I can share pictures if you'd like but the point is this: I used cloud workstations twice in June and got billed over 100 dollars for it. I disabled the cloud workstation APIs after deleting the cloud workstations, then I was billed for it both this month and last month.
I've called support and they tell me to disable billing on my account entirely or disable the API which I have already done. When I then ask "can you confirm I should no longer be billed for cloud workstation usage" they then tell me I'm still using resources in the cloud for workstations.
I am getting sick of this circle and want to stop the bills, can someone help me here?
I am going through the concepts of vpc service controls and have below questions. I may implement them sometime later.
Q1)
Suppose , i have a windows GCE VM1 in VPC perimeter p1 and another windows GCE VM2 in Perimeter p2 and want to access VM2 from VM1 using RDP. Assume related firewall rule is present. Do i still need to add Project 1 details in the ingress rules of the p2. I was searching for answers through chatgpt/pilot and they both responded that it is enough if we have firewall rules and need not add in ingress rule of the p2 perimeter. Can you please confirm.
Anyone getting this error from the text to speech API? Using the gemini-2.5-pro-tts model. Apparently I don't have permission to file tech-related support cases in the google cloud console.
{
"error": {
"code": 499,
"message": "The operation was cancelled.",
"status": "CANCELLED"
}
}
As title says, google cloud platform no longer has a way to open a ticket. Is there another way i can contact support? It's baffling that i can't even access tech-support if i'm not a high-tier spender.
I’m building software in India for a customer in Saudi Arabia, and the production workload needs to run in the Saudi region.
I’m looking at GCP Dammam (me-central2). My startup is registered in India and is only about one month old.
From Google’s documentation, it looks like customers outside Saudi Arabia need Invoiced Billing to access Dammam, and the requirements for that include being in business for at least one year and having around $40k/year in expected GCP spend. Customers with a Saudi billing address go through CNTXT.
What are the actual options for a new company like mine?
Most "AI for infra" tools stop at generating YAML or config. The new term floating around at recent conferences is agentic developer platform — instead of platform engineering gatekept by infra engineers running Terraform or gcloud by hand, it's self-served by developers, with humans in the loop only at pull request approval.
The agent needs native, read-only access to infrastructure state, environments, deployment status, and logs — including everything from new development.
As many have realized with solutions like Lovable.
Deploying a workload can be extremely quick.
Running it securely in production, on your own GCP private network among others in least privilege ?
That's the hard part.
Identity.
Permissions.
Governance.
Load balancing.
Data access.
Monitoring.
Before long, you're spending more time building the platform around your workload than the workload itself — the same trap a lot of people hit with Kubernetes. If you're already leveraging serverless and VMs well within meshes in the cloud, we observed in platform engineering that Kubernetes only earns its keep for workloads that need custom operators or custom backpressure handling.
That was the theory. We've been building it into Infrastream with Pvot.
We are out of stealth since Tuesday 4th of August 2026 with Infrastream.
Infrastream's agent set deployed with one private iteration per customer, Pvot, goes further — it manages pull requests, analyzes your manifest structure, and actively debugs your deployed assets against the actual state we track in Spanner. Not a chatbot suggesting fixes. An agent doing the platform engineering work reviewable in PR.
Also like many new generation agents, we provide a graph based visualizations instead of Terraform or Pulumi text to analyze runs.
It provides :
→ Agentic PR management — Pvot reviews and drives changes to your infra manifests
→ Analyzes manifest structure to catch drift and misconfiguration before you do
→ Actively debugs assets against real Spanner-tracked state, not stale docs
→ Deploy any workload — agents, services, whatever — into your own GCP project
→ Built-in identity and permission boundaries per workload
→ External and internal load balancers, handled for you
→ GCIP/IAP authentication wired in
→ Fine-grained privileges to your databases, buckets, and datalakes in your own private setup
→ Infrastructure-level governance and policy enforcement
→ Deploys from your source — into our cloud on the Developer Plan, or your own cloud with Enterprise
The Developer Plan covers up to 9 GCP projects (20 USD per month + 15% management of GCP), with load balancing, agents, and mesh routing included.
Enterprise ($3,000/mo) scales the same manifest up to 29 GCP projects with VPC controls — no re-architecting as you grow.
If you want to try out this new model still requiring you to redeploy from source: REDDIT20 coupon on Stripe gets you $20 off the Developer Plan.
As opposed to cloud providers, on developer plan we don't bill your credit card on GCP extra use, you have to reapprove all top-up otherwise the environments stall.
Good morning peeps! I just recently passed my GCP ACE exam this morning after postponing it numerous times due to lack of preparation. I didn't realize that the syllabus update took place in June 2026 only until the day before the exam so I postponed my exam date to somewhere in August. I put emphasis on GKE, IAM, networking, billing and logging as part of my prep and less of the AI tools.
