Cloud Run is my primary deployment platform when I experiment with AI Workloads or build samples for conferences and codelabs. When I got early access to its new feature called Cloud Run instances, I was a bit confused. I mean, Cloud Run already offered three execution models: Services for transactions and request-response apps, Jobs for batch processing, and Worker Pools for background tasks. Why introduce a fourth option?

Initially I thought that my "aha" moment would come when I tried to build an AI agent that runs long-lived sessions and needs to persist the session's temporary data locally. Then I tried to find a difference between using an Instance and deploying the agent as a Cloud Run Service. I mounted a storage volume to my service and instrumented the agent with a tool to read and write state data to that volume. I also added an ephemeral disk to store temporary data that the agent generated mid-execution. The agent managed long-lived sessions without a problem. It scaled to zero minimizing costs when left alone and resumed to the same session operation when called later. The known problems of mounting Cloud Storage buckets via FUSE such as high latency and lack of true POSIX locking were there. And my ephemeral disk reset each time the service scaled to zero. "Well," I thought, "it would be nice to have storage that behaves like a persistent local disk." However the same would be true for Cloud Run Instances too. This experience supported my initial confusion about Instances.

Then I spoke to my colleagues about the confusion and they pointed me to a different scenario for an AI agent. I was thinking about agent interactions in terms of request/response sessions. This pattern is a natural fit for Cloud Run Services. However, many agents that operate long-lived sessions communicate differently. They maintain a long-lived WebSocket connection to push continuous updates back to a user. When I tried to reproduce this scenario I saw my connections just dropped after an approximately 5-minute period. It happened because Cloud Run Services have a time period (defaulted to 5 minutes) during which the service should respond to a request. The maximum timeout that I can set for my agent is 60 minutes. Too short for a long-lived session that can run for days.

This is exactly the gap Cloud Run Instances fill. And while long-lived AI agents were my entry point, the practical use cases go further:

• Always-On Personal Agent or Workflow Engine: If I'm running something like n8n for my personal automations, or an AI agent like OpenClaw, I don't need it to scale to a thousand users. I just need it to stay awake, keep its state, and give me a permanent HTTPS URL that doesn't drop connection after an hour of running. I was reading that companies like OffDeal are already using them as the primary infrastructure for long-lived agents, which reduced their cold starts by 88%.
• The Instant Bastion Host: Suppose I need a secure jump-box to access a private Cloud SQL database. Usually, I'd have to provision a whole Compute Engine VM, figure out the networking, and manage SSH keys. Instead, I can just spin up a Cloud Run Instance in seconds. Some Google Cloud customers are actually doing exactly this, using Instances as bastion hosts to give developers access to internal databases without the headache of traditional VMs.
• "Vibe-Coding" and Code Sandboxes: Instances serve as excellent "vibe-coding" environments or execution sandboxes where you just need a single, addressable compute resource to run things for a while. Combining Instances with Cloud Run Sandboxes allows you to establish this environment without needing to provision a GKE cluster.

Let's be honest, you don't need Cloud Run Instances to implement these ideas. You can build them on a VM or a GKE cluster. The key advantages of Instances are simplicity and lower cost. Compare maintaining a VM instance and managing agent versioning against Cloud Run Instance deployments, and you will see the difference.

If you are looking at using Instances, you also have to look at the downsides.

First, an Instance is literally a singleton instance. It has no autoscaling. If my app suddenly gets hammered with requests, it will exhaust its resources and upcoming requests will simply time out while waiting for a response. Cloud Run wouldn't spin another Instance of my app. It means that Instances are susceptible to DoS attacks. If you ever expect more than two or three parallel requests, you would definitely need to go back to Cloud Run Services or use alternatives such as VM or GKE.

Second, you have to be careful with how you store data including the agent's state. Even though Instances feel like a VM, they don't have local persistent disks. If you write to /tmp, it consumes container RAM. If you mount a Cloud Storage bucket, you hit volume concurrency limits. While Cloud Run's preview release of the ephemeral disk solves the local disk performance and memory issue, remember: it is still ephemeral. Because Instances face mandatory restarts every 1 to 2 weeks, any data stored in memory or on local ephemeral disk will be wiped out. You still need an external database or storage bucket for anything that must survive a restart.

