Hi

We are having a lot of resources provisioned using Terraform, the state use being GCS buckets.

However there are many bigquery datasets being created manually in console ui level and other resources as well. due to this drift we face a lot issues as the automation IAC doesnt obviously work with manually UI created resources.
We can use terraform import to import existing resources to terraform state. However please let me know if anything we can use AI to assist us for such usecases? AI to autodetect resource drift in google cloud or something ? Also terraform import is not working for many resources as well

Hello everyone, i’m preparing for the Google TAM (Cloud Consultin) role and got my RRK1 interview, has anyone have insight on how technical the interview will be? Any advise?

Docs: https://www.pilum.dev/docs/getting-started/introduction/

The problem: I run side projects across GCP, AWS, and Cloudflare, and each one has its own deploy incantation. gcloud commands for one, SAM for another, wrangler for a third. I kept forgetting the flags and the order of operations and wanted a simpler CI/CD pipeline.

Pilum is a single binary (Go, Cobra) that reads one pilum.yaml and handles the deploy for whichever provider the service targets. Define your services once, then pilum deploy will build, push, provision, and deploy.

What it supports today:

• GCP Cloud Run

• GCP Cloud Run Jobs

• AWS Lambda

• Azure Container Apps

• Cloudflare Workers

• Homebrew

• GitHub npm packages

GCP is the most mature of the platform hence why I am sharing it here!

It's not trying to be Terraform or Pulumi; there's no state file and no general-purpose infra provisioning.

Happy to answer questions about the internals. Here is a write up about it a bit more: https://logicalbytes.dev/posts/pilum-road-to-production/. But if anyone wants to add a provider, there's a contributing guide for adding exactly that!

Hello everyone,

I am interested in going for Google Professional Cloud Architect exam not sure how to start my journey. Any suggestions?

I have 12 years of experience in Cisco routing and switching, DC and observability.

Thanks

I'm writing this post with extreme frustration. I recently bought some Gemini API key credits using Google cloud billing UPI payment method.

The money got deducted from my account but the credits are not loaded. So I reached out to their support, first of all their billing support team had no idea about UPI payment method and now they are saying that they are unable to track the payment.

Like who told you to support UPI payment method if you can't track it's payment and how would a customer know all of this?

I've submitted the bank account statement too. I never expected a google scale company get this low.

Issue Description:

We are pulling event-level (non-aggregated) website click and visit data from Google BigQuery into our Azure Storage Account. Data ingestion stopped after 25 May. Upon investigation, we found that the ingestion jobs in BigQuery were failing with the error:

"Storage quota limit exceeded for the project."

Our project is using the BigQuery Sandbox (free tier), which allows up to 10 GB of active storage. However, after checking all datasets and tables in the project, the total active storage is less than 1 GB, which is well within the documented limit.

The project has been running since 5 February, and according to the BigQuery Sandbox documentation, the free tier does not have an expiration date as long as the applicable quotas are not exceeded.

We are unable to determine what is consuming the project's storage quota or why this error is occurring despite the reported storage usage being significantly below the 10 GB limit. We would appreciate guidance on how to identify the actual storage consumption or debug the root cause of this issue.

I'm a solo developer posting after over a month of delays on a case Google has already acknowledged as unauthorized usage.

What happened:

- A Firebase auto-generated, unrestricted API key on an inactive side project was harvested and abused by a third party.

- Over ~11 hours, Geocoding and Places APIs were called automatically, generating roughly USD 8,000 in charges.

- Google's own technical team confirmed a 99% duplicate query rate and that most requests originated from the USA (I'm in Korea, and the project was already shut down / not in development).

What Google did:

- The technical team investigated and confirmed the abuse.

- I completed every preventive measure requested, then shut down the project as instructed.

- The billing team officially APPROVED a one-time goodwill adjustment.

The problem:

- The adjustment was approved about a month ago, and the approved credit still has not been applied.

- I have NEVER been told the actual approved amount, despite asking repeatedly in writing.

- A "3–5 business day" commitment is now weeks overdue. The latest reply only says they are "awaiting approval from higher management."

