I've seen one too many stories on Reddit and Hacker News about AI agents running wild and generating massive cloud bills. It got me thinking about how we can prevent this from happening on Google Cloud.

I put together an architecture covering spending caps, IAM, quotas, and automated kill switches to help keep runaway AI costs under control.

Here's the write-up: https://medium.com/@rasvihostings/stop-your-ai-agents-from-burning-100k-overnight-8ab7f3fd0045

Curious to hear how others are tackling this problem. What guardrails are you using?

Anyone having Idea about gcp and gcp resources and practicing the gcp labs . Please let me know that I got an opportunity so ...

[ Removed by Reddit on account of violating the content policy. ]

A few people here have asked what changed in the Professional ML Engineer guide after the June 1 update. I had to go through it line by line for a project anyway, so here's my summary. This is all from the official guide PDF. I haven't sat the new exam.

Structure

• Still 6 sections, same order. Approximate weights: low-code AI ~13%, collaborating on data and models ~16%, scaling prototypes into models ~21%, serving and scaling ~20%, automating pipelines ~18%, monitoring ~13%. (Yes that's 101%, blame Google's rounding.)
• Vs the previous guide: pipelines went from ~22% to ~18%, scaling prototypes from ~18% to ~21%, collaborating from ~14% to ~16%. Google's old PDF link now serves the new guide, but there's an archived copy of the old one if you want to compare.
• 16 subsections went down to 14. The standalone AutoML subsection is gone (AutoML training now sits in 1.1), and so is the standalone metadata one (artifact, version and lineage tracking is in 2.3 now).

Naming

• Vertex AI is now Gemini Enterprise Agent Platform everywhere in the guide. For exam purposes it's mostly a rename: Vertex AI Pipelines is now Agent Platform Pipelines, Vertex AI Prediction is now Agent Platform Inference. I wouldn't find-and-replace your notes blindly though, a few things moved around.

New or more explicit

• 1.1: AutoML training on Agent Platform, and fine-tuning Gemini from BigQuery
• 1.2: evaluating and picking models from Model Garden, tuning Gemini / Imagen / Veo, cost vs latency vs availability for Gemini apps
• 2.1: picking a preprocessing tool by data size and complexity (SQL vs Spark vs in-memory Python)
• 2.3: predictive and gen AI evaluation are named together now, and LLM-as-a-judge is called out explicitly
• 3.1: choosing a model type (ARIMA vs DNN vs LLM) under cost, latency and scale constraints
• 4.1: prebuilt vs custom containers, versioning in Model Registry, canary rollouts next to A/B, pre- and postprocessing at inference time
• 5.1: Ray on Agent Platform gets named next to Agent Platform Pipelines (Managed Service for Apache Airflow is just Cloud Composer's new name, and Composer was already there)
• 5.2: CI/CD/CT spelled out (CT = continuous training)
• 6.1: LLM security. Data exfiltration, malicious prompts, sensitive data in prompts, Model Armor and safety filters
• 6.2: training-serving skew, data drift, concept drift and feature attribution drift grouped together, plus monitoring gen AI solutions
• The intro now mentions prompt/context engineering

No longer named explicitly (doesn't mean they can't show up)

• The Agent Builder RAG objective, TFX / Kubeflow DSL pipeline design, hosting MLflow, Jenkins, Reduction Server / Horovod, TensorBoard, and edge as a training hardware example
• Framework examples are PyTorch / scikit-learn / JAX now, a lot less TensorFlow-heavy

My take: it's still an ML engineering / MLOps exam, just with gen AI added on top. I wouldn't call it a "build agents" exam. If your prep material is from before June and leans on TFX, Kubeflow DSL or TensorFlow details, I'd shift some of that time to picking and tuning models in Model Garden (Gemini / Imagen / Veo), LLM-as-a-judge style evaluation, and LLM security (Model Armor).

Official guide: exam guide PDF

Disclosure: I build a PMLE practice site, which is why I was reading the guide this closely. There's a free diagnostic that scores you by section. No account needed. The 5-question quick check takes about 5 min and samples the five biggest sections; the full 20 takes about 20 min and covers all 6. Not affiliated with Google. If I got anything wrong above, tell me and I'll edit.

Bug bounty while it's new: if you find a question with a wrong answer (seeing all the answers needs a free account), comment here or DM me. First person to report each one gets a free 90-day pass once I've confirmed and fixed it.

I’m a cofounder of an early-stage startup. We recently had a Vertex AI job run overnight that ended up costing us around C$75K in 14 hours.

Our startup credits ran out during the job. The first charge we saw was around C$8K on our credit card, and we immediately shut everything down. But due to delayed billing data, the charges kept showing up hours and even days later. By the time everything propagated, we were left with a C$71K bill that we simply can’t afford.

We requested a one-time adjustment, but Google Cloud Billing Support rejected it. Our account rep also tried helping but got pushback.

Has anyone been through something similar and managed to get a refund or adjustment? Would really appreciate any advice on who to reach out to or how to escalate this further.

