Google LLC is giving enterprise customers more choice on where they want to run their cloud workloads.

The company today launched Google Distributed Cloud, a new service that combines hardware and software to extend Google Cloud infrastructure to customers’ data centers and edge locations. That was just one of several new services and updates announced during a busy day at Google Cloud Next ’21.

Besides extending its cloud infrastructure, the company unveiled Intelligent Products Essentials, a new service that enables manufacturers to build products infused with artificial intelligence. And there are multiple updates to Google’s data and analytics portfolio, with new features such as a managed Spark on Google Cloud, BigQuery Omni general availability and Vertex AI Workbench.

Google’s Distributed Cloud offering is a major new initiative that’s designed to bring many more workloads into Google Cloud. It essentially brings the Google Cloud stack into customers’ own data centers, allowing them to run on-premises applications with the same Google application programming interfaces, control planes, hardware and tools they use to connect with their other Google apps and services.

It’s an idea that may sound familiar. Indeed, Google Distributed Cloud seems to be Google’s answer to Microsoft Corp.’s Azure Stack and Amazon Web Services Inc.’s Outposts, which are services that extend the Azure and AWS clouds into customers’ own data centers.

In a blog post, Google said Distributed Cloud is all about helping companies to accelerate cloud adoption. Enterprises still run an awful lot of applications that cannot be moved to the public cloud because of concerns about compliance, data sovereignty, the need for low latency and numerous other reasons. Distributed Cloud extends the company’s cloud infrastructure, making it possible for apps that need to remain on-premises to take advantage of everything Google Cloud has to offer.

“Google Distributed Cloud GDC is a fully managed portfolio that extends Google Cloud to the edge and right into their data centers,” said Sachin Gupta, vice president and general manager for infrastructure. “They can focus on applications and leave the complexity to us.”

Underlying the Distributed Cloud is Google’s Anthos platform that helps to unify infrastructure and application management in multiple public clouds, on-premises and the edge to enable consistent operation across all of those environments.

“Google Distributed Cloud taps into our planet-scale infrastructure that delivers the highest levels of performance, availability, and security, while Anthos running on Google-managed hardware at the customer or edge location provides a services platform on which to run applications securely and remotely,” the company explained.

With Google Distributed Cloud, the company says, customers will be able more easily to migrate or modernize their applications and process data locally using Google Cloud’s database, machine learning, data analytics and container management services. They’ll be able to run Distributed Cloud in four different locations: at Google’s 140+ network edge locations, at the “Operator edge” to take advantage of Google’s communication service provider partner’s networks, in their own data centers, and at the Customer Edge, which is remote locations such as retail stores, factory floors, branch offices and so on.

A key part of the service is the hardware needed to run Distributed Cloud on-premises, and Google said it’s launching with systems available from the likes of Dell Technologies Inc., Hewlett-Packard Enterprise Co., Cisco Systems Inc. and NetApp Inc. “We are the only cloud provider that gives customers the option to scale compute and storage independently,” Gupta said.

Google said it’s launching with two products in preview. Google Distributed Cloud Edge is in preview now, giving customers a way to run their apps at Google’s Edge locations. Google Distributed Cloud Hosted, meanwhile, is a more secure offering companies can host themselves, or with a secure partner, that doesn’t require connectivity to Google Cloud. It’s scheduled to launch in preview in the first half of next year.

“Distributed Cloud Hosted builds on the digital sovereignty vision we outlined last year,” Gupta said. “It’s a safe and secure way to optimize on-premises performance without connecting to Google Cloud.” The offering is built with open application program interfaces “for consistency and portability,” Gupta added.

Building smarter products

The distributed cloud concept could well be a key enabler of Google’s push into intelligent product manufacturing that was also announced today. Intelligent Products Essentials is a suite of tools manufacturers can use to embed intelligence into their products using Google’s AI services, the company explained. They’ll be able to rapidly deliver products that adapt to their owners, update features over the air using AI at the edge, and provide customer insights using analytics in the cloud.

