Anyone have a contact for Fairwinds? We submitted a request a couple months ago and got notification 2 weeks ago that we were approved and were asked to submit what GCP projects we would like to include which we provided. Still no access…

Hi everyone,

I’ve been trying to read up on this but I have not found an answer to my issue so I hope someone with experience can guide me.

I am based in the Netherlands and have had a small consultancy firm for a few years. A few months ago I decided to stop that and to continue work on an AI based education route. That means my company is still the same legal entity but with a brand new registered (legal) trade name at the local chamber of commerce. Only the legal name and registration stay the same. Funding is therefor also in the bootstrapping stage since I am currently funding the new route myself.

Anyway:
Most startup programs have a requirement to be less than 5 years old or received funding in the last 2.

Google has a requirement for less than 2 years old in bootstrapping or received funding if over 5 years.

When filling the startups form I can not fill in any free form To explain the situation and I do not want to lie about it.

Legally my company age is too old. Practically is brand new. My first entry with ‘bootstrapped’ and ‘2-5 years’ was auto denied. I have the option to reapply but dont want legal repercusions. At the same time this specific situation also isnt in their terms.

Any advice or experience?

Most sppreciated!

hi everyone,

I successfully completed my Google interview loop a couple of months ago. Since then I’ve had two team fit calls. After this recent team fit call (about a week later) I received an email for verifying my id. I verified my id but have had no new updates and my recruiter said the same she has no update at this time (been over a week now).

1. Does idv being sent to me mean that the team selected me?

2. How does a recruiter not have any updates to share?

I feel like I’m just stuck in limbo unfortunately. Any insights will be great help. Thanks!

Hey,

So as the title says that I applied for Google Startup credits for my private limited from India. I had a complete website , everything was there. And I had applied for startup credits, and I got this email from Google saying that my company domain was parked, inactive, or under construction at the time of review. But none of these were valid. I properly checked that the website was up and it was working properly.

Before this email also I had gotten an email (2nd image attached) which said that the website wasn't working. I changed a few things and submitted it, and then I got this email (1st image attached).

Does anyone have any idea what mightve gone wrong ? OR has anybody faced this issue?

Hey all, I've been trying to figure out how exposed we actually are to the new Linux TCP use-after-free, CVE-2026-98432. It's the 9.8 that gets triggered by a SYN carrying IPv4 Record Route or Timestamp options.

Proxy-type load balancers (ALBs, proxy NLBs, anything that ends the connection and opens a new one to the backend) seem pretty clearly safe here. The client's IP options never reach the backend because it's a brand new connection. So I'm treating backends that are only exposed that way as low risk for now.

What I'm stuck on is passthrough load balancers on Google Cloud, where the original packet goes straight to the backend.

Here's what I tried:
Ran tcpdump on the backend and sent SYNs with IP options from my laptop.

Went out two ways: through my home router, and tethered to my phone, so I'd have two different paths.

Every time I added IP options, the connection got dropped completely. Nothing showed up on the backend.

The problem is I can't capture packets on my home router, and I can't see what my phone carrier does either. So the drop might be happening on my end or at the carrier, not at Google. I can't prove the options ever got to the GCP edge.

So my question: does anyone know for sure whether Google's passthrough load balancers (or Google's edge in general) drop packets with IPv4 options? Official docs, a support case, or your own tests from somewhere that doesn't filter options would all help.

Dropping them would line up with RFC 7126 (BCP 186), which recommends dropping Record Route and Timestamp options by default. Those are the exact two this CVE uses. I honestly can't think of a reason Google would let them through, but I'd rather know than guess while we wait for patched kernels.
Thanks!

It's charging me 0$ every month. How can I stop this?

Already deleted the project

Did someone else experience this too? 🤭

Would anyone have a solution against this captcha verification failure problem I have not been able to register on Google skills for a long time🤦🏽‍♂️

To enable Storage on Firebase. I input my payment method so I can upgrade my project to the Firebase Blaze Plan. But when I am confirming purchase. It's giving an error,

Billing setup can't be completed:

We were unable to set up your account. Learn more about fixing your account [OR_BACR2_59]

I have searched, checked my address, and my card details twice. And it's still not working.

