles - isolates credentials and sessions by agent and purpose. 3. trusted injector - a lightweight chrome ext that injects the credentials in the page. the credentials are never shown in plain text to the agent, prompt, chat or tool output. 4. model-enforced policy - definines agent's behavior for a specific product or service, like "view amazon orders only". this is enforced through the model via system prompt. the weakest link in all of this that relies on model strength to prevent manipulation but design tradeoff needed for maximum autonomy. 5. human-in-the-loop approve/deny - whenever an agent wants access, a human will approve/deny using their device and has the ability to remember answer. 6. audits and access logging - we log all access by process to easily see usage and identify bad actors. how do you give password access to your agents?

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  Mayor Craig Scott 🏳️‍🌈 🇨🇦 (@CraigScottNL) reported 24 minutes ago

  @kristinaennis Go on your Amazon app and contact support. I had the same issue and they corrected it right away and credited my credit card.

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  Magz (@cpratheraz) reported 32 minutes ago

  @thatthingido2 You know how to fix that, right? Don't ******* buy from Amazon. Most sellers on Amazon have their own website which is cheaper. Amazon has fees to use their platform for sellers. Do you think the sellers don't pass on that additional cost? Just sayin'

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  Praavin 🇮🇳 (@pravin_looks) reported 33 minutes ago

  @amazon after 5 days of delivery date still My Medicine tablet not delivered,customer care said package lost in transit but still no update, communication, email, no sms this is the service of Amazon ? In emergency I ordered medicine but I face this issue. ID- 404-2248078-4812365

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  Valiant Vibe Coder (@GeorgeGood60669) reported 34 minutes ago

  @TMTLongShort The more I checked what he was saying, the more I found him lying about. The $14k "cost" is retail API pricing, not OpenAI's actual cost. He literally admits "we don't know" the real cost, then later calls the API price the "honest cost". He uses GitHub going down as evidence that AI is making code quality worse, when GitHub itself says a huge part of the pressure on its infrastructure is the explosion in traffic from AI-assisted and agentic coding. He says AWS went down multiple times because of AI coding tools. Amazon explicitly says that's false. One limited incident involved an AI tool, the cause was user error, it wasn't AI-written code, and the supposed second incident didn't happen. He says software at Google, Microsoft, Amazon etc is "uniformly worse", then basically admits straight afterwards that he can't quantify it and is relying on anecdotes. He also claims AI isn't getting meaningfully cheaper or better. Meanwhile the cost of reaching the same capability has been falling around 5-10x a year, and actual capability measurements show progress accelerating in 3 out of 4 metrics studied. Then there's the 70% AI revenue claim, which he talks about like it's a known fact when much of the cross-company number comes from analyst estimates. It's the same thing over and over. Make the strongest possible claim, use a number or example that sounds damning, leave out the bit that changes what it actually means, then move on.