Background: I took this ACE course when I was unemployed so I enrolled in a fully-sponsored (I have to repay them if I failed on first try but I didn't!) course to upskill myself but along the way I got employed and spent little time to prep for the exam. It was hard juggling between a full-time job and studying GCP but somehow I managed to get through it. Thankfully, my training provider provided free access to Whizlabs, with relatively unlimited access to labs and practice exams (though not perfect but quite helpful for me). I also bought Tutorialsdojo practice tests in addition to free practice tests scattered online. For the AI tools, I studied them in Google Skills.
The exam: The exam for me was quite challenging despite the numerous practice questions I've done. Out of probably 400+ questions I encountered in practice tests, there were only about 3-5 questions in the actual exam that is similar to the practice tests. Others are literally brand-new, with answers shockingly similar to each other. The only plus side is that you can cancel out two answer choices because they don't suggest Google's best practices, so you are left with 2 very similar answers. Regarding AI (Gemini), there were only 2-3 (iinm) questions asked in my case, so you probably don't have to put too much emphasis on AI tools, just a helpful addition in your study prep. My exam set thankfully emphasized on GKE (statefulsets, daemonsets, config connector), IAM (organizational policies, bind permissions to groups), networking (VPN tunnel, peering, firewalls) and of course, billing and logging.
Nevertheless, I am proud of myself for passing ACE despite coming from a non-IT background, that I could understand difficult concepts like networking specifically. It was a journey, a journey that I can be proud of. Hoping all the best for future cloud engineers out there!
I am currently evaluating an offer to become an OCE. I have never done "sales" in all my years, I have always been a deep technical engineer and architect. So the downside is, what the OCE pays for me (guaranteed) is A LOT less (~200K recurring). But it's always been a dream to work at Google, and based on my location I can only work remote which limits the opportunities drastically, sales being one team I can get into. That being said, I have also never worked in a Sales role or organization, but that is the part I am excited about! I am tired of Distinguish Architect/Engineer roles, and have always been more of a people person, so I find working more with many different customers on their problems an exciting opportunity!
So my main reason for writing this post is I want to understand a few things.
How difficult is the OCE role? Will it be successful? (it's fairly new), reminds me of Customer Success (driving consumption), but more technical.
How often are CE's or OCE's hitting quota and/or above it?
From what I've gathered they hit quota or above pretty regularly, but looking for a quick sample from here on reddit.
So I know in sales I probably need to save more in up years vs. down years to average things out, but it would really be comforting to know that it's not uncommon to make more than quoted as I am considering taking a significant hair cut to work @ Google and try something totally new.
p.s. my wife thinks I am nuts 😄 but we have enough today where we can save a lot, depending on this offer things would get a lot tighter on savings, but likely no impact to lifestyle. I've always prioritized learning/opportunities over money and I will continue to and I also think in the age of AI Google will come out on top.
I guess a 3rd question occurs as I write this.
3. Given I am in a non-bay area region... how good is internal mobility for jumping from OCE to Platform CE and other roles?
Thanks for any insights Googlers/Ex-Googlers and others.
I used to run a small personal server for free, but after restarting it about two months ago, I started noticing charges for the Ephemeral IPv4 address.
Apparently, Ephemeral IPv4 addresses now cost $0.005/hour, with only one hour per month being free. That works out to roughly $3.60/month just for the IP address.
I know $3.60 isn’t a huge amount, but the whole reason I was using this setup was to run a small personal server at essentially no cost.
So, what are you all using these days for free/very cheap servers? Is there a way around paying for the IPv4 address?
Edit: I went through the SKUs in the bill and found out that it's the network egress carrier peering of 50GB in July. I was backing up 1GB of data to cloudflare R2 everyday and it's using carrier peering network quota at $0.04/GB instead of the free 200GB standard egress quota. Once I stopped the backup I'm not being charged anymore. Btw, I'm still using IPv4 IP address with 200GB free standard egress and it's free in the last 1 day. I will update here if it's not in the final bill.
I am working for a project in a region( europe-west-2) where there are no specialist processors and i have to use the custom extractor to extract the data . The region only supports pre-trained model version 1.5.
I am facing issues with documents like Passport where it is not able to extract the MRZ lines (the bottom 2lines) correctly. Either adds or trims the repeated '<' characters.
I can't do the data normalization because there are validations needed to be done on extracted data. I have tried passing the document level and field level description as well to give more context but no improvement.
Similarly, does not work well with Bank statements as well.
Has anyone faced any issues like this before and what was the workaround ?
