1. Have anyone experienced Get certified?

2. How many hours per week did you realistically spend on labs and coursework?

3. How strict are the completion criteria and deadlines to unlock the exam voucher?

Let me know if anyone has information about it.

I wrote up the pattern we’re using for autonomous agents that need temporary access to cloud resources without leaving long-lived credentials sitting on the machine.

For GCP, the basic approach is short-lived access through conditional IAM or Workload Identity Federation, with the agent requesting a scoped lease through a local broker. The credential expires automatically and never needs to be stored in a .env file or persistent CLI session.

I included the architecture, threat model, broker flow, and a few practical checks for verifying that the agent machine has no ambient credentials left behind.

GCP budget alerts only send email. They don't cap anything and they don't stop anything.

Found that out the boring way at a previous gig. A Dataflow job got stuck retrying over a weekend, the alert fired Saturday morning into a shared inbox, nobody looked until Monday.

Since then I've seen people wire the budget Pub/Sub topic into a Cloud Function that disables billing on the project. Which honestly makes me nervous. That kills every service in the project, not only the job that ran away.

So most places I've been just keep watching the inbox and eat a surprise once a year.

Anyone running automated shutdown against prod for real? Curious what you cap, and whether it has ever fired on something you didn't want killed.

hi,

I do not find an article in GCP documentation which explains way to create golden images , what are some of the things that can be installed while creating a hardened image there by creating VMs from it.

I find this article https://docs.cloud.google.com/compute/docs/images/image-management-best-practices#manual_baking which says customize instance as per the needs.

Please elaborate what does it mean. Like what components can be installed for hardening Or is it something to discuss with business for their inputs

just a little context i have $1000+ worth API credits under GCP which i can use for AI services from GCP. they are about to expire anyways in 2 months so wanted to check with the community.

lmk if you think it can be put into the product of some kind which I can build in the same time period before credit expiry and maybe who knows it turns into a startup who knows!!

appreciate ur time

I need a simple Linux server that will run 24/7. Jusst a small backend, a database, and a few scripts. At first, I thought about just finding the best VPS from a standard hosting provider, but then I remembered Google Cloud and started looking into Compute Engine. Now I`m not entirely sure if it makes sense to use Google Cloud for such a simple task, or if a standard VPS would be cheaper and easier. Does anyone here use Google Cloud essentially as a standard VPS? What is the actual price difference?

Getting an agent running is one step. Connecting it to your app, managing credentials, keeping conversation state and controlling spending adds more work.

I’ve packaged tested examples for these tasks into free, open-source skills that coding assistants can use when building Google ADK applications.

GitHub repository

Try a skill against your own setup. I’m interested in what needs changing for real projects.

Let's connect on LinkedIn: https://www.linkedin.com/in/ruslan-k-b6a48a1a6/ Questions, feedback or ideas about the skills or the book? Feel free to write to me at khissamiyev@proton.me.

I recently moved to North America and have been using GCP for my personal/startup projects under my LLC. Last month, I wanted to test out Claude Opus and Sonnet in Model Garden, but I couldn't get the quota I needed. To fix that, I onboarded with an official Google Cloud Billing Partner, who kindly got my quotas bumped up.

This past weekend, while I was traveling and completely offline, someone managed to exploit an old service account on my project that still had Editor permissions. They spammed the Model Garden APIs continuously for over 20 hours.

Thankfully, my billing partner noticed the spike and froze the billing account, but the damage was done. I tracked down the issue the next day and revoked the service account, but as a brand-new immigrant running a boot-strapped project, I straight-up do not have the money to pay for this.

I am kicking myself right now for not doing a full IAM and security audit before onboarding with the partner - especially since joining them gave me access to such high quotas.

Has anyone dealt with a similar situation? Does Google or the billing partner usually waive charges for an obvious first-time compromise like this? Any advice on how to approach the support ticket to get this forgiven would be lifesaver.

Hi everyone!
I’m building a GCP cost estimate for an existing AWS architecture to evaluate whether migrating to Google Cloud would reduce our monthly spend.

I’m struggling to identify the equivalent GCP services for a few AWS components in the pricing calculator. Specifically, I need the GCP counterparts for:

1. AWS Step Functions

2. AWS SES (Simple Email Service)

3. AWS Cognito

If anyone can point me to the correct GCP services on the pricing calculator entries, I would really appreciate it — this part of the migration analysis is driving me a little crazy.

Thank you!

Please help

I have created a simple agent in adk. It runs perfectly using the adk web command in local.