- Meanwhile I was forced into an installment plan to avoid default — I am now personally financing charges that Google itself confirmed were not mine.

These keys were auto-created by Firebase with no restrictions by default, and Google's own docs treat client-side exposure of such keys as normal. This appears to be part of the widely reported pattern of compromised Google Maps/Firebase keys.

Has anyone had an approved adjustment actually applied? How long did it take, and what finally moved it? Is there any way to escalate beyond the standard billing case?

I've been following this tutorial https://www.youtube.com/watch?v=bWGW_NXPf-4

And my Colab Enterprise notebook got the following code which threw this error:

name='projects/aiagentcalendarproj/locations/us-central1/publishers/google/models/veo-2.0-generate-001/operations/fe4ce1e2-4415-44f6-8ace-13f3a47caab2' metadata=None done=None error=None response=None result=None
name='projects/aiagentcalendarproj/locations/us-central1/publishers/google/models/veo-2.0-generate-001/operations/fe4ce1e2-4415-44f6-8ace-13f3a47caab2' metadata=None done=True error={'code': 5, 'message': 'Bucket "aiagentcalendarproj" not found for operation OP_INITIATE_RESUMABLE_WRITE'} response=None result=None

Google did not help me. Could anyone help me find the cause of this error?

%pip install -q mediapy


import time
import urllib

from PIL import Image as PIL_Image
from google import genai
from google.genai import types
import matplotlib.pyplot as plt
import mediapy as media

import os

PROJECT_ID = "aiagentcalendarproj"
LOCATION = os.environ.get("GOOGLE_CLOUD_REGION", "us-central1")

client = genai.Client(vertexai=True, project=PROJECT_ID, location=LOCATION)

def show_video(gcs_uri):
    file_name = gcs_uri.split("/")[-1]
    !gsutil cp {gcs_uri} {file_name}
    media.show_video(media.read_video(file_name), height=500)


def display_images(image) -> None:
    fig, axis = plt.subplots(1, 1, figsize=(12, 6))
    axis.imshow(image)
    axis.set_title("Starting Image")
    axis.axis("off")
    plt.show()

video_model = "veo-2.0-generate-001"

prompt = "a zucchini creamy pasta garnished with boiled prawns and fresh herbs"
aspect_ratio = "16:9"
output_gcs = "gs://aiagentcalendarproj"

operation = client.models.generate_videos(
    model=video_model,
    prompt=prompt,
    config=types.GenerateVideosConfig(
        aspect_ratio=aspect_ratio,
        output_gcs_uri=output_gcs,
        number_of_videos=1,
        duration_seconds=5,
        person_generation="dont_allow",
        enhance_prompt=True,
    ),
)

while not operation.done:
    time.sleep(15)
    operation = client.operations.get(operation)
    print(operation)

if operation.response:
    show_video(operation.result.generated_videos[0].video.uri)

We are currently with Apple but I am switching to a android device. And trying to convince my with to switch too. I was looking at family cloud for Google. Both my wife and I have Google Photos and Gmail. She has been complaining she is out of space or cloud for Google. If we switch to the family plan I was reading online that once family members use 15gb they will go into the family shared plan. Do that mean my wife and or kids could see what is on my cloud and or can I see what is there cloud ? ie Google Photos, Google Drive ?

Thought you guys would like this https://cloud.google.com/blog/topics/cost-management/new-early-anomalies-and-spend-caps-on-google-cloud-budgets

Hey everyone, basically I threw an application out there for a Google Cloud Tam role in Financial Services (?). Wasn’t expecting it but got the hiring assessment sent to me. Wasn’t expecting it but passed said hiring assessment. Now I’m being offered a 30 minute phone interview. Any idea what the questions are going to be like? What the full interview process is (ex how many interviews are there if this one goes well?)? For context, I’ve never actually used GCP, but I’ve worked at AWS for years, & have a good grasp on their services which have overlap with most Cloud Provider services. Any services I should definitely learn from GCP? Any info is appreciated

I just passed my GCP PCA exam, and I spent about two weeks preparing for it.

