Google Distributed Cloud adds AI, ML and Database Solutions to deliver customers even greater flexibility and choice
Vice President & GM, Infrastructure, Google Cloud
Organizations need a cloud platform that can securely scale from on-premises, to edge, to cloud while remaining open to change, choice, and customization. They must be able to run their applications wherever they need, on infrastructure optimized to process a very high volume of data with minimal delay, all while maintaining the satisfaction and stability of their ML-driven user experiences. At Google, we deeply understand these customer requirements, which is why we launched Google Distributed Cloud last year. With Google Distributed Cloud, we bring a portfolio of fully managed solutions to extend our infrastructure to the edge and into customers’ own data centers.
Today, Google Cloud customers love our artificial intelligence (AI) services for building, deploying and scaling more effective AI models with developers successfully using our core machine learning (ML) services to build and train high-quality custom ML models. Our customers are also using a variety of our managed database solutions because of their simplicity and reliability. However, some customers have highly sensitive workloads and desire to use their own private, dedicated facilities.
For these customers, we’re excited to announce they will be able to run a selection of these same AI, ML, and database services in Google Distributed Cloud Hosted inside their own data centers within the next year. With this announcement, customers get to take advantage of Anthos, a common management control plane which provides a consistent development and operations experience across hybrid environments. This same experience is now available for on premise environments.
Our portfolio of AI, ML, and database products enable customers to quickly deploy services with out-of-box simplicity that includes delivering valuable insights through both unstructured and structured data. The integration of our Google Cloud AI and database solutions into the Google Distributed Cloud portfolio means the ability to harness real-time data insights like never before due to the proximity to where the data is being generated and consumed. This includes ensuring low latency to support applications that are mission critical to businesses such as computer vision, which can be used on the factory floor to detect flaws in products or to index large amounts of video. The addition of these transformative capabilities allow customers to save money, innovate faster and provide the greatest flexibility and choice.
With this integration, customers using Google Distributed Cloud Hosted will have access to some exciting AI features. One example is our Translation API that can instantly translate texts in more than one hundred languages. Translation API is a feature available in Vertex AI, our managed ML platform that is generally available and allows companies to accelerate the deployment and maintenance of AI models. With this announcement, customers who need to run highly sensitive workloads in an on-premise or edge environment can now leverage the unique functionality of Translation API along with other Google Cloud pre-trained API’s in Vertex AI such as Speech-to-Text and optical character recognition (OCR). These features were all trained on our planet-scale infrastructure to deliver the highest level of performance, and as always, all of our new AI products also adhere to our AI Principles.
Additionally, by incorporating our managed databases offering onto the Google Distributed Cloud portfolio, customers can process data locally to migrate or modernize applications, opening up more time for innovation and to create value in their applications. This is especially true in industries like financial services and healthcare where there are compliance requirements on where data can reside.
With these new AI, ML and databases products available in our Google Distributed Cloud portfolio, customers will still have full authority to maintain autonomy and control over their own data centers, yet can rely on Google for the latest technology innovations in cloud services.