Introduction - Google Cloud Platform Tutorial

To understand the impact that cloud can have on a business, it's important to first recognize some of the fundamental cloud concepts. By the end of this section, you'll be able to describe the benefits of moving to cloud infrastructure through customer business use cases, explain how moving to the cloud shifts an organization's spending from capital expenditure to operating expenditure and how that affects their total cost of ownership, identify when private, hybrid or multicloud infrastructures best apply to different business use cases, define basic network infrastructure terminology, and explain how Google Cloud supports digital transformation with global infrastructure and data centers connected by a fast, reliable network. Cloud adoption has made a positive impact on some of the world's leading companies across various industries. Let's start with an example of how the cloud provided flexibility and improved performance for the Canadian food and pharmacy leader, Loblaw. Loblaw is Canada's largest retailer with nearly 2,500 corporate, franchised, and associate owned locations and nearly 200,000 full and part time employees. The vice president of technology at Loblaw explained, "We want our tech talent focused on creating better experiences for our customers, not maintaining infrastructure." Loblaw took a lift and shift approach to accelerate the initial migration to Google Cloud. This means they focused on moving their existing virtual machines on-premises to compute engine instances in the cloud without needing to redesign them. However, they designed the cloud architecture to be easily converted to using Google Kubernetes engine for automated deployment and scaling later. This shows how an open cloud can grow with an organization's needs. With a more responsive e-commerce site and the ability to handle more traffic without affecting the customer experience, Loblaw could run marketing promotions and generate additional revenue. With these improvements, they expect to reclaim 50% of their site reliability engineers time to focus on innovation. Now let's shift our focus to another example, this time on how the cloud provided scalability and cost reduction. HSBC is one of the world's largest banking and financial services organizations, serving more than 40 million global customers from offices in 64 countries and territories. Committed to a cloud first strategy, in January 2021, HSBC embarked on an ambitious project to enhance and futureproof their risk management on the cloud. Their previous on-premises system was not capable of meeting future regulatory and business demands. HSBC built a cloud native risk management solution that boosts calculation speed to 10 times faster while lowering costs. This equated to 3 billion calculations per second. The power of a data cloud is that it has almost unlimited resources to process large volumes of data and reduce time to insights. A global head of traded risk technology at HSBC, explains, "We knew that a cloud-native solution gave us the ability to scale and run at a reduced cost. We did a proof of concept using Google Cloud and we quickly realized that this could be very successful." HSBC built a cost effective platform that is faster and more efficient while meeting their regulatory and compliance requirements. And in a final example, let's look at how the cloud has brought agility and valuable insights while maintaining trust to an organization. The American Cancer Society is a community based voluntary health organization dedicated to eliminating cancer as a major health problem. Their mission is to free the world from cancer by funding and conducting research, sharing expert information, supporting patients, and spreading the word about prevention. Among women, breast cancer is the most common diagnosed type of cancer yet if detected early, is also one of the most survivable cancers. Mia M. Gaudet, PhD, is the Scientific Director of Epidemiology Research at the American Cancer Society. Through her research, she's obtained over 1,700 high resolution tissue images from participants diagnosed with breast cancer. This valuable data could help them discover factors that could lead to a cancer diagnosis and improve survival rates. The challenge was to identify novel patterns in digital images of breast cancer tissues to potentially improve patient outcomes. Their research group partner with Slalom, a Google Cloud premier partner and sought to combine machine learning powered insights with cloud computing performance to improve timeliness and accuracy. By building a machine learning pipeline using Google Cloud platform now called Vertex AI, they train models for AI image analysis of tissue scans to find cancer indicators. The team achieved 12 times faster image analysis with enhanced quality and accuracy by removing human limitations. Dr. Gaudet said, "The ability to perform image analysis by using deep learning for epidemiological breast cancer studies opens a new frontier of research, and Google Cloud makes it easier. We're excited about what we'll find." The American Cancer Society is now equipped with processes in a cloud infrastructure that will be reusable on similar projects, providing a foundation for future work.