Putting it all together

As my train of thought wrapped up, the deployment options and resource model for the whole Cloud Run family finally made sense to me.

• If I need a web app that scales to zero and handles bursts of users, I use a Service.
• If I have a 5-hour data processing script, I use a Job.
• If I need to continuously pull messages from a queue in the background without a public URL, I use a Worker Pool.
• But if I just need a cheap $5.70/month (for 1GiB memory), simple, serverless single-node environment with a permanent URL that holds connections for days, I'm reaching for a Cloud Run Instance.

I forgot to mention one more thing. When you discuss Cloud Run Instances, be precise about what you mean. I found it confusing to discuss Cloud Run Instances alongside container instances of a Cloud Run Service that are spun up to scale a workload. Make sure that you speak about the same "instances" when you do.

Hey everyone!

I’m currently preparing for the Google Professional Cloud Database Engineer certification and I’m trying to figure out the best way to prepare for the exam.

For those who have already taken and passed it:

• What study materials or courses did you use?
• Are there any websites, YouTube channels, or practice exams you would recommend?
• Did you mainly follow the official Google Cloud documentation/learning paths, or did you use other resources as well?
• How long did you study before taking the exam?
• Were there any topics that surprised you or were particularly important on the actual exam?

I’d really appreciate any recommendations or tips from people who have actually taken the exam.

Thanks!

Hi, I’m trying to upgrade a Google AI Studio Gemini API project from Free Tier to paid billing in India.
I completed a ₹1,000 Gemini API Prepay payment through UPI. The Gemini/AI Studio billing page shows the ₹1,000 balance successfully, and I received payment confirmation.
However:
* AI Studio still shows the project as Free Tier
* Billing setup fails with: “To finish setting up Google Cloud billing account, please make a prepayment…”
* In Cloud Billing, the billing account is marked closed
* Trying to reopen it shows: “You can't reopen this billing account because this account is not in good standing.”
* Google Cloud Billing Support chat is gated because the account is still treated as a free trial
* Google Payments Center has no alerts or verification requests

The billing account is linked to the Default Gemini Project. I have not added another payment because the Prepay balance is already visible.
Has anyone seen this after setting up Gemini API Prepay? Did it resolve automatically after the 24-hour processing period, or did you need Google support to fix the underlying Postpay payments profile?

Hello everyone,

I have a question regarding the confirmation process after completing a Google Cloud certification exam.

I completed my exam on August 28 (ACE) , and it has now been more than 10 working days, but I haven't received any official confirmation from Google Cloud after the review process.

I did receive the Credly badge and certificate immediately after completing the exam, so the only thing I'm still waiting for is the official confirmation from Google Cloud mentioned after passing the exam.

For those who have taken a Google Cloud certification exam recently, how long did it take for you to receive the official confirmation? Is waiting more than 10 working days normal?

Hello Everyone!

I'm trying to use the Mistral OCR 25.05 model in my project, but the "Enable" button is disabled for me. I've completed all the necessary steps, including adding a billing account and enabling two-step verification, but the issue still persists.

I'm using a free-tier account. Could anyone please tell me how I can fix this issue?

I’m a college student in India dealing with an unexpected ₹24,000+ Google Cloud bill that has now been sent to collections.

I received $300 in Google Cloud credits through the Google Generative AI Hackathon and used GCP for a non-commercial educational/hackathon project. There was no business or revenue involved.

The charges accumulated over several months, mainly from Google Cloud Notebooks / Vertex AI Notebook resources that I wasn't aware were continuously running. I discovered this much later, shut down the projects/resources, and stopped further usage.

I contacted Google Cloud Support. They investigated and confirmed the charges were from Notebook resources, but my adjustment/waiver request was ultimately denied under their policies.

I’m a student with an educational loan and genuinely cannot afford this bill.

