Build a Data Mesh on Google Cloud with Dataplex, Now Generally Available
Democratizing data insights and accelerating data-driven decision making is a top priority for most enterprises seeking to build a data cloud. This often requires building a self-serve data platform that can span data silos and enable at-scale usage and application of data to drive meaningful…
Ready, Set, Launch! Cloud Spanner Makes Application Launches Easier with Warmup and Benchmarking Tool
Cloud Spanner is a fully managed relational database with unlimited scale, strong consistency, and up to five 9s of availability. To achieve the powers of consistency, scale and availability by default Cloud Spanner has a built-in mechanism to automatically shard your database and provide a…
Developing High-quality ML Solutions
When a deployed ML model produces poor predictions, it can be due to a wide range of problems. It can be the result of bugs that are typical in any program—but it can also be the result of ML-specific problems. Perhaps data skews and anomalies…
Introducing Google Cloud’s Tomcat Migration Tooling
Apache Tomcat is one of the most commonly used web servers and servlet containers for running Java applications. Many enterprises run production Java web applications on Tomcat servers, running on virtual machines and are looking to modernize those applications to run in containers and enjoy the…
Choosing the Right Network Architecture for Your Apigee-fueled APIs
API gateways are a critical component of a modern architecture. Apigee X is Google Cloud’s API management platform. It also allows users of the legacy Apigee Edge product to leverage Virtual Private Cloud (VPC) products and features, like Cloud Armor and Load Balancers. With these new security and availability advantages come a new…
Think Serverless: Tips for Early-stage Startups
As Google Cloud has become a choice for more startups, I’ve experienced an increase in founders asking how they should think about cloud services. Though each startup is different and requirements may vary across industries and regions, I’ve seen a few core best practices that help startups…
Unleash Collaboration with New Experiences in Google Workspace
16 years ago, Google launched Google Docs and Sheets and introduced the world to a new way of working. For many, it was the first time they worked in the same digital space together, in real time, without the burden—or risk—of sending documents back and forth. That…
Supercharge Your Event-driven Architecture with New Cloud Functions (2nd gen)
Today, Google introducing Cloud Functions (2nd gen) into public preview, Google Cloud’s next-generation Functions-as-a-Service product. This next generation version of Cloud Functions comes with an advanced feature set giving you more powerful infrastructure, advanced control over performance and scalability, more control around the functions runtime and triggers…
Orchestrating PyTorch ML Workflows on Vertex AI Pipelines
Previously in the PyTorch on Google Cloud series, Google trained, tuned and deployed a PyTorch text classification model using Training and Prediction services on Vertex AI. In this post, we will show how to automate and monitor a PyTorch based ML workflow by orchestrating the pipeline in a serverless manner…
Add Intelligence to Your Document Processing with Google’s Enterprise Knowledge Graph
Google Cloud introduced Document AI to automate document processing and to streamline workflows with state-of-the-art machine learning models. With the deep neural networks, the models generalize the learning from seeing hundreds of thousands variations of the documents. But when information is missing or ambiguous on a document…