With a global, always-on workforce, the U.S. Navy requires secure collaboration between teams across countries and time zones. This is especially relevant for the 50,000 U.S. Navy sailors deployed aboard approximately 100 ships at any given time, who need to connect with personnel at regional shipyards for everything from routine maintenance, to more serious ship repairs.

Google Public Sector directly assists Naval Sea Systems Command (NAVSEA), the largest of the U.S. Navy’s five “systems commands,” by providing support to the U.S. Naval Ship Repair Facility and Japan Regional Maintenance Center (SRF-JRMC) in Yokosuka and Sasebo, Japan. NAVSEA is using Google Workspace, which harnesses Google’s threat protection and zero trust capabilities, to enable effective, secure, and compliant collaboration between the SRF-JRMC and Navy stakeholders around the world.

The workforce in the SRF-JRMC facility had two unique challenges. The first was around ineffective collaboration and communication channels. Before deploying Google Workspace, a Navy officer in Japan would need to be on-base to communicate over a secure connection, and calls were typically late at night given the time difference. This challenge was even further magnified when the COVID-19 pandemic hit, further restricting staff mobility.

The second challenge was a language barrier. With more than 3,000 Japanese Master Labor Contract (MLC) employees providing critical support to SRF-JRMC’s shipyard, Navy leadership needed an easier way to communicate with their Japanese-speaking counterparts. Breaking down this barrier would ensure work could be completed faster and more effectively, facilitating a more collaborative environment.

Enabling secure collaboration

The Navy partnered with Google Public Sector to enable Google Workspace for SRF-JRMC. Today, Google Workspace assists the Navy’s shipyards by enabling Google Voice for secure voice over Internet Protocol (VoIP) calling options, so personnel can join calls and sessions on-site or at-home to communicate securely and reliably across continents. In addition, early access to solutions like English to Japanese translated captions in Google Meet help break down the language barrier by providing instant translation during meetings. The platform also saves the U.S. Navy thousands of dollars a month in phone bills by providing country-specific dial-in numbers for interviews.

Moreover, Google Workspace tools like Google Drive and Docs also help to simplify human resource workflows by streamlining the hiring for onboarding local Japanese employees for the shipyard. Having a shared Google Drive eliminates the need to send multiple files back and forth among the NAVSEA team, allowing them to minimize on-premises storage space. In addition, Google Docs enables Navy employees to communicate and collaborate with each other and with potential candidates securely, and across any device.

“As the largest overseas ship repair facility of the U.S. Navy, operational readiness and continuity of operations is our top priority,” said Peter Guo, chief information officer at SRF-JRMC. “Cloud collaboration capabilities provide us seamless and secure connectivity across continents and break down language barriers with our colleagues across the globe. We’ve improved our ability to operate anytime, and anywhere and have increased our ability to securely communicate and coordinate especially during network outages and natural disasters.”

Providing pandemic assistance

Google for Government’s Workspace solutions also became useful to the SRF-JRMC during the pandemic, providing valuable communication and collaboration tools during a time of uncertainty. In addition to deploying Google Workspace, SRF-JRMC’s IT department created a COVID-19 Pandemic Dashboard, a Google-based site that consolidated Japanese and international open-source data on COVID-19 outbreaks and provided updated guidance. The Dashboard was built in less than two hours, using Looker Studio, and it leveraged an automated data collection process to track local hospitalization numbers. Before building the site, it took the NAVSEA team hours to compile this information; now, the team can access this information in real-time.

“This Dashboard drastically reduced redundant weekly meetings centered on COVID-19 updates, and saved more than 10 hours per week manually gathering data and presenting it via slide decks,” said Guo. “Additionally, this capability enabled our leadership to make real-time, data-driven decisions and put necessary risk mitigations in place. It empowered supervisors across the shipyard to reference this website at any time and put additional health measures in place to minimize the transmission of COVID-19. Every minute counts at our two shipyards in Japan, so this made a tremendous impact on our operational efficiency and ensured the safety of our sailors.”