Edit: I agree that this was a legitimate bill. But if anyone understands the startup economics and the situation of affordability and knows if google can help in that regard, please lmk!!!

Just passed the GCP PMLE Exam. Took me about a month and some change to prepare for it. GCP Study Hub is a life saver! It's the only resource I used with ChatGPT to explain answers. The practice exams that they provide are more than sufficient and the wording for questions were extremely similar. Highly recommend it for anyone trying to obtain a cert from google.

I created many RAG scripts using SQL in BigQuery, but it's time to include git and code to organize my work. I know Python and I use Agent Development Kit to create my AI agents applications so I want a tool just for create RAG. I searched about it and I found LangChain. I wanted to use LangChain because is more popular and easier to get support but looks like they are including LangGraph together and forcing langchain to became a agent builder tool. I don't want one more agent tool because ADK is my specialty. So I found LlamaIndex and I liked what I saw because it is exclusively for RAG. But looks like LlamaIndex is not popular, there are not too many content... I don't know. What would you use? Is there a better tool?

Recently google is conducting a competition in google skills(google cloud). In that I entered wrong referral code instead of my college's . Sorry for my english. But I did every course and exercises in that gmail. Gdg campus organizer from my college is asking me to create new acc and start from scratch if I wanna participate. I am mainly participating because of merch..💔

This referral code helps tracking the progress. I completed it in a day. Only to realize I entered a wrong referral code

New to gcp. I had a couple of python-flask apps that I made for personal use and had deployed them on render for free. But recently, they got suspended and now I am looking for good alternatives. Now GCP says they have free tier but the credits last for 90 days. But gemini says after the 90 days, it'll still remain free if used within specified limits. Furthermore, I checked gcp and found out I already had a free tier billing account (which I might have created accidentally while trying to explore gcp in past. I tried making a new billing account and it asks for 15k INR. Now I am too confused. Can somebody explain me if I can still use free tier? Why do I need to pay 15k for a new billing account?

Any idea about the OTE and RSU package Google can offer for a Level 6 role in Germany or Switzerland? There is not much public data about their compensation levels in those countries.

I'm planning to move a mission-critical, latency-sensitive service there from Heroku, which has had recurring router outages recently - requests failing to reach our app even though the dynos themselves were healthy. The service is written in Go and handles ~7 req/s on average, with bursts up to ~150 req/s. Has anyone had issues with Cloud Run's routing layer, especially lately? Also, with AI-driven cyberattacks on the rise, do you rely on Cloud Armor or keep something like Cloudflare in front?

I'm planning to move a mission-critical, latency-sensitive service there from Heroku, which has had recurring router outages recently - requests failing to reach our app even though the dynos themselves were healthy. The service is written in Go and handles ~7 req/s on average, with bursts up to ~150 req/s. Has anyone had issues with Cloud Run's routing layer, especially lately? Also, with AI-driven cyberattacks on the rise, do you rely on Cloud Armor or keep something like Cloudflare in front?

Every year around Sept-Dec Google sponsors DevFest events organized by local communities. These are events run by non-Google employees who volunteer their time because they're interested in tech, meeting people, and helping their community. It's a great way to meet people interested in tech, hear some cool talks, and maybe even get some swag/prizes. Events tend to be free or low cost compared to professionally run conferences, and you can always contact the organizers to volunteer in exchange for a free ticket.

Here's a link to the page where you can find all the events:

https://developers.google.com/community/devfest#find-a-gdg-community

Disclaimer: I'm helping plan the event in Los Angeles

We are BequalifyAI team, a startup building affordable AI analytics. We train our solutions on Google’s foundation models, and one of our primary strategic goals was securing the Google for Startups Cloud Program grant for AI startups. We operate in Ukraine (only the first photo is in Ukrainian).

One morning, our owner account was blocked. The reason? The algorithm falsely flagged us as a "bot". We are a human-operated startup.

We went through all standard recovery procedures and submitted formal appeals. They were rejected i think even without human review.

Due to a blocked owner account, our GCP project is suspended. And it cannot be restored until we restore access to the email.

Support officially warned us that creating a new Google Account or GCP project for the same business is considered a "circumvention" of their policies. If we try to rebuild, the new account will likely be suspended.

We are completly stuck and data that was on bucket and database is frozen.

1. Photo. Our owner account block.
2. Photo. Сreating a new one is not recommended.
3. Photo. Support operate under strict guidelines and can offer no further resolution for GCP project.

If you are building your AI startup on GCP, be aware that a single flag can instantly lock your data and ban your company from the ecosystem forever, with zero human oversight.

(Note: English isn't my first language, so I used AI to help write this post clearly, but the situation below is the result of a grueling week-long email chain with Google Support)

Has anyone else navigated this GCP infinite loop?

It's been 2 weeks since the beta ended. It should be any day now, right?

My Firebase scheduled function suddenly gets 403 Forbidden when fetching Reddit RSS feeds (https://www.reddit.com/r/{subreddit}/.rss).

I've tried setting a Chrome User-Agent, but it still fails. The same feed works locally.