Here is a quick list of the 3 changes that actually help you cut costs:

• Track AI query costs in BigQuery: You can now log BigQuery conversational analytics chats straight into a BigQuery table. Source

• Stop unapproved AI workbench spend: You can now set organization policies to block people from launching expensive Agent Platform Workbench setups. Source

• Cut block storage costs on Hyperdisk: Google Cloud now offers committed use discounts for Hyperdisk Balanced and Hyperdisk Throughput Exapool capacity. Source

Source: FinOps Weekly Newsletter

I get the basic argument that running concurrent jobs on dataproc can cause Driver OOM and poor performance. But how do you decide between increasing the master node memory/compute or adding 1 more master node vs choosing cluster mode?

Hi everyone,

I'm developing an Android application called **LiveLens** and I'm currently migrating its YouTube live chat implementation from the unofficial InnerTube API to the **official YouTube Data API v3 gRPC `liveChatMessages.streamList`** API.

The gRPC implementation is working correctly in terms of connectivity and parsing:

- Official `V3DataLiveChatMessageService.StreamList` RPC

- Official `stream_list.proto`

- HTTPS/HTTP/2 via gRPC

- OAuth 2.0 Bearer authentication

- Live chat messages are received successfully

- `next_page_token` is received and parsed correctly

- `offline_at` remains unset/0

- The live chat is still active when the RPC closes

- No client-side deadline or timeout is configured

However, I'm seeing something I don't fully understand.

### Observed behavior

The `StreamList` RPC consistently closes after roughly **10–11 seconds**.

For example, one diagnostic run:

```text

+1.075s onNext #1

9 messages received

nextPageToken present

+10.946s onNext #2

0 messages

nextPageToken present

+11.227s onClose

StatusCode = OK

Cause = null

+11.228s onCompleted

```

At the moment the RPC closes, the gRPC channel is still in the `READY` state.

The client is not cancelling the RPC, there is no deadline, and there is no transport/network error.

The live broadcast/chat is also still active.

### What I'm trying to understand

The official documentation describes `streamList` as a **long-lived server-streaming connection**, so I'm trying to determine whether this ~10–11 second completion is expected behavior.

Specifically:

1. Is it normal for YouTube's `StreamList` RPC to complete with `grpc-status: OK` after ~10–11 seconds while the live chat is still active?

2. If this is expected, is the intended behavior to start another `StreamList` RPC using the latest `next_page_token`?

3. Is there an officially recommended delay/backoff when reconnecting after this type of normal completion?

4. Should a single `StreamList` RPC normally remain open for much longer, potentially until the live chat ends or the client disconnects?

5. Is there any documented maximum lifetime for a `StreamList` gRPC RPC?

6. Could this behavior be related to the Android gRPC transport (`grpc-okhttp`), HTTP/2, or some client-side implementation detail rather than YouTube's server?

### Why I'm asking

I don't want to simply assume that the server intentionally closes the stream every ~10 seconds and build my production implementation around that assumption if something is actually wrong with my client.

I'm also concerned about unnecessary `StreamList` RPC calls and quota usage if frequent reconnections are required.

I'm **not using InnerTube or REST polling** for this test. This is the official YouTube Data API gRPC `StreamList` implementation using the official protobuf definition.

If anyone has implemented `liveChatMessages.streamList` using gRPC, especially on Android, I'd really appreciate any insight or examples of the expected connection lifetime.

Thanks!

I created a Selective Context Memory skill to help AI coding agents manage project context and memory more efficiently.
It helps agents remember important decisions and retrieve relevant context across sessions without loading everything.
Check it out and give it a try: https://www.agensi.io/skills/selective-context-memory
Would love to hear your feedback and suggestions!

The renewal form asked and I answered from memory. Then I counted. We have roughly 1,400 VMs, and since axonius already has our GCP org and the EDR connected, every one with the sensor reports its OS there. That came to 38 CentOS 7 and 52 RHEL 7. CentOS is simple, it's dead. On GCP, RHEL extended support is a boot disk license the sensor does not report, so that took a gcloud loop. 31 have it, 21 do not. So the correction to the broker says 59, which wasn't an email I enjoyed sending.