Delivering the best possible tools means making life better and work more fulfilling for millions of people, inside and outside of government. To help government agencies maintain access to communications and collaboration tools that they need during and after an incident to keep work going, we are also offering workshops for federal, state and local governments. Learn more about Google for Government solutions for the Department of Defense, and Google Workspace for Government.

While the promise of artificial intelligence transforming the manufacturing industry is not new, long-ongoing experimentation hasn’t yet led to widespread business benefits. Manufacturers remain in “pilot purgatory,” as Gartner reports that only 21% of companies in the industry have active AI initiatives in production. 

However, new research from Google Cloud reveals that the COVID-19 pandemic may have spurred a significant increase in the use of AI and other digital enablers among manufacturers. According to our data—which polled more than 1,000 senior manufacturing executives across seven countries—76% have turned to digital enablers and disruptive technologies due to the pandemic such as data and analytics, cloud, and artificial intelligence (AI). And 66% of manufacturers who use AI in their day-to-day operations report that their reliance on AI is increasing.

The top three sub-sectors deploying AI to assist in day-to-day operations are automotive/OEMs (76%), automotive suppliers (68%), and heavy machinery (67%).

In fact, Bryan Goodman, Director of Artificial Intelligence and Cloud, Ford Global Data & Insight and Analytics shares, “Our new relationship with Google will supercharge our efforts to democratize AI across our business, from the plant floor to vehicles to dealerships. We used to count the number of AI and machine learning projects at Ford. Now it’s so commonplace that it’s like asking how many people are using math. This includes an AI ecosystem that is fueled by data, and that powers a ‘digital network flywheel.’”

Moving from edge cases to mainstream business needs

Why are manufacturers now turning to AI in increasing numbers? Our research shows that companies who currently use AI in day-to-day operations are looking for assistance with business continuity (38%), helping make employees more efficient (38%), and to be helpful for employees overall (34%). It’s clear that AI/ML technology can augment manufacturing employees’ efforts, whether by providing prescriptive analytics like real-time guidance and training, flagging safety hazards, or detecting potential defects on the assembly line.

In terms of specific AI use cases called out by the research, two main areas emerged: quality control and supply chain optimization. In the quality control category, 39% of surveyed manufacturers who use AI in their day-to-day operations use it for quality inspection and 35% for product and/or production line quality checks. At Google Cloud, we often speak with manufacturers about AI for visual inspection of finished products. Using AI vision, production line workers can spend less time on repetitive product inspections and can instead focus on more complex tasks, such as root cause analysis. 

In the supply chain optimization category, manufacturers said they tapped AI for supply chain management (36%), risk management (36%), and inventory management (34%).

In our day-to-day work, we’re seeing many manufacturers rethink their supply chains and operating models to better accommodate for the increased volatility that has been brought about by the pandemic and support the secular trend of consumers asking for increasingly individualized products. We’ll share more on deglobalization in the third installment of our manufacturing insights series.

AI use differs by geography, but not for the reasons you may think

The extent to which AI is already being used today varies quite strongly between geographies, according to our research. While 80% and 79% of manufacturers in Italy and Germany respectively report using AI in day-to-day operations, that percentage plummets in the United States (64%), Japan (50%) and Korea (39%).

It’s tempting to state this disparity is due to an “AI talent gap.” Although the most common barrier, just a quarter (23%) of manufacturers surveyed believe they don’t have the talent to properly leverage AI. Cost, too, does not appear to be a roadblock (21% of those surveyed). Rather, from our observations, the missing link appears to be having the right technology platform and tools to manage a production-grade AI pipeline. This is obviously the focus of our efforts and others in the space, as we believe the cloud can truly help the industry make a step change.

Looking ahead: The Golden Age of AI for manufacturing

The key to widespread adoption of AI lies in its ease of deployment and use. As AI becomes more pervasive in solving real-world problems for manufacturers, we see the industry moving away from “pilot purgatory” to the “golden age of AI.” The manufacturing industry is no stranger to innovation, from the days of mass production, to lean manufacturing, six sigma and, more recently, enterprise resource planning. AI promises to bring even more innovation to the forefront. 