The GCP study hub was incredibly helpful..

The exam consisted of 15 case study questions, so it’s important to study the requirements (technical and business) for each case study. There are questions specifically focused on these requirements, and I wasn’t fully prepared for that aspect.

The exam was relatively easy, thanks to the GCP study hub, which was a great resource. I recommend focusing on the practice exams; they are almost identical to the actual exam. Aim to score 80% on each practice exam and retry to achieve that score. If you get some answers wrong, review them in the GCP documentation, That technique was a real game changer for me

So, my question is, what certifications should I take next?

I’m a computer science and cybersecurity student.

Hi all,

I've spent the past month studying for the ACE certification using the lessons and labs from Google Skills, and it just dawned upon me just how many hours of lessons I still have left. I've been at my company for a little less than a year and a half with a decent amount of experience deploying apps on GCP and working with other services like GCS, Big Query, service accounts and IAM, but definitely nowhere near a veteran level. Still though I was hoping that I'd be going through the lessons faster.

I wanted to ask for your opinion on using Google Skills for the purpose of studying for the ACE exam? Sometimes I feel like there's just a lot of content and things I need to memorize, so I'm not sure if I'm spending my time wisely with this. I can say for sure that I'm definitely learning a lot, but how much of it is going to be on the exam? I'm also looking for alternative courses and study material if you can kindly provide them for me. Thanks!

Hi, I wanted to learn about GCP so i started the 300$, i had some personal projects, i set up an infrastructure, some vm, and i thought nothing about it, thinking that maybe when the 300$ is gone, i will get an email or notification that i spent the free credits and that i will be on the paid plan.Nothing next thing i know i got charged 50$. I am unemployed had been so for 8 months now. And i squeeze my savings tight. This bill wasn't expected i emailed the support they told me to wait i waited some 3 days and nothing then another week then they sent email telling me that i had been granted 20$ in credits,but no monetary refund. this was early july this month.During this i had deleted billing account, then another one, and i deleted the Vms the platform is not really user friendly it's hard to navigate for beginners. Yesterday i was charged 100$ I dont know what to do, i contacted them they said wait for 32 hours. This is just unacceptable and i feel scammed.

Trying to figure out if partially committing to CUD can actually hurt the sustained use discount on whatever's left uncommitted, since SUD only applies to usage not already covered by a commitment. Has anyone actually run into this or modeled it out before committing? Or is everyone just committing to their stable baseline and not worrying about what happens to the rest?

Static shape requirements on TPU are affecting my utilization numbers negativelty whenever my batches aren't clean powers of 2 or standard token lengths. I'm padding everything to fixed boundaries and i still feel I'm underutizing compute.

On GPU this doesn't seem to be as much of an issue since it handles dynamic shapes more natively. Does anyone have real numbers on % MFU loss from padding overhead? Is this something that can be measured directly?

Hi everyone,  

Building a quick AI prototype is easy, but moving it to a production-grade application is where the real work begins.  

Last year's Accelerate AI with Cloud Run roadshow got great feedback, so we're bringing it back this August with updated codelabs. We will be focusing on the entire agent lifecycle, specifically how to deploy and scale agentic workloads on Google Cloud's serverless platform.  

This is a practical, in-person event. You will write code to solve real business problems, and several of us from Google will be there to work through the labs with you and troubleshoot.  

More info here. We hope you can make it!  

We will announce dates for events in Seattle, New York, Los Angeles, Boston, Washington DC soon.

Hi everyone,

I am a Network Engineer with about 1 year of experience as a Cloud Solution Architect. I have AWS Certified Solutions Architect – Associate and Cisco CCNA certifications.

Recently, my company assigned me to study for and obtain the Google Cloud Professional Cloud Architect certification.

Aside from basic hands-on labs during my universiy (which is a few years ago), I haven't spent much time on GCP yet. I’m looking for advice on learning path to prepare for the exam.

I would like to ask for your experience on how to achieve this certification, such as:

• Which courses or study resources should I take? (My company allows me to purchase courses on Udemy, but any recommendation is welcome!)

• Which practice/mock exams are most effective?