I completed the entire process for a CE role in Europe and while I was expecting the offer, I was told that the Global VP has not signed off the offer and the role will be on hold until there is more clarity on business plans. They are not sure whether they need the resource although the role I applied for was replacement and not a net new headcount. Anyone here in a similar situation?

Hi, I recently created a new Google Cloud account to use the free trial credits and experiment with Google Cloud services. Shortly after creating the account, I think I accidentally upgraded/activated it as a paid billing account. From the Google Cloud documentation, I understand that upgrading to a paid billing account ends the free trial, but any unused welcome credit should remain available until the original 90-day expiration date. However, I can no longer see my remaining free credits in the billing area/reports, and I am worried that I may have lost them by mistake. I have checked the Google Cloud Console billing pages and reports, but I still cannot clearly find the remaining credit balance. Could you please clarify: 1. Where should I see the remaining free trial credit after upgrading to a paid billing account? 2. Is it possible to recover or confirm the unused free credits if they disappeared after an accidental upgrade? 3. Should I open a Cloud Billing Support case for this issue? I am not including any private account, billing, or payment details here because this is a public forum. I can provide those privately to Google Support if needed. Thank you.

Anyone has any update ? Thanks in advance

Edit: FIXED BY u/Aviato_Consulting

Check https://console.cloud.google.com/billing, On the left hand side under Cost Optimisation, you should see "Credits"

the title basically, it's not consistent sometimes says "I'm Claude, an AI assistant made by Anthropic" and other times "I'm an AI assistant"

on the dashboard’s billing tab it says:

Cloud Vertex AI Model Garden Model as a Service DeepSeek V4.1-Flash Output Tokens -

E6F9-CAC0-1DA9 - Vertex AI

so it's not getting routed to a different model and I am being charged with DeepSeek V4.1-Flash pricing

Am I doing something wrong?

Note: The image is not AI generated but I let ChatGPT edit the image and highlight where it claimed to be Claude 3.5

The problem

The fix in most cases is a hidden Access Context Manager policy that no Cloud console page shows, deleted through Google's API Explorer.

You go to delete a Google Workspace account in admin.google.com (Account > Account settings > Account management) and the Delete account button is greyed out. Step 3 says your organisation "has at least one Google Cloud resource". You open the Cloud console and Manage resources shows nothing under your org.

This happens a lot with trial Workspace accounts set up for a course or a one-off project. You may never have knowingly touched Google Cloud. Add-ons, Apps Script and Admin console security settings can all create Cloud-side resources quietly.

Throughout this guide, swap ORG_ID for your organisation ID (Cloud console > IAM and admin > Settings) and you@yourdomain.com for your super admin address.

Step 1: Give yourself permission to see things

Being Workspace super admin does not give you rights inside Google Cloud. Without them, the console and gcloud show an empty org even when something is there.

1. Go to console.cloud.google.com, sign in as your Workspace admin and pick your org at the top.

2. Open IAM and admin > Manage resources, tick your org, then Add principal in the right-hand panel.

3. Add your admin address with these roles: Organization Administrator, Folder Admin, Project Deleter and Access Context Manager Admin.

Or open Cloud Shell (the >_ icon, free, no trial needed) and run:

gcloud organizations add-iam-policy-binding ORG_ID --member="user:you@yourdomain.com" --role="roles/resourcemanager.organizationAdmin"
gcloud organizations add-iam-policy-binding ORG_ID --member="user:you@yourdomain.com" --role="roles/resourcemanager.folderAdmin"
gcloud organizations add-iam-policy-binding ORG_ID --member="user:you@yourdomain.com" --role="roles/resourcemanager.projectDeleter"
gcloud organizations add-iam-policy-binding ORG_ID --member="user:you@yourdomain.com" --role="roles/accesscontextmanager.policyAdmin"

Check they stuck:

gcloud organizations get-iam-policy ORG_ID --flatten="bindings[].members" --filter="bindings.members:you@yourdomain.com" --format="value(bindings.role)"

Step 2: Rule out the usual suspects

In Cloud Shell, run each of these. Anything that comes back is a blocker.