Is Reddit blocking Google Cloud/Firebase IPs? Has anyone found a quick workaround that doesn't require Reddit API approval?

Update: As quick fix I am using a proxy server.

Hi all,

I'm in the TPU Builders Program and have been trying to get a ct6e-standard-4t flex-start VM for a few days now, with no luck.

- My Quotas are clean

- I swept all zones with full-length (2h) --request-valid-for-duration requests. Every single attempt returned ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS / reason: stockout, either instantly or after sitting PENDING for the full window.

- I ran a loop cycling through all zones every couple of minutes for 90+ minutes straight.

Has anyone else run into this recently, or gotten v6e flex-start to actually succeed in the last week or two? Any tips on timing, zones, or anything else I might be missing would be really appreciated.

Thanks!

My Google Cloud project got suspended because its billing account was suspended over an unpaid balance (~$380) from a different project. My project itself had $0 charges.

When I try to change the project to a new billing account, I get “Unable to change billing account. Complete the Account Verification Form.” I’ve submitted the form and an appeal and contacted billing support. The only reply said they handle reinstatement only.

Has anyone been through this? How long did reinstatement take, and which support channel finally got a response? Is there a way to move a project off a suspended billing account without paying the other project’s balance?

Thanks.

Background

I work with big data for a living and enjoy tinkering with a homelab. I do believe that homelabbing as a hobby was super helpful for understanding a few items from the exam. I also completed the Digital Leader and ACE exams before taking the PCA. I found that taking exams in that order was really helpful for creating a good foundation for the PCA.

Study Method

I took a lot of mock exams from a few different courses, I don't have an exam or course I'd recommend. Just pick one course that looks good to you and stick with it. I would suggest doing as many mock exam questions as you can. For me, this was about 20 questions a day, maybe less if I needed to focus on learning a new topic. After every question, review what you got wrong and explore any new key terms or topics of interest. Researching random topics helps to keep the studying from becoming boring and also helps your overall knowledge grow. Take notes on keywords and anything of interest that catches your eye.

All my notes eventually became a Web App that I personalized for my own tastes with the help of Claude Code. I focused a lot on terminology and word association. For example if you see "global" and "relational" then you should start thinking "Spanner" is a likely answer choice. I also needed visuals for networking and security so I included a section for these as well. To be clear, the web app does not contain any mock exam study questions and is not an exam dump. It's a quick reference guide that worked well for my study methods.

Observations

Maybe I got lucky with my exam version but the case studies on my exam didn't require any prior knowledge or reading of the case studies. I did review them a few times while studying but nothing was memorized. During the exam I found that the questions held all the information needed to pick the correct answer.

Exam Advice

• In options for the exam, on the left side of the screen enable both "notepad" and "strikeout." It's super helpful being able to remove answer choices that you know are not the correct answer. I minimized the notepad to only hold a few words. Any keyword in the question I thought useful I wrote down. I then used this as a main reference to selecting answer choices instead of rereading the question multiple times.
• Keep an eye on the clock, and keep questions to a time limit, if you're over time (like 1.5 minutes per question) then flag the question and move on.
• Flag any question you don't understand, but select an answer choice and strikeout any answer you know are not the answer before moving on. Use the notepad to leave a quick note to yourself to quickly say what this question is asking for. If you have time at the end of the exam then come back to the flagged questions.

In order to prepare for the Google Cloud Generative AI Leader (GAIL) exam I built the "long read" exam guide book with Claude Code. I passed the exam today and decided to share that book free on GitHub with whoever is interested -

https://github.com/vkorost/google-certified-ai-leader-guide

The GitHub project has the details about how that book was built.

I will just mention a few things here as a quick recap -

1. The ultimate sources of truth were the official exam guide, the official study guide and the official Google Cloud documentation.
2. However the exam requirements mention a few things not covered in the Google Cloud docs, because some of the things the exam want you to know is not about Google Cloud products at all, but IMO rather about *leading AI adoption the way Google understands it* (prompt engineering, implementation steps, responsible AI), so Google's own non-product writing was used to fill in the gaps (cited with URLs in the book's endnotes).
3. Then subtitles from a few dozen YouTube videos where people talk about the exam were gathered and used for clues wrt what areas had to be covered in the book, so that there would be no surprises later. None of that info was used as a source of truth, but rather as a list of things to look up in the official docs first.
4. The guide is not built by the exam sections, but rather in the order the decisions arrive: what the technology is, what you are choosing between, what Google sells, how to make the output better, and how to lead it. IMO that way the book reads more naturally.

for applying to the gcp for startups, i received a billing id, and the billing id while filling the startup application says is not active and i need to put in Rs. 1000 (India) for it to be active. Am i doing something wrong or is this standard procedure?

In network tier documentation page, it says regional external ipv6 is supported in preview. But when i create a custom vpc so i can assign an ULA ipv6 block, thus giving me ability to assign ipv6 address to my compute instance, the standard network option is still grayed out. How do i create a compute instance with ipv6 address in standard network tier? Thanks.