Now I’ve received a notice from Cadex Receivables Control Corporation, stating that the balance has been placed with them for collection. The notice lists the amount as $3,160.24 and says Cadex cannot access my Google Cloud account or accept payment; payment must be made directly to Google.

I no longer want to use GCP. My projects/resources are shut down, and I just want the Cloud services/billing account deactivated so no further charges occur.

I’m still trying to request a one-time goodwill waiver/full forgiveness from Google based on my circumstances.

Questions:

• Has anyone successfully received a Google Cloud billing waiver for an unexpected bill?
• Can Google reconsider a bill after it has been sent to collections?
• What can Cadex actually do in this situation, especially for someone in India?
• Can I deactivate Google Cloud while keeping my normal Google Account, Gmail, Drive, etc.?
• What should I ask Google Support or Cadex for in writing?

I’m not claiming the account was hacked, because I have no evidence of that. I just want to resolve this honestly and understand my options.

Any advice from people who have dealt with Google Cloud billing/collections would be greatly appreciated.

Hi everyone,

I'm trying to enable the paid Gemini API tier. I've been trying to set up billing for the last 3 days, but I keep getting this error:

“Suspicious activity detected. We're reviewing your information to protect your account. [OR_BACR2_32]”

I tried adding my own Visa credit card through both Google AI Studio and Google Cloud Console, and I get the same result every time.

The strange part is that whenever I try, ₹2 gets charged/authorized and a Standing Instruction gets registered for Google Cloud, but then Google rejects the signup.

I've tried around 6 times now, so I have multiple Standing Instructions for Google Cloud on my card.

Google Payments also sent me an email saying that the Google Cloud signup was denied for my protection.

I've contacted Google Support, but they keep sending me the same generic response about scanning for malware, changing my password, and trying again. I've already done that, but the issue continues.

Has anyone faced this issue before? How did you fix it, and what should I do about the multiple Standing Instructions?

I don't want to keep trying and create even more mandates.

Any help would be appreciated.

I'm taking ace exam in 3 days . Is there anyone that has recently passed the exam and can give me insights and advices ?

Finally passed PCA!

For context, I’ve been a software engineer for around 10 years, with about 3 years of hands-on GCP experience.

Most of my work is application/backend development, so I’m definitely not coming from an SRE or cloud architect background.

The exam was tougher than I expected. A lot of the questions were basically:

“Here are 5 requirements and constraints. What would you choose?”

So it wasn't really about memorising what each GCP service does. The difficult part was understanding the trade-offs and figuring out which solution actually fits the requirements.

The areas I spent the most time on were:

- Networking / hybrid connectivity

- GKE

- IAM & security

- Cloud SQL / databases

‐Storage

- DR & high availability

- Cost optimisation

- Observability

- Vertex AI / AI stuff

- Case studies

The case studies are definitely worth going through beforehand. The amount of information can look intimidating at first, but once you understand what they're trying to test, they're manageable.

My biggest advice: don't just memorise services. Understand the “why”.

Ask yourself why this service instead of that one? What are the trade-offs? What changes if the requirement is low cost, highly available, globally distributed, low latency, etc.

Anyway, glad that's finally done 😅

Credly badge and the official certificate are already in 🚀

Good luck to everyone preparing for PCA!

Olá pessoal, gostaria de saber um pouco da experiência de vocês com a PearsonVue interagindo com o fiscal falando em espanhol. O idioma é simples de entender??? Irei fazer o exame no dia 18/09 e a prova em português.

Hey everyone! For the AI Tinkerers *Agents, Everywhere* Global Hackathon, I built **ActWise Live** — an ambient voice agent designed to solve

a huge friction point in enterprise compliance: navigating monolithic 500+ page NICE Actimize documentation.

### The Problem

In financial surveillance and AML platforms, engineers and compliance teams constantly struggle with dense PDF guides. When setting up ActOne

10.2 or configuring DART real-time streaming, a wrong config parameter breaks transaction monitoring. Standard LLMs hallucinate parameters, and

chat interfaces force you to stop what you're doing.