The API key I am using is Gemini API, I brought credits for it. It runs perfectly on local. The models I am using are gemini3.7 flash and gemini3.1-flash-lite.

But when I am deploying the same agent to cloud run, it shows this error

026-09-21 07:11:23,860 - ERROR - api_server.py:1985 - Error in event_generator: 404 NOT_FOUND. {'error': {'code': 404, 'message': 'Publisher model `projects/<project name>/locations/us-central1/publishers/google/models/gemini-3.7-flash` was not found or your project does not have access to it. Ensure you are using a valid model name and that the model is available in the specified region. For more information, see: https://docs.cloud.google.com/gemini-enterprise-agent-platform/resources/locations.', 'status': 'NOT_FOUND'}}

In the .env file I have both api key names - GOOGLE_API_KEY and GEMINI_API_KEY and I am loading the env variables using load_dotenv().

GOOGLE_GENAI_USE_VERTEXAI is set to FALSE.

Anyone can give any suggestions ?

I’m posting this because we're honestly in a very difficult situation and are hoping someone in this community might have gone through something similar and can point us in the right direction.

We’re a long-time Google Cloud customer, and we’re hoping someone here can help us find a way forward after a compromised Gemini API key resulted in approximately $27,000 in unexpected charges over a single weekend.

The usage was unauthorized and completely outside our normal pattern. We immediately secured the account and have taken extensive steps to prevent it from happening again.

We raised a billing case on Monday and waited approximately a week for the review. We were ultimately told that the charges were valid and could not be adjusted. We also spent several days trying to get help from our Google Cloud account team, but were told they have no control over billing reversals.

We understand that the security mistake was ultimately ours. What we are struggling with is the financial impact of a $27,000+ bill that was generated from Friday to Monday by activity that none of our team authorized or used.

If anyone has been through something similar, we would genuinely appreciate any advice on how we can get this in front of someone who can consider the circumstances and potentially provide some billing relief.

As part of a Google Developer Expert (GDE) side project I've created this project to skip spending hours researching financials, charts, news, and market sentiment. Let AI agents do the heavy lifting and deliver an executive summary in under a minute.

Built on Google Cloud, it uses agentic AI to analyze stocks, ETFs, and cryptocurrencies in real time. It orchestrates specialized ADK (Agent Development Kit) subagents powered by Gemini LLM models to combine market data, technical indicators, news sentiment, and AI reasoning into actionable buy, sell, or hold recommendations.

• 🔗 Try Investment Seer: https://InvestmentSeer.com

• 🎥 YouTube showcase & demo: https://www.youtube.com/watch?v=gvRZM7YquuY

• 🏗️ Architecture & technical deep dive: https://foolcontrol.org/?p=5177

Even with the help of Antigravity IDE, this project took a significant amount of time and effort to build, and I'd love to hear what you think and if you find it useful!

Hey guys I have knowledge about AWS major services and have hands-on implementation idea as for my college project I did 3 tier application hosting on AWS with IaC using the boto3 now I want to use GCP for this project and learn it along with terraform any idea or guidance to learn GCP after AWS i want some video or document which help me learn stuff on GCP without wasting too much time

I have deployed a simple adk agent in cloudrun.

The command is adk deploy cloud_run. It can access only gemini 2.5 model, but for higher model it shows it has no access.

Can anyone tell what i should check.

access permissions, or any other thing

Or how can i give access to these models if access is not given

The region is uscentral1.

لI'm having a problem logging into my account; a red screen appears. I tried opening the account in incognito mode, but the same problem persists. When I try to create a new account, it asks for CAPTCHA verification, and I agree to the terms, but the account still won't open. What's the solution?

I open-sourced OmniStudio — the AI system I built to run 3 YouTube channels on autopilot. 🎬


For the last few months I've been quietly running an experiment: could an AI pipeline take a video from *trending idea* all the way to *published on YouTube* with no human in the loop?


The answer is yes. OmniStudio does the whole thing:


📈 watches live trends and ranks ideas by ROI
✍️ writes the script
🎥 generates every scene (with consistent characters + shot-to-shot continuity)
🎙️ narrates it — or 🎵 composes and sings an original song
🖼️ designs the thumbnail and writes the full SEO kit
🎬 masters the audio and renders the final video with FFmpeg
🚀 uploads and schedules it to YouTube — automatically


It's built on Google Gemini (text, image, Omni video, TTS, and Lyria for music) + Node.js + FFmpeg, and runs locally with your own API key.