Intelligent Products Essentials will enable manufacturers to deliver more personalized customer experiences, for example by creating chatbots that deliver contextual responses based on a product’s status and the customer’s profile. They’ll also be able to predict product failures, for example in a smart car, by detecting operating thresholds and anomalies. Armed with this knowledge, companies then can proactively recommend service using AI.

Naturally there’s a fair few components bundled into Intelligent Products Essentials. The main one is Edge Connect, which makes use of Google’s IoT Core and Pub/Sub services to enable deployment and management of firmware over the air. Google is also providing an Ownership App Template customers can use to build product companion apps, as well as product fleet management tools and the essential AI capabilities through its Vertex AI service, such as DialogFlow, Vision AI and AutoML.

Google said Intelligent Products Essentials can be used to build smarter products across the consumer, industrial, enterprise and transportation spaces. International Data Corp. analyst Kevin Prouty said the service is all about enabling more decision-making.

“IDC sees faster and more effective decision-making as the fundamental reason for the drive to digitize products and processes,” he said. “It’s how you can make faster and more effective decisions to meet heightened customer expectations, generate faster cash flow and better revenue realization.”

Doing more with data

As always, there were plenty of product updates to go along with the new product releases announced today. Many of them are focused on simplifying how customers work with and get value from their data.

In particular, Google is looking to simplify the process of getting value out of data, akin to how Google originally simplified search. “Data is stuck in that age of complexity,” Gerrit Kazmaier, vice president and general manager of Google’s data portfolio, told SiliconANGLE in an interview. “Data is the origin of value creation. We want to give people the tools they need so they can use data the way they want.”

For instance, Google said it’s extending its Vertex AI platform with the launch in preview of Vertex AI Workbench. Launched in May, Vertex AI is a managed machine learning platform that can train AI models using 80% fewer lines of code than alternative platforms.

One of the main advantages of Vertex AI is that it brings together all of the Google Cloud services necessary for building machine learning models under a single, unified user interface and API. With the launch of Vertex AI Workbench, customers can access a premium, unified user experience that integrates data services such as Dataproc, BigQuery, Dataplex and Looker.

Google also said it’s expanding its Contact Center AI and DocAI services. Contact Center AI is a service that automates call center operations and it’s getting new CCAI Insights (pictured below) that provide out-of-the-box modeling techniques that help teams to better understand customer interaction data. As for DocAI, an AI-powered document processing service, there’s a new tool here called Contract DocAI that can be used to extract insights from the unstructured text in contracts to reduce the costs associated with contract processing.

Yet another update pertains to BigQuery Omni, which is now generally available after launching in preview earlier this year. The service is designed to address complex data management across hybrid and multicloud environments, making it possible to analyze data sitting in Google Cloud, AWS and Azure.

That plays into Google’s data simplification drive as well. “You just give it a query… it just gives you the result back on virtually any size of data in a short period of time,” Kazmaier said.

Launching in preview, meanwhile, is Spark on Google Cloud. The company says this is the world’s first autoscaling and serverless Spark service. It means Apache Spark, a unified analytics engine for big data processing, is now available as a premium offering on Google Cloud. Google said it can be used to process and analyze data from services such as BigQuery, Dataproc, Dataplex and Vertex AI.

“There are no worries about clusters and configurations and you can launch directly” from within the analytics engines, said Kazmaier, who cited a five-times jump in productivity because data scientists don’t need to switch back and forth. “I think it will have as big an impact as BigQuery,” he said.

Finally, and perhaps even the most intriguing of Google’s announcements today, is the preview launch of Google Earth Engine on Google Cloud. It’s a new service that makes Google Earth Engines’ more than 50-petabyte mass of high-resolution satellite imagery and geospatial data available for “planetary scale analysis,” the company said.

Enterprises that are interested will be able to integrate Google Earth Engine with BigQuery, various machine learning services and even Google Maps to dig into Google’s satellite imagery. They may gain some insights on how the world is changing and what actions they can take in pursuit of noble goals around sustainable sourcing and energy savings.

With reporting from Paul Gillin and Robert Hof

Images: Google