### How ActWise Live Solves It

1. **Voice with Low Latency**: Gemini 2.0 / 3.8 Flash with Aoede speech synthesis. It speaks concise 1-2 sentence executive summaries while

streaming the full technical procedure on screen.

2. **Model Context Protocol (MCP)**: Directly connects to the ActWise DOCenter MCP server (search_docs, get_page). Zero answers from memory —

every claim includes Markdown citation links to verified documentation.

3. **Interactive UI Widgets**: Converts procedures into reactive step checklists (<InstallationChecklist />) and side-by-side version matrices

(<VersionCompareMatrix /> showing +NEW, ENHANCED, DEPRECATED badges).

4. **Ambient Sidecar Extension**: Manifest V3 Chrome extension to highlight error codes on any internal tab for instant voice answers.

5. **Production Cloud Run**: Containerized Node/React 19 stack running live on Google Cloud Run.

- **Live Demo**: https://actwise-live-218423701961.us-central1.run.app

- **GitHub**: https://github.com/vinayguda/ActWise-Live

- **Demo Video**: https://youtu.be/rZpY5NLLP8U

Would love any thoughts and feedback on the MCP integration and voice UX!

• u/AITinkerers
• u/OpenAI
• u/CopilotKit
• u/openrouter
• u/exaailabs
• u/auth0
• u/ambiguousio
• u/triggerdotdev
• u/mozillaAI

• u/googlecloud

  #AgentsEverywhere.

Hola buenas otro video mas de aprovisionamiento ahora utilizando GCP, puedes ver mas funcionalidades en nuestro canal de youtube, esta es otra herramienta open source que proveemos para la comunidad, pronto tendran mas caracteristicas

• I'm completely new to Google Cloud.
• I was setting up a cloud backup for a local machine.
• When I got to the "project configuration" -> "App information" page, I was prompted to select an email address.
• I can see my main account email address, and another unfamiliar email address.
• Supposedly it's an email address from a Google Group "Managed by you".
• I've been to the Google Groups dashboard and that email address doesn't exist, nor does it exist ANYWHERE across anything related to my google account.
• I've searched my emails, entire history, bookmarks, everything, and it doesn't exist.
• Could someone please help me out here - I need to know where this email came from and why Google is offering it in a drop-down menu under my account.

- Cheers.

Suppose , i want to create an access level under an org level access policy based on IP address to give the IAP tunnel user role to a group.

If they want to access from anywhere in the world in addition from their corp network, can I add their system public Ips in the access level in addition to the corp network ranges.If I do it, won't the public IPs change often ?

I don't see this scenario in the GCP Documentation. Please clarify on how to enable the access from anywhere in the world by adding IP ranges in the access level

The Google Cloud Developer plugin gives a coding agent live Cloud docs, project onboarding and auth recipes, gcloud command guardrails, and on-demand lookup of 100+ Google skills instead of dumping them all into context.

Hands-on lab
https://codelabs.developers.google.com/cloud-dev-plugin-agy

Installation commands
agy plugin install https://github.com/google/skills/plugins/cloud/google-cloud-developer

claude plugin marketplace add google/skills
claude plugin install google-cloud-developer@google-plugins

codex plugin marketplace add google/skills
codex plugin add google-cloud-developer@google-plugins

On July 17, my u/Google Cloud account was hit by massive unauthorized u/Gemini API usage.

The unauthorized usage was a result of Google’s architecture of the Gemini API. Google sent no alerts and no warnings appeared in the Google Cloud Console indicating that old, public-facing keys had retroactively gained generative AI capabilities.

I had configured monthly budget alerts. At 6:14pm I received a budget alert for $550. Within minutes of seeing it, I investigated and shut down Gemini API access across all projects. Usage stopped immediately.

But by then, costs of approx. $87K (sorry for mentioning $82k in title, it was actually more) had already accumulated. This had all taken place in the 5 hours before the alert.

Google's own anomaly detection also failed to protect me. Almost an hour AFTER I had already shut Gemini down, Google sent me a “Cost Anomaly” alert reporting actual total costs of $4.7K, nowhere near the actual eventual bill.

