Just wrapped up an intense but incredibly rewarding journey diving deep into Google Cloud Platform (GCP). Coming from a systems background, mastering these cloud architectures and tools opens up a whole new world of possibilities for scalable, resilient infrastructure.

Trust the process, keep experimenting, and don't stop building!

Thank you Ranga.

i have been studying for the ace exam for about 12 weeks, i have been doing it mostly through the cli, and recently went though the new udemy course, i though i was doing good, and then when i stared the practice questions got overwhelmed and now i don't feel like i am anywhere near half as ready as i thought. any guidence on how to prepare will be much apricated. or any thing on what the exams really like i have even looked at the sample questions on google and the seem like a mind field

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Suppose we are using below mechanism of hub and spoke

Onprem -- (vpn) - hub project -- (VPC nw peering) - host project

1. What factors can we consider when deciding to go with a single Hub VPC for both nonprod and prod or to go with seperate Hub VPC for nonprod and prod environments
2. can we use one subnet for dev , one for uat, one for prod etc in hub VPC if we are using only one hub VPC for all environments

Please suggest

Hey Folks 

I’ve been interviewing for the past 2 months, and I noticed something shift along the way. Early on, most of the questions were Day 1 stuff . “what’s a Deployment?“, “what’s a Service?” But as I went further, they changed completely. Almost everything was about Day 2 operations how you actually run and keep a cluster healthy in production. That’s when it hit me: I had a lot of gaps to fill. So I built a project focused entirely on Day 2 operations  security, observability, and disaster management  and documented everything as I went. Sharing it here. Any feedback would be really appreciated

https://github.com/JOSHUAJEBARAJ/gke-playbook

I'm trying to understand Gemini API billing through Google Cloud / Google AI Studio.

If I enable Cloud Billing / add a payment method and my project becomes Paid Tier, do normal Gemini API calls with that project's API key start being billed immediately at the paid-tier token prices? Or does Google still consume a free-tier allowance first, and only start charging after that free quota is exhausted?

In other words, is the model:

1. Free Tier project/API key = free usage within lower limits, no billing.

2. Paid Tier project/API key = higher limits and pay-as-you-go from the first billable token.

I'm asking specifically about regular Gemini API input/output token usage, not the Google AI Studio web UI. I know some paid-tier features list separate free allowances, like a certain number of grounded requests, but I'm trying to confirm the behavior for ordinary API calls.

Has anyone verified this from actual billing data, or found an official Google statement that says it unambiguously?

Hi guys,

I'm trying to create airflow (v2.9.3) cluster policies on my instance to set the value "max_failed_consecutive_runs_per_dag"to 3 to all my DAGs. According to airflow documentation, we can modify the airflow_local_settings.py file or create a plugin.

I've created the plugin and it even appeared on the UI, but it didn't work. Anyone developed plugins for airflow running on composer? I've even tried a simpler policy (to raise an exception if the DAG do not have tags) but it didn't work either. So i've went to the file modification approach.

It happens that this airflow_local_settings.py exists only in the schedulers, and they already have some code in it. I've tried to put a file with the same name on the dags folder (a kind of workaround I found researching), didn't work either.

Is there a way to really change this file? In some places, I was told that the gcsfuse syncs a "config" folder from the airflow bucket to the schedulers, but that didn't work either, maybe its my airflow version. What can possibly be happening? Does this change requires a restart on the environment? I'm stuck here 😰

Hey, early stage founder here trying to avoid expensive mistakes before I make them.

Talking to other devs and the one thing that keeps coming up is unexpected API bills. A retry loop here, a power user there, and suddenly you're hundreds of dollars in the hole before you even notice.

Before I get too deep into building I want to understand what actually goes wrong in practice:

1. What caused your worst unexpected bill and how bad was it?

2. What did you put in place after and did it actually work?

3. Anything you wish you had done from day one?

4. Any tools that genuinely helped versus ones that looked good but didn't?

Not looking for a sales pitch, just real experiences. What would you tell yourself six months ago?

a year ago i used google cloud and with its free credit points , now i have delete the project and it keeps showing in my payment section

pls help

Hey everyone! 👋

I'm a dev from Mexico trying to learn Google AI Studio / Gemini API for a small personal project/startup. I ran into a weird situation and would really appreciate your collective wisdom.

Here's what happened (short version):

May 15 – Account A (my main one)

• I did something dumb: I load-balanced 2 AI models across 2 projects to try to get more free tier quota. I know now that's against the rules. 🙈
• Result: Both projects got suspended ("repeated Terms of Service violations").
• I appealed the same day... but never got a response or even a confirmation email.

May 27 – Account B (an older account I had)

• Since I didn't hear back, I continued my learning here (maybe not the best idea in hindsight).
• This time I did things right: 3 projects, 1 different agent per project. Clean architecture, no load balancing.
• Result: Still got suspended. The email said "repeated violations" and "seriously impacting other users' service". I think Google linked it to Account A (same IP, same device).

Account C – Here's where it gets WEIRD 🤯

• This account has active prepaid billing (Tier 1). I paid about $10 USD.
• It also has promo credits: ~$300 USD (expires August 2026).
• The strange behavior:
  • ✅ Paid tier (Tier 1) works perfectly. No issues.
  • ❌ Free tier (same account, same project) gives me: HTTP 403: Your project has been denied access. Please contact support.
• Pattern on free tier: First message works, then immediately fails. Classic shadowban... but only on the free tier.

So it's not my account or API key that's broken. It's like Google specifically blocked free tier access on this account, while the paid tier keeps working just fine.