To learn more about these findings and more, download our infographic here and our full report here. 

^{Research methodology
The survey was conducted online by The Harris Poll on behalf of Google Cloud, from October 15 – November 4, 2020, among 1,154 senior manufacturing executives in France (n=150), Germany (n=200), Italy (n=154), Japan (n=150), South Korea (n=150), the UK (n=150), and the U.S. (n=200) who are employed full-time at a company with more than 500 employees, and who work in the manufacturing industry with a title of director level or higher. The data in each country were weighted by number of employees to bring them into line with actual company size proportions in the population. A global post-weight was applied to ensure equal weight of each country in the global total.}

Meeting the rapidly growing demands of our customers’ high performance computing and data-intensive workloads requires deep innovation — at Google Cloud, we know we can’t rely on ever-faster CPUs alone, like Moore’s Law has enabled in the past. Customers can either optimize their workloads for a given platform, or we can offer them a platform that is optimized for their specific needs. At Google Cloud, we choose the latter.

Today, we have an exciting new release resulting from these efforts: the new C3 machine series powered by the 4th Gen Intel Xeon Scalable processor and Google’s custom Intel Infrastructure Processing Unit (IPU). Along with the recently announced Hyperdisk block storage which offers 80% higher IOPS per vCPU for high-end database management system (DBMS) workloads when compared to other hyperscalers. C3 machine instances can deliver strong performance gains to enable high performance computing and data-intensive workloads. Customers such as Snap, for example, have seen approximately a 20% increase in performance for a key workload over the previous generation C2.

The C3 machine series is just the latest example of this architectural approach. For over two decades, Google has purpose-built and designed some of the world’s most efficient and scalable computing systems to meet the needs of our customers. We built the Tensor Processing Unit (TPU) to power real-time voice search, photo object recognition, and interactive language translation; unveiled Titan, a secure, low-power microcontroller to help ensure that every machine boots from a trusted state; and launched Video Coding Units (VCUs) to enable video distribution that addresses a range of formats and client requirements. We engineer golden paths from silicon to the console, using a combination of purpose-built infrastructure, prescriptive architectures, and an open ecosystem to deliver what we term workload-optimized infrastructure.

Getting to know the C3 machine series

The Compute Engine C3 machine series, now available in Private Preview, is the first VM in the public cloud with the 4th Gen Intel Xeon Scalable processor and with Google’s custom Intel IPU. C3 machine instances use offload hardware for more predictable and efficient compute, high-performance storage, and a programmable packet processing capability for low latency and accelerated, secure networking.

“We are pleased to have co-designed the first ASIC Infrastructure Processing Unit with Google Cloud, which has now launched in the new C3 machine series. A first of its kind in any public cloud, C3 VMs will run workloads on 4th Gen Intel Xeon Scalable processors while they free up programmable packet processing to the IPUs securely at line rates of 200Gb/s. This Intel and Google collaboration enables customers through infrastructure that is more secure, flexible, and performant.” – Nick McKeown, Senior Vice President, Intel Fellow and General Manager of Network and Edge Group

The System on a Chip hardware architecture introduced in C3 VMs can enable better security, isolation, and performance. In the future, this purpose-built architecture will also allow us to offer a richer product portfolio, such as support for native bare-metal instances.

Hyperdisk block storage and 200 Gbps networking

Block storage and VMs go hand in hand. Last month, we announced the Preview release of Hyperdisk, our next-generation block storage. The new architecture decouples compute instance sizing from storage performance to deliver 80% higher IOPS per vCPU than other leading hyperscale cloud provider. And compared with the previous generation C2, C3 VMs with Hyperdisk deliver 4x higher throughput and 10x higher IOPS. Now, you don’t have to choose expensive, larger compute instances just to get the storage performance you need for data workloads such as Hadoop and Microsoft SQL Server.