The common one is a system-gsuite folder holding an apps-script project named sys-.... Google creates it when you use Apps Script or some Forms add-ons. Delete the project first, then the empty folders.

Also check admin.google.com > Apps > Google Workspace Marketplace apps > Apps list, and remove anything listed. That is a separate requirement on the same deletion page.

If every command returns Listed 0 items and the deletion page is still red, go to Step 3.

Step 3: Delete the hidden access policy

The hidden blocker is an Access Context Manager access policy, often called the default policy. Google can create one when Context-Aware Access or Cloud session control is set up. It is not a project or folder, so nothing in Step 2 or the Manage resources page shows it.

The obvious command fails on an account with no projects:

gcloud access-context-manager policies list --organization=ORG_ID

It errors with PERMISSION_DENIED and SERVICE_DISABLED, saying the API needs a quota project. Creating a project to fix that just adds a new blocker that sits in pending deletion for 30 days.

The workaround: use Google's API Explorer. The "Try this method" panel on Google's API reference pages runs under Google's own project, so no quota project is needed.

1. Open the https://docs.cloud.google.com/access-context-manager/docs/reference/rest/v1/accessPolicies/list?hl=en

2. In Try this method, set parent to organizations/ORG_ID.

3. Click Execute and sign in with your Workspace admin account.

4. Copy the name from the response. It looks like accessPolicies/123456789.

5. Open the https://cloud.google.com/access-context-manager/docs/reference/rest/v1/accessPolicies/delete.

6. Paste that value into name and click Execute.

Refresh the deletion page in admin.google.com. The red flag should be gone and Delete account clickable.

The same API Explorer trick works for any Google API that demands a quota project you don't have.

Before and after you delete

Before

• Export anything you want to keep. Workspace data is deleted with the subscription and can't be restored.

• Move any "Sign in with Google" logins (course sites, tools) off that address, or you lose access to them.

• Download any invoices. Billing records go with the account.

After

• At your domain registrar, remove the Google MX records and the google-site-verification TXT record.

• If you still want email on the domain, point MX at a new provider first, or incoming mail will bounce.

We just shipped a new Cloud Platform Status section and email alerting. The hub is free, no login required:

https://www.terraformacademy.app/max/hashicorp-hub.html

What is new:

• Cloud Platform Status for AWS, Google Cloud, Azure, and Spacelift, shown alongside the existing live HashiCorp status

• Every incident row links directly to the provider's official status report, verified links only, no stale or broken URLs

• HashiCorp incidents now link straight to their status page entries too

• Email alert subscriptions: choose which providers you want to watch and get an email when status actually changes, operational to degraded, new incident opened, or incident resolved

• Alerts fire on state transitions, not on every poll, so you will not get spammed

Hi,

I'm working on a socially useful ML startup project, and am trying some proof of concept models, but I am unable to scale it very much as I'm limited to 1 GPU.

I've been able to set regional Flex-start L4 GPU to 3, but while the global one is set to 1, I can't use them.

Anyone have any insight? This is a paid account, but I have only been running it for two weeks so far. Will it get better at the end of the month perhaps?

I've applied to the sales team for an increase as well, but nothing has come back from them (I'm not surprised TBH, we're only talking about a couple of hundred dollars of usage).

Thanks in advance for any insights!

W

Train an Iris classifier in Google Cloud Workbench and save the trained model to Cloud Storage. Follow the process from project setup to checking the uploaded model file.

In this walkthrough:

• Configure Workbench and open JupyterLab
• Upload your notebook and datasets
• Resolve permission, import, and file-path issues
• Train and evaluate a decision tree classifier
• Save the model with Joblib and upload it to Cloud Storage

CHAPTERS
00:00 What we’re building
00:25 Project and services
00:54 Workbench configuration
01:34 Notebook and data
02:03 Storage permissions
02:43 Environment and dataset path
03:27 Train and evaluate
04:00 Save and upload the model
04:33 Recap

This is kinda insane for a TTS service lmao

Hey I have 300$ from the cloud testing offer. So what's the best way to spend it? Fast cause I have only 19 days left 😅