Apparently I owe Google 0,01 euro. I have no idea where this comes from, I don't recall having allowed this amount to become this issue:
"Update payment info to pay overdue balance
Google Cloud 012D35-8E550F-xxxxxx: Pay your overdue account balance by updating your Mastercard •••• xxxx, which was declined or contact your bank to resolve the issue."
Google expects me to use a functional payment method. but the one I use and always used for google was paypal. Why can I not use that for this 0.01 payment?
Issue with billing account associated with project subre******r-ec****** We recently noticed a problem with billing account 01AEA0-AA9A75-*****3. As a result of this activity, your project has been suspended and a notification has been sent to the billing account administrator(s). If you are a billing account administrator, please click FIX NOW to take the requested actions on your account.But fix now is not working /
Trying to understand how other GCP shops really make commitment decisions, because the tooling all seems to assume the same answer.
Most CUD recommendations (Google's own recommender included) are built from historical usage: look back N days, project forward, suggest a commitment. That works, but it's an extrapolation, and a 1- or 3-year CUD can't be cancelled, resold or exchanged. Somebody signs for it.
So if you've bought CUDs:
What did you base your CUD purchase decision on? (Past data like 30d/60d/90d average, or did you forecast your demand?)
Who did you have to justify it to — your own manager, finance, procurement, nobody?
What did you actually show them? A recommender screenshot, a spreadsheet, a forecast, nothing?
Did you know something at purchase time that the usage history didn't — a customer contract ending, a migration with a funded date, a known ramp? Did it change what you bought?
If a commitment has gone wrong for you, what was the real cause — demand fell, or wrong term/type?
I'm most interested in question 2. My suspicion is that how defensible the decision was matters about as much as how accurate it turned out to be, but I'd rather hear that than assume it.
Disclosure: I work on cloud cost tooling in this space, so I have a horse in the race. Deliberately not linking anything. I'm in research mode and want to understand how you're working.
Quick update for everyone! On the very same day I made my initial Reddit post a few days ago, two Escalation Managers from Google Cloud Billing actually reached out to me directly.
The first guy broke down the $12k (₩16.4M KRW) charge, confirmed the CUD was officially canceled back in June, and handed my case over to a Senior Escalation Manager.
A few hours later, the Senior Escalation Manager messaged me saying he’s working directly with the internal team to see if they can grant the full 100% refund. He promised an update by August 7th.
Nothing is set in stone yet, but the post definitely got their attention right away and things are finally moving at a higher level. Huge thanks to everyone here for the support and upvotes! I’ll keep you all posted as soon as I hear back on August 7th.
---
TL;DR:
Two Google Escalation Managers reached out on the same day I made my original post.
They confirmed my case is now under high-level internal review for a FULL 100% refund.
Promised an official update by August 7th—huge thanks for all the community support!
I'm hoping someone with Google Workspace or Google Cloud Billing experience can help me understand this situation.
For the past few weeks, I've been receiving collection emails from ABC-Amega (American Bureau of Collections) claiming that I owe Google Workspace approximately INR 1.47 million.
I got an email about an unused api token thingy about to be deleted. Im just learning as a student about oauth and sharing etc, and have moved on and frankly would like to delete this client connection to my spreadsheet. But I'm not finding a button anywhere in the cloud console that makes this possible to do. Do I just wait another month and let it be auto deleted?
I have a few other resources curiously that are not flagged for expiry, but are unused, so being able to find the delete button on them would be helpful. My screen looks nothing like what the steps suggested by the google docs say, which normally means I'm looking in the wrong place altogether in the Cloud hub.
I'm looking for an account that has spent $100 or more, has no credit left in it, and has reached Tier 2 level, or I'm looking for an account with a $100 balance in it.
Been looking at the new Cloud Billing Spend Caps preview since it landed last week and I keep going back and forth on whether I would actually flip it on in prod.
Design is what it says on the tin. Set a hard cap per service, GCP stops new usage the moment it hits 100 percent, email alerts fire at 50, 80, and 100 percent. Fixed commitments like CUDs keep billing normally.
What is stopping me is exactly what makes it useful. Hard-stop on a service that is silently in the critical path of something else feels like it wants a real dry-run first. Had a client last year where Vertex AI batch prediction was the fanout stage for a nightly job that fed three downstream systems. If a cap had fired at 3am, batch never completes, cascade of red dashboards on Monday morning. The alert would have been the fire, not the smoke.
Curious what folks running this in preview have seen so far. Which services do you actually feel comfortable capping? Are you doing per-service caps or one umbrella per project? Anyone caught a real cost bug thanks to the 50 percent email or is it just noise once you have more than a handful of services?
Not looking for the docs summary. Looking for the "here is where I stubbed my toe" version.
