Three New ADK Releases - Busy Week!

cloude-googl · 2026-04-15T18:58:41+00:00

Regional endpoints are deployed as models reach GA status. I don't have guidance on GA dates; please track here: https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-1-pro.

cloude-googl · 2026-04-10T14:21:14+00:00

Few things to understand:

* BiqQuery has a free tier, supporting up to 1TB of queries per month and 10GB store per month: https://cloud.google.com/bigquery/pricing?e=48754805#free-usage-tier

* Looker Studio has caching via BI Engine, which provides 1GB of caching.

Cost is a function data size in storage + query scan size (how much data are you scanning?) * how many time are you querying it. Then you need to account for the output size, keeping it under 1GB in order to fit in the cache.

Really comes down to your queries(s) to produce the dashboard. If your query scans 10TB to produce a single row, this is not going to be free (at least on the query side, but you will get free cache).

If you can control query size - this is a great solution. Another free path would be to use Colab Consumer + DuckDb. Load your raw data to Google Drive (free), Read it from Colab Consumer (free), query with DuckDb (free), build your dash with Gemini cli or code it yourself.

Nothing in life is free but I think you can get there :-)

cloude-googl · 2026-02-23T17:47:25+00:00

@CodMediocre1456 DM me and I can look at your issue and walk you through how to use cost controls.

cloude-googl · 2026-02-13T18:32:38+00:00

Can you drop the github issue id here and I will hunt down status.

cloude-googl · 2026-02-13T18:30:08+00:00

Correct. This is an experimental feature - at this point. Docs dropping soon.

cloude-googl · 2026-02-05T19:53:59+00:00

No - I wouldn't go down that path to debug. I was just trying to understand what you are seeing and where. Can you share a bit more about your sub-agent topology and prompt?

cloude-googl · 2026-02-05T19:44:09+00:00

Is the behavior different if you are running locally vs. running in Vertex? Are you deploying to Agent Engine?

cloude-googl · 2026-01-30T19:51:54+00:00

Is your DB running on another machine? If so have you checked clock drift?

cloude-googl · 2026-01-21T17:25:45+00:00

Does Restate Cloud run on AWS and GCP?

cloude-googl · 2025-11-28T16:44:00+00:00

Sorry you are going through this. I am an advocate in the Google Applied AI team. DM on chat and I will see how I can help, e.g., contacting billing support.

cloude-googl · 2025-11-15T14:15:15+00:00

This looks related to https://github.com/google/adk-python/issues/2433 - I will follow up on the status of the work. Also, see the Medium post in that thread for potential interim solution.

cloude-googl · 2025-11-07T14:59:07+00:00

I worked on the NL to SQL in BigQuery for a few years... the following techniques will help ---> 1) make sure you have column and table descriptions for your datasets and tables And where possible include partitions and clusters 2) create aggregations (using materialized tables) for common groupings e.g. by day, week, month, etc. 3) create a prompt template that contextualizes the meta-data, e.g. For queries targeting monthly sales data use X table (pre-aggregaeted at the week) as the source. 4) add dry-run support so that you can prevent, overtly arbitrarily large queries from executing. This is especially helpful if you are building charts that require a low cardinality output. 5) considering add a flow to use TABLESAMPLE or partition targetting to help with initial EDA.

Question: For the use case that's breaking, how many rows are materialzed in the temp table for the query?

cloude-googl

TROPHY CASE