To enable high performance computing workloads, C3 VMs also feature 200 Gbps low-latency networking powered by our custom IPU, as well as line-rate encryption using the open source PSP protocol.

What our customers and partners are saying

“We were pleased to observe a 20% increase in performance over the current generation C2 VMs from Google Cloud in testing with one of our key workloads. These continued performance improvements enable better end user experience and application cost efficiency.” – Aaron Sheldon, Sr. Software Engineer, Snap Inc.

“Based on the initial performance data, running weather research and forecasting (WRF) on C3 clusters can deliver as much as 10x quicker time to results for about the same computational cost. This will significantly accelerate R&D for our customers in weather, environment, and engineering domains.” — Michael Wilde, CEO, Parallel Works Inc.

“In early testing with our flagship products, including Ansys Fluent, Mechanical and LS-DYNA, on the new Google Cloud C3 VM, we’re seeing up to 3x performance gains over C2 VMs due to higher memory bandwidth and lower network latency.” – Shane Emswiler, Senior Vice President of Products, Ansys

Where we are headed

With the exponential rise in the complexity of cloud infrastructure, we as an industry must turn to automation to manage these platforms efficiently at scale. Along with Infrastructure as Code, custom chips like the Titan, the TPU and the IPU, pave the way for a not-so-distant future where we’ll automate over half of all infrastructure decisions, configuring systems dynamically in response to usage patterns. At Google Cloud, we are committed to continuing our long history of hardware innovation with a focus on workload optimization and automation.

To learn more about C3 VMs and Hyperdisk, check out our session at NEXT ‘22, How Google Cloud optimizes infrastructure for your workloads. To request access to the C3 VMs or Hyperdisk, please reach out to your sales representative or account manager.

In an industry as highly regulated as healthcare, building a single secure and compliant application that tracks patient care and appointments at a clinic requires a great deal of planning from development and security teams. So, imagine what it would be like to build a solution that includes almost everything related to a patient’s healthcare, including insurance and billing. That’s what Highmark Health (Highmark)—a U.S. health and wellness organization that provides millions of customers with health insurance plans, a physician and hospital network, and a diverse portfolio of businesses–decided to do. 

Highmark is developing a solution called Living Health to re-imagine healthcare delivery, and it is using Google Cloud and the Google Cloud Professional Services Organization (PSO) to build and maintain the innovation platform supporting this forward thinking experience. Considering all the personal information that different parties like insurers, specialists, billers and coders, clinics, and hospitals share, Highmark must build security and compliance into every part of the solution. 

In this blog, we look at how Highmark Health and Google are using a technique called “secure-by-design” to address the security, privacy, and compliance aspects of bringing Living Health to life.

Secure-by-design: Preventive care for development

In healthcare, preventing an illness or condition is the ideal outcome. Preventive care often involves early intervention—a course of ideas and actions to ward off illness, permanent injury, and so on. Interestingly, when developing a groundbreaking delivery model like Living Health, it’s a good idea to take the same approach to security, privacy, and compliance. 

That’s why Highmark’s security and technology teams worked with their Google Cloud PSO team to implement secure-by-design for every step of design, development, and operations. Security is built into the entire development process rather than waiting until after implementation to reactively secure the platform or remediate security gaps. 

It’s analogous to choosing the right brakes for a car before it rolls off the assembly line instead of having an inspector shut down production because the car failed its safety tests. The key aspect of secure-by-design is an underlying application architecture created from foundational building blocks that sit on top of a secure cloud infrastructure. Secure-by-design works to ensure that these building blocks are secure and compliant before moving on to development.

The entire approach requires security, development, and cloud teams to work together with other stakeholders. Most importantly, it requires a cloud partner, cloud services, and a cloud infrastructure that can support it. 