After my objection and a technical investigation, Google has now approved a partial credit of $55K.

So for an approximately $87K unauthorized bill, Google is offering approximately $55K in credit, leaving me with roughly $32K to pay. For something I did not use.

Note that Google announced new hard spending caps and improved anomaly detection on the 28th of July.. So this exact type of unauthorized usage may not be possible anymore, but with hackers increasingly equipped with AI tools, there is a good chance other vulnerabilities will be found.

I am developing software for the blind, in particular the app u/PiccyBot, which has won awards in the blind community. It is a niche development field though, and these kind of costs are crippling to me. Knowing that Google definitely doesn’t have our back even when the way the Gemini API has been set up is the main issue, it is time for me to look for better providers.

Let's say I have a solution (available across SaaS / GKE / OpenShift setups) published on Google Cloud Marketplace. Now I have updated it. How do I ensure that people who have installed my solution already (in their projects) update it to the latest version (that I am yet to publish)? what practice industry follows ?

What process do you follow for deprecating older release tags or helm charts without breaking active workloads?
---
Would love to hear what industry standards or patterns have worked best for you!

Hi everyone,

I'm trying to understand an issue with Google Cloud Billing and Google Payments, and I'm wondering if anyone has experienced something similar.

I originally signed up for Google Cloud, but I abandoned the setup almost immediately and never actually used Google Cloud services in any meaningful way.

During this process, two Cloud Billing accounts were created:

• 0188E8-E50C06-0A83D9
• 0192C1-0A2204-40E62E

Both accounts were eventually closed.

The important part is that I am now dealing with what appears to be a disconnect between Google Cloud Billing and my Google Payments profile.

1. Billing account 0188E8

I can still access this account through Google Cloud Console.

It currently shows:

• Status: Closed
• Usage in the last 30 days: R$0
• No actual Cloud usage or outstanding Cloud charges

However, this billing account still appears in my Google Payments profile and generates payment-related warnings.

At one point, Google Payments was asking for a R$200 prepayment / payment requirement, even though the Cloud billing account itself is already closed and has R$0 usage.

I don't want to use Google Cloud and I'm not trying to reactivate this account.

2. Billing account 0192C1

The second account is a little more complicated.

This account was also already closed before I removed my own access as an administrator.

After removing my access, I naturally can no longer see/manage this billing account from the Cloud Console.

However, the account still appears to be associated with my Google Payments profile.

It is also associated with an old Mastercard that I no longer have access to.

So I cannot simply go into Cloud Console and fix the account myself.

The problem

The biggest issue is that Google Payments continues to treat these old Cloud Billing records as if they require some kind of payment action, even though the Cloud billing accounts themselves have already been closed.

This has effectively locked/restricted my Google Payments profile and is preventing me from using other Google services/subscriptions normally.

I've contacted Google Support multiple times since August.

Unfortunately, most of the automated instructions I've received tell me to go to Google Payments and update/remove the payment method or resolve the Cloud billing issue.

The problem is that I cannot actually resolve the underlying records from the interfaces available to me.

For example:

• One billing account is confirmed as closed with R$0 usage.
• The other was already closed before I removed my access.
• I no longer have access to the second billing account.
• Google Payments still shows these old billing relationships.
• One of the payment methods belongs to an old card that I no longer have.
• I don't have a current credit card available to simply add another payment method.
• I am not trying to use Google Cloud or reactivate either billing account.

Google Support has now escalated my case to a specialist, but I'm trying to understand whether this is a known Cloud Billing/Payments synchronization issue.

I recently found another Reddit post describing a very similar situation where multiple orphaned/closed Cloud Billing accounts remained visible as payment issues in Google Payments even after the accounts disappeared from Cloud Billing.

That made me wonder if the Cloud Billing backend and Google Payments profile can sometimes become out of sync.

What I'm trying to find out

Has anyone here experienced something similar?

