Harnessing the Power of Multicloud
To cut to the chase: Workday runs in multiple public clouds. Being multicloud allows us to pick and choose the best capabilities from the innovation race that’s taking place across vendors as they make multibillion-dollar investments in the public cloud. Indeed, we’ve made our own significant investments into our multicloud framework, which is built on Google Kubernetes Engine (GKE), giving us the ability to leverage the best of public cloud capabilities while providing flexibility to our customers.
Already, we offer customers the option to run our Workday Financial Management and Workday Human Capital Management (HCM) applications on AWS in the U.S., Canada, Singapore, Germany, and Australia. Additionally, Workday Financial Management and Workday HCM are available on Google Cloud in selected markets. Our goal is to continue to add additional products and regions to support our global strategic growth initiatives.
The significant capital investments made by public cloud providers and the resulting breadth of functionality is compelling. We aim to take advantage of these capabilities both to enhance the core Workday service as well as to leverage foundational tools such as artificial intelligence (AI) and machine learning (ML) capabilities. We’re partnering with public cloud vendors that provide the most innovative, compelling capabilities—such as Amazon Aurora, GKE, and more—so that we can deliver competitive advantages to our customers, particularly around AI and ML.
By collaborating with public cloud providers, we leverage their extensive infrastructure and capabilities to enhance our AI services. This enables our customers to use various AI and ML capabilities such as advanced analytics, intelligent automation, and predictive insights—unlocking faster innovation, scalability, and ROI.
A great example of this is with our first iterations of document-understanding applications, such as expense receipt optical character recognition (OCR), which was based on technology that we built in-house. OCR uses AI and ML to streamline a number of manual processes and remove the need for data entry by humans, such as expense receipt scanning and supplier invoice scanning. Today, we now utilize Google Cloud’s Procurement DocAI solution for OCR.
Similarly, rather than build and maintain specialized compute and storage infrastructure specifically for ML development, we leverage infrastructure services in AWS to meet those needs.
We want to focus our efforts where they bring the greatest value to our customers. In addition to continuing to build cutting-edge capabilities on our own, we also leverage innovation infrastructure from our partners. In other words, Workday features that complement the core Workday service, such as OCR, may leverage and integrate with several public cloud providers—providing best-in-class capabilities while protecting customer data and complying with regulatory requirements.
We know, though, that the use of a provider’s cloud services should be approached thoughtfully. While multicloud portability is required over time, we’re looking beyond the lowest common denominator of price per unit of compute/storage/networking and instead looking at overall value to our customers’ business.