Finding the right cloud and services for secure-by-design 

Highmark chose Google Cloud because of its leadership in analytics, infrastructure services, and platform as a service. In addition, Google Cloud has made strategic investments in healthcare interoperability and innovation, which was another key reason Highmark decided to work with Google. As a result, Highmark felt that Google Cloud and the Google Cloud PSO were best suited for delivering on the vision of Living Health—its security and its outcomes. 

“Google takes security more seriously than the other providers we considered, which is very important to an organization like us. Cloud applications and infrastructure for healthcare must be secure and compliant,” explains Highmark Vice President and Chief Information Security Officer, Omar Khawaja. 

Forming a foundation for security and compliance

How does security-by-design with services work? It starts with the creation and securing of the foundational platform, allowing teams to harden and enforce specified security controls. It’s a collaborative process that starts with input from cross-functional teams—not just technology teams—using terms they understand, so that everyone has a stake in the design. 

A strong data governance and protection program classifies and segments workloads based on risk and sensitivity. Teams build multiple layers of defense into the foundational layers to mitigate against key industry risks. Google managed services such as VPC Service Controls help prevent unauthorized access. Automated controls such as those in Data Loss Prevention help teams quickly classify data and identify and respond to potential sources of data risk. Automation capabilities help ensure that security policies are enforced.

After the foundational work is done, it’s time to assess and apply security controls to the different building blocks, which are Google Cloud services such as Google Kubernetes Engine, Google Compute Engine, and Google Cloud Storage. The goal is to make sure that these and similar building blocks, or any combination of them, do not introduce additional risks and to ensure any identified risks are remediated or mitigated. 

Enabling use cases, step by step

After the foundational security is established, the security-by-design program enables the Google Cloud services that developers then use to build use cases that form Living Health. The service enablement approach allows Highmark to address complexity by providing the controls most relevant for each individual service. 

For each service, the teams begin by determining the risks and the controls that can reduce them. The next step is enforcing preventive and detective controls across various tools. After validation, technical teams can be granted an authorization to operate, also called an ATO. An ATO authorizes the service for development in a use case.

For use cases with greater data sensitivity, the Highmark teams validate the recommended security controls with an external trust assessor, who uses the HITRUST Common Security Framework, which maps to certifications and compliance such as HIPAA, NIST, GDPR, and more. A certification process follows that can take anywhere from a few weeks to a few months. In addition to certification, there is ongoing monitoring of the environment for events, behavior, control effectiveness, and control lapses or any deviation from the controls.

The approach simplifies compliance for developers by abstracting compliance requirements away. The process provides developers a set of security requirements written in the language of the cloud, rather than in the language of compliance, providing more prescriptive guidance as they build solutions. Through the secure-by-design program, the Highmark technology and security teams, Google, the business, and the third-party trust assessor all contribute to a secure foundation for any architectural design with enabled Google Cloud services as building blocks. 

Beating the learning curve 

Thanks to the Living Health project, the Highmark technology and security teams are trying new methods. They are exploring new tools for building secure applications in the cloud. They are paying close attention to processes and the use case steps and, when necessary, aligning different teams to execute. Because everyone is working together collaboratively toward a shared goal, teams are delivering more things on time and with predictability, which has reduced volatility and surprises. 

The secrets to success: Bringing everyone to the table early and with humility

Together, Highmark and Google Cloud PSO have created over 24 secure-by-design building blocks by bringing everyone to the table early and relying on thoughtful, honest communication. Input for the architecture design produced for Highmark came from privacy teams, legal teams, security teams, and the teams that are building the applications. And that degree of collaboration ultimately leads to a much better product because everyone has a shared sense of responsibility and ownership of what was built. 

Delivering a highly complex solution like Living Health takes significant, more purposeful communication and execution. It is also important to be honest and humble. The security, technology, and Google teams have learned to admit when something isn’t working and to ask for help or ideas for a solution. The teams are also able to accept that they don’t have all the answers, and that they need to figure out solutions by experimenting. Khawaja puts it simply, “That level of humility has been really important and enabled us to have the successes that we’ve had. And hopefully that’ll be something that we continue to retain in our DNA.”