Google Cloud Technology Nuggets — September 1–15, 2022 Edition

Welcome to the September 1–15, 2022 edition of Google Cloud Technology Nuggets.

Register for Google Cloud Next ‘22

Google Cloud’s biggest event of the year is scheduled to be held on October 11–12th and it is unique with its global digital broadcast, featuring live keynotes from five locations across the globe — New York, Sunnyvale, Tokyo, Bengaluru, and Munich.

Check out the Google Cloud Next website for more details and register today. The blog post summarizes the event format, physical events happening across the world and more.

Containers and Kubernetes

If you have been using GKE, you are aware that Google manages the Kubernetes Control Plane. During troubleshooting, it is important that you have access to various control plane metrics that can help you understand the problem. These metrics could range from health of the API Server, Pod states and more. Keeping that in mind, Kubernetes Control Plane metrics are now available not just in the Cloud Console (as shown below) but also via Google Cloud Monitoring Metrics via which you can set up alerts and via 3rd party integrations as needed. Check out the blog post for more details.

In the weekly Cloud Wisdom series, that addresses questions that our customers ask us, the focus this week is on how to optimize your costs with containers. With the move from VMs to containers, it is important to understand several areas that you can look into to both optimize your move to App Modernization via Containers. It’s a great way to understand the various options that you have to run containers on Google Cloud and to learn about various innovations with Compute and Google Kubernetes Engine that help you with cost optimization. Check out the blog post for more details.

Storage and Data Analytics

Google Backup and DR is now available directly from the Google Cloud console. The service allows administrators to create backups for VMs on Compute Engine, VMware Engine or on-premises VMware, databases (such as SAP, MySQL and SQL Server), and file systems. . Check out the blog post for more details.

Datastream for BigQuery is now available in preview. It allows for a seamless replication from various database sources directly into BigQuery. These database sources could be AlloyDB for PostgreSQL, PostgreSQL, MySQL and Oracle. Check out the post for more details.

Data Governance in an organization helps to address key dimensions around data namely management, protection, discoverability and accountability. Check out the post that covers not just an understanding of these key concepts but various Google services that can help you achieve that. Its a solid checklist for you to bookmark in this area.

Ad Personalization is a critical use case for Google. This is powered due to the features provided by Google Bigtable. Check out this blog post that helps to map various features of Bigtable that make this possible.

Earlier in this newsletter, we saw Cloud Wisdom Weekly cover various ways to optimize your containerization costs. Another Cloud Wisdom Weekly published in this period, covered ways to optimize data management and analytics.

Identity and Security

PII (Personal Identifiable Information) data in Bigquery presents a couple of challenges: identifying it and ensuring that the right security controls are in place in terms of access to that data. Typical solutions address this in a manner that duplicates this data and then kicks off the process to identify it. What if you could do all of that within BigQuery itself. Check out a solution developed by Google Professional Services that does just that.

Machine Learning

How do you take your Machine Learning models from Prototype to Production. What are tools and services that a cloud provider provides that makes this a reality. In a series of video tutorials, take a look at the journey that shows how to build, train, scale, and deploy machine learning models on Google Cloud using Vertex AI. The list includes:

• Getting started with Notebooks for machine learning
• Storing data for machine learning
• Training custom models on Vertex AI
• How to get predictions from an ML model
• Tuning and scaling your ML models

Check out the blog post for more details.

DevOps

We are familiar with the concept of Continuous Integration (CI) and Continuous Delivery (CD). How about understanding how to build out a secure CI/CD pipeline with Google Cloud services. The blog post explains how to build one and covers various Google Cloud services like Cloud Build, Artifact Registry, Cloud Deploy, Binary Authorization, GKE, Cloud Pub/Sub and Cloud Functions.

Developers and Practitioners

Cloud Spanner trial instances are now available to all developers for a period of 90 days. The Spanner instance where users can create GoogleSQL or PostgreSQL-dialect databases, explore Spanner capabilities, and prototype an application to run on Spanner. How about having the instance installed with a guided tutorial that helps you to get started with Cloud Spanner. Check out the blog post for more details.

Check out the post that helps you through the sample instance, the demonstration application that is available and more.

If you enjoy using an IDE for your development, it’s interesting to see that you can now manage your Compute Engine instances from Cloud Code. Cloud Code is a plugin for popular IDEs like VS Code, Jetbrains IDEA and is also available in Cloud Shell.

The support for Compute Engine in Cloud Code includes viewing the VMs, connecting to the VMs via SSH, uploading files to the VMs, Viewing logs and more. Check out the blog post for more details. For more information on Cloud Code, check out the main documentation.

We have been covering the Databases on Google Cloud series for a while now in this newsletter. Part 6 of the series is out now and it’s an interesting step-by-step guide to predicting the success/failure of a movie. The guide covers creating a model using BigQuery ML and the same process by using Vertex AI AutoML with the same BigQuery data.

Let’s learn about GCP

Cloud is one of the fastest growing areas in which multiple job opportunities are opening up. But if you are from a traditional IT background, non-IT background, not having a degree or looking to change course from a different career to cloud, it seems that the odds are stacked against you. However, this should not deter you from pursuing your dream of working in the Cloud. This blog post looks at several such scenarios and presents a path to achieve that. You can also check out the full Cracking the Google Cloud Career playlist.

Looking to learn a new programming language? Did you know that Go Language is used in several of the most popular Cloud infrastructure projects like Kubernetes, Docker, Prometheus, etc. Check out this interesting article titled “Why I love Go” and get inspired to take your next step to learn Go. Begin with a Tour of Go, for a start.

The Cloud Digital Leader certification has been one of the most popular certifications in Google Cloud. If you would like to get certified, there is a no-cost Google Digital Leader training on Google Cloud Skills Boost program. Check out the blog post for more details.

Hackathons / Contests

There are a couple of contests with a great set of prizes up for grabs:

Google Cloud Fly Cup Challenge : This challenge is in a partnership with the Drone Racing League (DRL). Participants will be asked to combine DRL race data and Google Cloud Data Analytics Tools to build models and predict race outcomes. The event has just been launched and will be in 3 stages, going into Cloud Next ’22 and till the end of the year. Register now and read the blog post for more details. Grand Prize winners stand to win an all expenses-paid VIP trip to DRL’s final race in early 2023.

Google Maps Platform Hackathon: For Google Maps developers, build out a unique experience and stand to win one of several prizes, in a total of $24000 prize money. Check out the blog post for more details or visit the Devpost Hackathon site. Get inspired by the demo gallery.

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