Our previous article provided tools and techniques to transform your productionalization process and make it ready for Cloud workloads. In this post, we will cover technical examples of GCP controls and how it can help your organization maintain your security and compliance posture in GCP. In comparison to on-prem infrastructure, GCP is a highly integrated […]

To help our customers on their path to success with Google Cloud, we published the Google Cloud Architecture Framework – a set of canonical best practices for building and operating workloads that are secure, efficient, resilient, high performing, and cost effective.  Today, we’re diving deeper into the Architecture Framework System Design pillar, including the four […]

Over the past year, serverless application development has seen tremendous interest.  The number of opportunities that show up on job boards showcase how critical this skill has become. It’s not surprising that at Google, we have seen the use of Serverless products increase by 4X over the past year. Particularly, as developers have moved away […]

For many of those building in the cloud, speed and security of deployments are amongst their top priorities. At times these goals can seem at odds with each other, especially if security guidance is distributed, written more as reference than opinion, and lacking in tooling for actual implementation in your environment. But they don’t have […]

In this blog post I describe the ‘Edge’ profile for Anthos on bare metal. I compare this new option against the default profile. I also introduced the recently published “Rolling out clusters on the edge at scale with Anthos on bare metal” guide that walks you through the steps to install Anthos on bare metal […]

Organizations that are modernizing with the cloud are increasingly looking for ways to simplify and automate container orchestration with high levels of security, reliability and scalability. GKE Autopilot, which became generally available earlier this year, is a revolutionary mode of operations for managed Kubernetes that makes this possible, reducing the need for hands-on cluster management […]

AI researchers and engineers need better data to enable better AI solutions. The quality of an AI solution is determined by both the learning algorithm (such as a deep-neural network model) and the datasets used to train and evaluate that algorithm. Historically, AI research has focused much more on algorithms than datasets, despite their vital […]