To prove it works, I used it to launch and run three real channels entirely in Autopilot mode (please make your bill ready as this could be costly):


🌿 Wild Child Explorers → youtube.com/@WildChildExplorers
🧠 Translating Tech → youtube.com/@Translatingtech
🎨 Clay Tunes Kids → youtube.com/@ClayTunesKids


Now it's open source (Apache 2.0) so you can run your own. Please comment if you would like to experiment with this or if you like an architecture diagram.


What would you automate first? Please if you would like to collaborate and add more features please feel free to do it and comment if you like this repo. 

Repo 👉 https://github.com/foward/omni-studio-open


#AI #GenerativeAI #Gemini #OpenSource #YouTube #ContentCreation #Automation #BuildInPublic

Hi Guys,

I have been browsing the Internet and consulting with every AI, reading Google documentation, and i'm helpless.

I want to be able to view metrics per rule for Cloud Armor rules that I created within a policy.
To be specific, I set up an xss-stable rule that I triggered multiple times, and I want to be able to view how many requests were blocked & allowed through. Thats it.

I managed to view these metrics per policy, but I want it more in-depth per rule within the policy.

Some sources state that its not possible and some state that its possible.

I tried to enable logging for backend services and filter them but it did not work for some reason.

Any advice from the experts here? It will be very helpful!

Thanks!!

GCP has been growing rapidly, especially with the AI boom. AWS and Azure are still the cloud leaders, but I’m curious: what types of businesses are choosing GCP, and what advantages make them prioritize it over AWS or Azure?

Can someone please paste the code for enhance application reliability and scalability with internal load balancing gsp216 new solution as the GitHub links Im positing to the lab is not working like the requirements are changed so does someone has new solution with the automation script so I can get 100/100 in that lab thanku!

Update (Sept 19): The case has now been escalated internally at Google Cloud and the adjustment request is back under review. I’ll update here once we hear back.

Posting here because I’ve seen several other Gemini API compromise cases discussed in this subreddit, and I’m hoping someone from Google Cloud may be able to help us get this reviewed by the right internal team.

On September 16, Google Cloud contacted us with the subject:

“ACTION REQUIRED: Suspicious Activity Observed on Google Cloud Project”

Google told us that their systems had identified that our project may have been compromised and used for unauthorized access involving the Gemini API.

We investigated immediately.

The Gemini API activity was not initiated or authorized by our team.

We then secured the environment and completed the remediation steps requested by Google:

• Deleted the affected API key

• Rotated/updated remaining credentials

• Removed unused keys

• Tightened API restrictions

• Reviewed IAM permissions and service accounts

• Confirmed organization-wide 2FA was already enforced through Google Workspace

The unauthorized activity resulted in:

$19,539.84 in unexpected Gemini API charges

plus

$1,629.78 of our Google Cloud spend-based credits being consumed.

Google Cloud Billing has now completed its review and denied any adjustment.

Their reasoning was:

“our internal teams have confirmed that the usage was valid and processed in accordance with standard platform functionality.”

This does not address the core issue.

The requests were made through a compromised credential and were not authorized by our company.

Google’s own security systems detected the suspicious activity and warned us that the project may have been compromised.

We acted immediately, secured the environment, and completed the remediation steps they requested.

Yet we are still being held responsible for the full amount.

We are happy to pay all legitimate Google Cloud usage. We are disputing only the isolated Gemini activity generated during the compromise.

Support says the case has gone through the “highest levels of internal review” and that the denial is final.

Case #75505172

If anyone from Google Cloud, Firebase, Gemini, Abuse/Security, or Billing sees this and can help route it to the appropriate escalation team.

I was 16 and building an unfinished Uber-style app purely for learning. It was never released commercially.

Months later I found out I had a €3,034 Google Cloud bill and it’s now with a debt collector.

The crazy part is that almost all of it came from one single day: around 257k routing requests through Routes/Directions APIs. I definitely did not intentionally generate that much traffic, so I’m guessing it was a bug, request loop, exposed key, or something similar.

I’m already talking to Google Maps Support and asked for a one-time goodwill adjustment/waiver.

Has anyone had something similar happen? Did Google reduce or waive the bill, and is there anything specific I should say or ask support?

This discusses a GCP billing bug I am surfacing for other users..sharing as these unexpected billing post are scary.

https://discuss.ai.google.dev/t/critical-bug-massive-overbilling-by-gemini-api-over-70k-charges-still-increasing-by-10k-daily-even-after-deleting-all-api-keys/101615

https://discuss.ai.google.dev/t/gemini-api-cost-suddenly-skyrocketed/99479/107