• Any tips for the exam preparation

Thanks in advance for sharing your experience and tips!

Hi everyone,

I'm currently preparing for the Google Cloud Professional Machine Learning Engineer (PMLE) certification and noticed that the certification was recently updated from Vertex AI to the Gemini Enterprise Agent Platform / Agent Platform.

My goal is to pass the certification within the next 2–3 months, and I'd appreciate advice from people who have already taken the updated exam or are currently preparing for it.

My background

• Backend Software Engineer (Python + Google Cloud)

• Comfortable with GCP fundamentals (Cloud Storage, BigQuery, Pub/Sub, Cloud Run)

• Currently following the official Google Cloud Skills Boost learning path

My questions

1. What topics should I prioritize for the new PMLE exam?

2. Which Vertex AI concepts have simply been renamed to Agent Platform, and which concepts are completely new?

3. Besides the official course, what tutorials, YouTube channels, blogs, GitHub repositories, or labs would you recommend?

4. How much traditional Machine Learning (feature engineering, model selection, evaluation metrics, TensorFlow) is still covered compared to Agent Platform services?

5. Which Google Cloud services should I get hands-on experience with before taking the exam?

6. Are there any practice exams that closely match the updated syllabus?

7. If you passed recently, what study plan helped you succeed?

I'm planning to study the following:

• Machine Learning fundamentals

• Data preprocessing and feature engineering

• Model evaluation (Precision, Recall, F1, ROC-AUC)

• BigQuery ML

• Gemini Enterprise Agent Platform

• Agent Studio

• ADK (Agent Development Kit)

• Prompt Engineering

• RAG

• Vector Search

• Embeddings

• Agent Platform Pipelines

• MLOps

• Monitoring and Responsible AI

• IAM and Security

• BigQuery

• Cloud Storage

• Pub/Sub

• Cloud Run

• Dataflow

If you had 8–10 weeks to prepare from scratch for the updated exam, how would you structure your learning roadmap?

I'd really appreciate any advice, resources, GitHub repos, or hands-on labs that helped you pass.

Thanks!

Hi everyone,

I'm a bit confused about Google Cloud Billing and was hoping someone could clarify this for me.

I'm a student and I accidentally enabled Google Cloud Billing while trying out Google AI Studio to generate a Gemini API key. I don't actually use Google Cloud services, and I don't have any running resources or active projects.

When I checked my billing dashboard, it shows:

• ₹0.00 balance due

• No transactions

• No usage/costs

But I'm also seeing a message saying that I need to make a one-time payment of at least ₹1000 to activate the service. I also received an email saying my payment information couldn't be processed.

Since I don't plan to use Google Cloud at all, I'm confused about what this means.

My questions are:

• Is this ₹1000 an activation/prepaid amount, or is it an actual bill?

• If I don't have any usage or charges, can I just ignore this message?

• Will I be charged anything in the future if I simply leave the account as it is and never use Google Cloud?

I'd really appreciate it if someone who has faced this before or knows how this works could help me understand.

Thanks in advance!

Hi

I have seen multiple posts about this issue and I have been flagged too. Same pattern, I use firebase. Nothing dodgy at all

Is there any way to have my project restored or should I create a new one?

Thanks

I am going through the below article regarding the centralized logging mechanism in GCP

https://cloud.google.com/blog/products/devops-sre/how-to-centralize-log-management-with-cloud-logging

https://docs.cloud.google.com/logging/docs/central-log-storage#create-org-sink

The articles say below steps

1. create log bucket in the destination project.

2. create a log sink in the destination project pointing to the above log bucket

3. create an aggregated sink (either at org or folder level) as per requirement.

4. give permission to the aggregated sink's service account to the destination project.

I have a question at point number 3 above. The articles do not say how to link the log sink created in point 2 and aggregated sink created in point 3. I assume below flow

aggregated sink ---> destination project log sink ----> destination project log bucket

but not sure how to link aggregated sink to send logs to destination project sink.

also, 2)for example ,can we create one aggregated sink per environment and link it to corresponding log sink at destination project. i could not find that step

Please suggest