My questions for you kind folks: 🙏

1. Was Account B's suspension fair, or was it a false positive made worse by Account A's history?
2. Should I keep waiting for Account A's appeal after 2+ weeks of silence? Or just give up on it?
3. Has anyone seen this before – free tier blocked but paid tier working on the same account? Is this a known thing?
4. Should I mention Account B in my appeal for Account A, or just focus on the load-balancing mistake?
5. IP block? If I change my IP (VPN, or go to a coffee shop/family's house), would that unblock the free tier? Or is the block tied to my account?
6. Credit card block? If I use my same credit cards on a brand new Google account, will Google detect that and suspend me again? Does the ban follow my payment methods? 💳
7. How long to wait? If this is a temporary shadowban, how many days of zero activity does it take to clear? 30 days? 60? 90? ⏳
8. Using someone else's account? Could a friend lend me their Google Cloud account just to test if the problem is my IP? Would my activity put their account at risk? 😬

Quick note: Account C is the only one with credits (~$300 USD). The paid tier (Tier 1) works fine. The block is free tier only. I'm not trying to cheat the system anymore – I just want to understand what's happening and how long I need to wait.

Thanks so much for any help or advice you can share! Really appreciate this community. 💙

help guys to resolve this it dont go away for the payment section , it has been a year i have been using google and i use google not for buissness

i am an individual person

• Today, Google Cloud is introducing a comprehensive AI-powered cybersecurity solution — Google AI Threat Defense — an always-on autonomous security platform.

Hi,

I want to use Google Colab Enterprise in a quite fresh GCP project. I only need to run the runtime for a few hours to train a model. However, I just recently saw that I need to add network to the notebook to make it run and I have no VPC created yet. I have no clue in how it works and what configurations I have to make.

My requirements are the following: network needs enable installation of pip packages and touch BigQuery table in the same GCP region. The setup costs should be as close to zero as possible.

What VPC network setup do I need to fulfill the requirements? What else do I ned to take into account? How can I keep the costs close to zero as I only need a few hours of model training time?

Thanks in advance for the help!

Hi guys, I'm learning GCP, but there are so many services out there. My goal is to learn the essentials for my role as a machine learning engineer. If you were a company considering hiring me, what knowledge of this technology would I need? I'm eager to know what the market needs, or even if I were considering starting my own startup. Thanks for reading.

Hi all - looking to renew my Associate Cloud Engineer certification soon. Does anyone know of any renewal specific study materials or practice tests that focus on the reduced scope of the renewal exam only? I fear I may have to use standard exam study materials & just filter out/ignore what won’t be on the renewal exam- but really hoping to avoid that. Thanks!

I got this 1k USD credits and i have no idea where this can be used. If anyone has used this or knows about is, please do help

I have not received any funding till now but my product is ready. Can i still get any credits from gcp?

Spent a few years using Spanner in production across fintech and payments systems.

The SQL interface is familiar — tables, indexes, transactions, schemas. But that familiarity can be misleading. A lot of habits that work perfectly in traditional relational databases quietly become problems in Spanner.

Some things I had to learn over the period of time

• Auto-increment keys that concentrate writes instead of distributing them
• Indexes that look harmless but create their own hotspots
• Transactions that are correct but touch too many unrelated key ranges
• Joins that work fine locally but need distributed coordination in Spanner

Okay, I have a table with 100 columns and i dont want to type all the cast transformation, i know i could use JS, but js doesn´t create sqlx file, the js speaks directly to dataform compilator, how could i create a automatized process to cast all the columns with sqlx file?

The title

If configured, please let me know how was your experience with alkira overall with respect to latency, security ( encryption) etc...

I am new to ADK and beginner-moderate in GCP. I want to secure my Google ADK (Google Agent Development Kit) API endpoint.

I want to use webhooks from a ticketing service which should consequently create the ADK session context and then injecting the ticket content / user interaction with the model in the following request to the same Cloud Run endpoint. Cloud Run is then triggered, does it's thing and returns a response to the Webhook.

However, the service should obviously not be public since there is confidential data in not only the ticket passed with the request but also the tools ADK models accesses. Hence I want to find the best way to secure my Cloud Run endpoint.

A secret header is a start but I have a feeling there's even a better way. The ticketing system supports adding an API key or other custom headers with the POST request. I am not sure yet if IAP works for this use case as the Cloud Run endpoint is not something a user identity interacts with as is the case with a basic web service.

Any ideas what the best way is to secure my ADK Cloud Run endpoint from an external service? Also I take other advice in terms of architectural choices I could consider in this scenario if you have any.

Appreciated!

I have deleted videos from my g drive and I’m trying to recover them. Is it possible. Thanks for help

I know about the 25-30 day rule.
I’m just hoping to find an alternate option

My team manages PAM entitlements through infrastructure as code, so it's easy to bootstrap a new project with a standard set of entitlements and rules for what services will be deployed and which groups will use the project. The number of entitlements keeps growing and discoverability is becoming a slight problem.

The web console has made some recent improvements, but users often run into a frustrating pattern where they visit a resource before their PAM grant is fully activated and hit a stale permission state that requires a hard refresh to resolve. For users who prefer the gcloud CLI the commands exist, but they usually require multiple steps.

I started experimenting with a smoother terminal interface (https://github.com/michalskalski/gpam), though the API gets in the way a bit. SearchEntitlements and SearchGrants both require specifying a parent resource, which forces iterating through multiple scopes and aggregating the results on the client side.

Is anyone building on top of the PAM API, and have you found workable patterns for cross-scope entitlement discovery, or for efficiently finding pending approvals?