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Google Cloud Outage Map

The map below depicts the most recent cities worldwide where Google Cloud users have reported problems and outages. If you are having an issue with Google Cloud, make sure to submit a report below

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The heatmap above shows where the most recent user-submitted and social media reports are geographically clustered. The density of these reports is depicted by the color scale as shown below.

Google Cloud users affected:

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Google Cloud Platform, offered by Google, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube.

Most Affected Locations

Outage reports and issues in the past 15 days originated from:

Location Reports
São Paulo, SP 1
Township of Evan, KS 1
Catania, Sicily 1
Guayaquil, Guayas 1
Mexico City, CDMX 1
Chhindwāra, MP 1
Los Angeles, CA 1
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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.

Google Cloud Issues Reports

Latest outage, problems and issue reports in social media:

  • ParagBatham
    Parag Dher Sare Paise Wala (@ParagBatham) reported

    @GoogleCloud I need urgent help with a disputed Google Cloud billing charge. I've tried getting through Google Cloud Billing Support, but the automated assistant won't connect me with a human. Please help me get this escalated to a billing specialist. I can provide the details

  • SippiSharma
    Surinder Sharma (@SippiSharma) reported

    We're a small business using Gemini API through @GoogleCloud & received an unexpected charge we haven't been able to verify. Billing support wasn't able to investigate further & we haven't found a way to reach tech support. Help! #GoogleCloudSupport #SmallBusiness @ThomasOrTK

  • der_chuddie
    𝔇𝔢𝔯 ℭ𝔥𝔲𝔡 (@der_chuddie) reported

    Any lawyer on X? I'd like to propose a CAL against @googlecloud @awscloud and @Azure for not enforcing basic outgoing request filtering and wasting everybody resources with the scanning of .***, .env, and wordpress plugins which represents 99% of the bad traffic.

  • Michael_WCD
    Michael Tierney (@Michael_WCD) reported

    @googlecloud Whats the protocol for passing context between agents in a network? Do you just pass the entire current state or some kind of delta?

  • exolete
    Abhinav Pathak (@exolete) reported

    @googlecloud Hi, we have added a new certificate to App Engine for a custom domain, but it has been more than an hour and it has still not been propagated. Is there currently an issue? How long does the propagation take.

  • ScarabOfficial
    Scarab (@ScarabOfficial) reported

    Hey, #Google, You still haven't corrected the poor English in your #GoogleCloud ad'. How many more times do I have to tell you ?

  • swarminged
    swarmsy (@swarminged) reported

    @trythreews @googlecloud This is Google looking at thousands of Web3 projects, vetting them, and deciding which ones deserve the top tier of their support. We are one of them, months into existence.

  • Basirkhan418
    Basir Khan (@Basirkhan418) reported

    @googlecloud The Google Cloud Console onboarding experience feels quite buggy. I’ve tried adding both credit/debit cards and UPI for payment. With the card flow, the payment was deducted and AutoPay was successfully set up for ₹15,000, but the onboarding still doesn’t proceed. I tried the UPI flow as well, but it gets stuck on the QR code page even after the AutoPay setup is completed. If a company at Google Cloud’s scale is facing onboarding issues like this, especially around payments and account setup, how are businesses expected to confidently get started? @AskGoogleCloud please look into this issue and help resolve it. I’ve already been charged/set up for AutoPay multiple times, but the account onboarding is still stuck. I’d appreciate a direct support response and resolution as soon as possible.

  • Woody2233
    Vincent Defarge (@Woody2233) reported

    @rseroter @googlecloud Identity and registration are a strong foundation. The next challenge is operational context: which service and business outcome can the agent affect, who owns it, and how do we observe or stop it? An agent registry becomes far more useful when it carries that context.

  • adelbucetta
    Adel Bucetta (@adelbucetta) reported

    @_lopopolo @googlecloud @OpenAI because the hard part was never writing code, it's automating what used to be human intuition about risk and reward

  • ofPowerofWant
    ofPowerofWant (@ofPowerofWant) reported

    @googlecloud I did collect everything and attempt to do this but @X has joined team "lock you out with something you never asked for" so without a passcode it's not happening Will just have to vent frustrations each time I receive an email until we can't access this at all either

  • jakob_btc
    Jakob (@jakob_btc) reported

    The privacy paradox of the AI era is that utility requires intimacy. To make an AI agent genuinely useful, you have to give it access to proprietary context: internal knowledge, emails, code, workflows. Generic data does not get you very far. So what happens to privacy when hiding the data is no longer realistic? My view is that the privacy stack is shifting from data redaction to verifiable processing. Three major shifts happening right now: 1. Confidential AI at Scale: We’re moving past relying on corporate promises. @googlecloud recently rolled out Confidential G4 VMs with NVIDIA Blackwell GPUs. The tech is mainstreaming. With hardware-based Trusted Execution Environments, your knowledge base is encrypted in memory while the model processes it. Even the cloud provider can’t peek 2. End-to-End Prompt Encryption: Infinite AI memory is a privacy nightmare. The next wave of tools will use localized, cryptographic session gates. Google again recently open-sourced Prompt Encryption SDKs to tackle this problem, establishing a secure channel that keeps data encrypted from the client all the way until it hits the secure chip, before the session vanishes 3. Local Middleware & Edge SLMs: Instead of sending everything blindly to centralized frontier models, enterprises are routing data through local semantic firewalls The bottom line: You will feed AI everything it needs to know, but the tech stack will make sure the vendor never actually "learns" or retains a single byte of it.

  • ajoshi31
    atul joshi (@ajoshi31) reported

    @GoogleCloud @GoogleCloud_IN @googleclod It's disappointing to see a startup application stuck for weeks with no ownership. Since June 12, every follow-up has resulted in the same response: "please wait 2 business days." No ETA. No decision. No accountability. I've already delayed our infrastructure rollout because of this. If there's still no resolution by this week, we'll migrate to other provider. Timeline: • June 12: Application submitted • Multiple follow-ups over 3+ weeks • Repeated "wait 2 business days" • Support apologized for the delays • Call scheduled, but no follow-up afterward

  • paulcdejean
    Paul Dejean (@paulcdejean) reported

    @googlecloud when i load the compute metadata page in my browser it crashes my browser, even though I don't have any metadata saved. Could this be related to "We are experiencing availability issues impacting Google Compute Engine, Google Cloud SQL, and Cloud Filestore globally"

  • Ai_Trend_
    Ai Trend (@Ai_Trend_) reported

    Your agent memorized the training environment, leading to production failures. EnvHarness solves this with a 200-line wrapper and an LLM that designs your curriculum. 🎯 The static trap: Most RL agents overfit to training. New observations or slightly different physics cause catastrophic failure. EnvHarness treats this as an environment bug, not an agent one. 🔧 How it works: EnvRigger, an LLM designer, analyzes your base environment and generates perturbation strategies like noise injection, parameter drift, and scenario mutation. The wrapper applies these dynamically during training. 📈 Results on real benchmarks: We saw a 9.0 point improvement on held-out tasks and nearly 10% faster convergence. These are not synthetic gains; they're on standard agent benchmarks reported in RL papers. 💰 Cost of doing nothing: You're either hand-designing robustness (slow, expensive, incomplete) or accepting brittle agents. EnvHarness is Apache-2.0, plugs into existing stacks, and avoids technical debt and accuracy costs. Stop training agents that fail when it matters. The wrapper ships today. #ReinforcementLearning #AIAgents #GoogleCloud

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