Google Cloud Platform

Cloud Spanner was designed to process cross-region transactions with strong consistency to simplify app development.

Since 2007, App Engine has made building and deploying production scale applications for the web easy.

This video walks you through how to upload a file and share it on Google Cloud Storage.

JAX is an open-source Python library that brings together Autograd and XLA, facilitating high-performance machine learning research.

Code for this episode → goo.gle/3eSifpa Cloud SQL documentation → goo.gle/3eSifpa Cloud Run documentation → goo.gle/3cMPsj3 Cloud Run is serverless, which means you don’t

HashiCorp Vault is a popular tool for secrets management, but can it be used with Kubernetes? The first part of this interactive demo-driven talk showcases how to run Vault as a service on Kubernetes.

Do you have a clear understanding of the difference between all of Google's load balancing product suite?

Documentation → goo.gle/3zWiKFH Feature engineering involves transforming raw data into high quality input signals for ML models, but what if there was a simpler way?

Learn more about AlloyDB, the new and powerful relational database service from Google Cloud.

Data Connector for Salesforce, a Google Sheet add-on, makes it easy to import, analyze, edit, and update your organization’s data from Salesforce.

Want to know how to save and share your queries in BigQuery hassle-free?

Firebase is the fastest way to build a scalable app from scratch, or to add functionality to your existing mobile apps.

What is Cloud Run? How does it help you build apps?

Perform fast, insightful analysis on Big Data.

Joe Kava, VP Google’s global data centers, talks about what makes our data center performance best in class.

In this episode of Google Cloud Migration 101, Priyanka Vergadia and Kyle Moschetto show you what sorts of applications are best to start your Cloud migration with.

Formerly known as Stackdriver, Google Cloud Operations Suite is a platform where you can monitor, troubleshoot, and improve application performance on your Google Cloud environment.

Jenkins is one of the most popular CI systems in the world. It’s flexibility and ecosystem allow it to be used for almost any task.

App Maker is G Suite's low-code app development tool that lets developers quickly build and deploy custom apps tailored to their company's needs.

Experiment with pipeline samples→ goo.gle/2QuyMSO Want to learn how to create an ML application from Kubeflow Pipelines?

Google provides infrastructure, services, and APIs for you to create your own machine learning models. They also have pretrained machine learning APIs that you can use in your applications today.

In this episode of AI Adventures, Yufeng Guo introduces the TPU v2 and v3. Specifically, he goes over their architecture, how they work, and how Google Developers can get their hands on these TPUs.

There are many different ways to think about running code these days. And the tradeoffs are different when you're working with existing systems as opposed to designing an entirely new system.

Google App Engine is a platform for building web and mobile apps that scale automatically, serve securely, and require almost no ongoing operations support.

Introduction to Vertex AI → bit.ly/Vertex_AI Train a Model on Vertex AI → bit.ly/40q5yXA Train and Use your own Models → bit.ly/42SWUm4 Are you interested in leveraging

With the rise of Large Language Models, search engines are rapidly evolving with the "semantic search" capability.

Google Cloud Skills Boost → goo.gle/3OVQ20t Kubernetes the Hard Way → goo.gle/3868mmQ Cloud Resume Challenge → goo.gle/3MUBhch Welcome to the first episode of Cracking The

Have you always wanted to build an IoT device and connect it to the Cloud? Feeling intimidated by the number of moving parts involved in making that happen?

Machine learning and transfer learning is the key to getting off the ground — from zero to production.

What if there was an AI tool that allowed manufactures the ability to reduce the cost of human operation, incorporate active learning for ML models, and provide quantitative metrics for investment