Jump to Content
Google Cloud

The overwhelmed person’s guide to Google Cloud: week of May 30

June 4, 2024
Richard Seroter

Chief Evangelist, Google Cloud

A weekly curation of the most helpful blogs, exciting new features, and useful events coming out of Google Cloud.

Try Gemini 1.5 models

Google's most advanced multimodal models in Vertex AI

Try it

The content in this blog post was originally published last week as a members-only email to the Google Cloud Innovators community. To get this content directly in your inbox (not to mention lots of other benefits), sign up to be an Innovator today.

New and shiny

Three new things to know this week

  • Connect to third party source control systems with Developer Connect. This new service is GA and it launches with support for GitHub (.com, and Enterprise). This offers a secure way to integrate source code with Google services. Check out the Quickstart.
  • Ground your LLM in Google Search results. Gemini is amazing, and it can be even more useful when you connect it with the world’s knowledge. Now you can ground Gemini results with Google Search to get up-to-date information along with citations.
  • Store basically anything in the Artifact Registry. When you have application packages—think Maven, npm, or Docker—or operating system packages, Artifact Registry offers a useful, secure, centralized access point. This latest update supports “generic” packages that can be uploaded or downloaded.

Watch this


Watch live coding with Google Cloud databases. Mark and Aaron are back with season 2 of their live coding series where they do things for the first time, while you watch.

Community cuts

Every week I round up some of my favorite links from builders around the Google Cloud-iverse. Want to see your blog or video in the next issue? Drop Richard a line!

  • Self-managed or managed infrastructure? Yahoo! runs a test. The team at Yahoo! wanted to compare the cost of running Apache Flink on GKE versus Google Cloud Dataflow. They offered some useful results, and valid caveats.
  • Notebooks are not enough. Benjamin claims that “doing AI’ is more than just throwing out some Jupyter notebooks. He shows us how to create a proper ML pipeline using Vertex AI.
  • Run Grafana yourself on GCE. You have a LOT of choices for observability and monitoring. In this post, Vishal walks through the steps of setting up your own Grafana instance on Google Compute Engine VMs.

Learn and grow

Three ways to build your cloud muscles this week
  • Use Colab or Vertex AI to try this notebook that shows off doc summarization. See Gemini in action by clicking through this notebook and seeing its powerful summarization features.
  • Build better with AI-assisted tooling. Join this online session on June 5th or June 6th to learn how Gemini Code Assist revolutionizes development with AI-powered coding advice and interactive assistance, making application development more efficient and impactful.
  • Learn how to create a multi-tier app with a global topology. You don’t always need to deploy globally, but when you do, it’s handy to have a vetted reference architecture. This new one looks at how to use Compute Engine and Spanner to lay out a widely available system.
  • Thinking of autoscaling your GKE pods? Here are the economical considerations. I like assessments such as this which show the benefits and tradeoffs of a technology choice. In this case, the writer explores the cost and performance implications of horizontal pod autoscaling.
  • Comparing the price-performance of self-managed PostgreSQL versus AlloyDB. You can definitely run databases yourself, but this post makes a good case for the financial and performance reasons to consider a managed service like AlloyDB.

One more thing

Firebase got supercharged at Google I/O. Steren shares some of his favorite updates to the Firebase service.

Become an Innovator to stay up-to-date on the latest news, product updates, events, and learning opportunities with Google Cloud.

Posted in