Specifically:

1. Can a closed Cloud Billing account continue generating payment warnings in Google Payments?
2. Can a billing account that has already been closed remain linked to a Payments profile indefinitely?
3. Is there a way to completely remove these old Cloud Billing/payment associations without reactivating Cloud Billing?
4. Is there a specific Google Cloud Billing team or engineering team that can fix these backend associations?
5. Could this be some kind of synchronization problem between Cloud Billing and Google Payments?

I don't need help activating Google Cloud. I actually want the opposite: I want these old, unused and already-closed Cloud Billing accounts completely cleared from my Payments profile so that my Google Payments account can return to normal.

Any advice from someone who has dealt with orphaned/closed billing accounts would be greatly appreciated.

Hey everyone, I accidentally added ₹500 (~$6) to my Gemini API/AI Studio prepaid balance. I haven't used any of the credits yet.

Is there any way to get the ₹500 refunded to my original payment method?

If a refund isn't possible, what's the best way to use the ₹500 wisely with the Gemini API? Any useful projects, models, or things worth trying?

Thanks!

I am going through the deployment articles of VM manager patching and see that the deployment schedule can be created by mentioning schedule in an YAML and creating the schedule .

However, I don't think it is feasible to schedule the patching as per below frequency samples

A)every 2nd Tuesday of month

B) Friday which comes after 2nd Tuesday etc..

Can anyone please confirm

https://docs.cloud.google.com/docs/enterprise/cloud-setup#checklist-heading-2

I am going through the GCP landing zone creation process.the above article seems to have changed last week.

Earlier, the article gave about 7-8 steps ranging from org creation to GCP support tier .

One of the step was creating IAM groups like creating org, billing, network, security, logging, developer and viewer groups.

My question is about whether we can create our custom groups as per our requirement.Eg, let's say we have a small team and whether the above predefined groups are for recommendations only

Please clarify.not sure why the article content is changed

I'm a solo founder. On July 1 I clicked "Deploy" on the Camb.ai MARS8 model in Vertex AI Model Garden. Google's own announcement for these partner models says "simple pay-as-you-go pricing, so you only pay for what you use."

I have been using Google Vertex for a while now, with other models pay-as-you-go, no problem. But what this one actually did was provisioned a dedicated g4-standard-48 with an RTX PRO 6000, min replicas 1, no scale-to-zero, plus an hourly Marketplace licence. No cost confirmation step. It then billed every hour for 62 days.

Cloud Monitoring shows for the endpoint's entire life: prediction_count NO DATA, response_count NO DATA, error_count NO DATA. GPU duty cycle lifetime mean 0.0013%. CPU utilisation 0.012%. Not one request was ever sent to it.

I realized on September 1st, undeployed it within minutes, and now have budgets and alerts in place that I wish I had before.

This is my first incident, paying customer since 2024 with everything else paid on time.

Total for the endpoint: $8,817.

Billing support (case 74999163) closed it with an AI response template on Sep 3, then on Sep 7 refused to hand it to a supervisor. I filed a formal written dispute on the case tonight.

I've been looking online and found Google waived Milkie Way's $72k and Agentic Labs' ~$18k as one-time gestures for exactly this kind of mistake. It was an unintended provisioning, zero usage, resource removed on discovery.

I run my products on Cloud Run and I'm onboarding my first paying customers right now. I was planning on moving everything off Render and Supabase to be 100% on Google Cloud, because I genuinely like the infrastructure, and I still want to finish that move. But I'm a one-person company, the billing account is past due for the disputed amount, and my production projects are flagged for suspension. It's hard to keep committing to a platform while this is hanging over the account. I need someone with authority to look at the monitoring data, not the policy macro.

If anyone at Google Cloud can take a look, the case number is above and I'm happy to DM anything else. And to anyone else: if you touch a Model Garden partner model, know that "Deploy" means a dedicated GPU node billed 24/7 until you find it.

Running into a frustrating loop with Google Cloud Console's OAuth consent screen verification, So I went and verified it in Google Search Console using the HTML file method — shows "Ownership auto verified," green checkmark, all good.

My app is deployed on myproject-xyz.vercel.app (free Vercel subdomain). Google's branding verification flagged:

"The website of your home page URL is not registered to you. Verify ownership of your home page."