Connected Data is the Lifeblood of Today's Retailers: IDC's 2022 Research - Build What's Next
Trend Analysis

Connected Data is the Lifeblood of Today’s Retailers: IDC’s 2022 Research

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The 2022's National Retail Federation (NRF) highlighted emerging themes and technologies dictating the retail industry. The way ahead is in digital along with a mix of physical stores, customer focused web apps, Metaverse and hybrid channels!

For a look ahead at the trends that will animate the retail industry this year, let’s take a look back at the 2022 National Retail Federation (NRF) “Big Show” in NYC.

Attendees at January’s event were treated to tangible examples of how retail challenges are being solved today, including new solutions to help them parse customer expectations and buying patterns, adapt stores into omni-channel experience hubs, and improve data visibility and actionability.

NRF 2022 also took the “omni-channel everything” theme of last year’s show to the logical next level: Enabling the best hybrid experiences. The message came through loud and clear of the importance of integration and interoperability in this new hybrid world – making everything work well together.

The need for modern digital infrastructure to enable this blending of physical and digital retail smoothly is paramount. To that end, technology vendors demonstrated how digital transformation initiatives, such as contactless and real time IoT and mobile applications, need to be built on cloud, edge, and secure connectivity to allow retailers to achieve the modern seamless hybrid retail that today’s consumer wants.

Other prominent themes and technologies highlighted at NRF included: extending engagement in the metaverse, sustainability, physical and digital security, and the agility and adaptability imperative.

The Metaverse and Hybrid (Omni-channel) Experiences


Today, the metaverse is an extension of our lives, enhanced by technology, which exists as a series of virtual worlds. In the future, the metaverse will be an interconnected, endless world where digital and physical lives fully converge. Imagine waiting for an appointment at a real booth on the NRF show floor while your avatar roams a fully fleshed-out digital NRF, meeting other virtual attendees, stopping for coffee at the digital Starbucks, and paying for a coffee that an in-the-flesh Starbucks employee brings to them. Digital and physical selves merge seamlessly in the metaverse, as the worlds draw closer together.

In the metaverse, brands have a digital presence, too. Nike filed seven trademarks late last year, including those for “Nike,” “Just Do It,” and its swoosh logo, and posted openings for virtual designer roles, indicating its intent to make and sell virtual branded sneakers and apparel. It subsequently purchased RTFKT Studios, a company that already makes and sells NFTs and digital sneakers. (In one collaboration with teenage artist FEWOCiOUS, the company sold 600 pair/NFTs of sneakers in just six minutes to the tune of more than $3.1 million.)

The metaverse also opens possibilities for gathering data about consumers and product demand. Imagine a sneaker drop in the virtual world. Certain styles of new kicks sell like gangbusters, giving the brand insight into what might sell IRL, intelligence that leads to trend-right production and less inventory headed for markdown or landfills. The metaverse can be a vehicle for more sustainable operations.

The metaverse further bridges the narrowing gap between digital worlds and physical worlds. Most consumers aren’t outfitting an avatar, but they are moving between online and offline and expect retailers to accommodate those hybrid omni-channel journeys seamlessly. Those demands have accelerated around last-mile delivery and experiences such as buying online and picking up in store (BOPIS) or at curbside, shopping in store and returning merchandise online, adding items to a BOPIS purchase when at the store, or communicating a substitution to the third-party grocery delivery service

Hybrid experiences open opportunities to please the consumer in new ways, but they also add expense and complexity. The need to meet this demand while enabling profitability was a major theme behind many of the technologies discussed at NRF. These included artificial intelligence (AI) for recommending the right product, return logistics software for defining and guiding product-specific reverse logistics workflows, order orchestration and fulfillment applications for omni-channel shopping, and last-mile delivery visibility for optimizing customer experience, to name a few. Also on display were task management applications help to improve and optimize in-store employee engagement, as well as touch-free applications to allow for faster payments and customer self-service checkout. RFID continues to improve inventory accuracy and inventory locating on the shelf, throughout the store, and the supply chain.

Sustainability


NRF 2022 saw a strong focus on sustainability. An NRF/IBV study released at the show highlighted the significant embrace of sustainable shopping by consumers. According to the survey, 62% of shoppers are “willing to change their purchasing habits to reduce environmental impacts.” About half indicated a willingness to pay a premium – on average a 70% premium – for sustainable products and brands.

Retailers are working to improve sustainability and reduce carbon footprint across operations by using sustainable sourcing through the supply chain, the store, and even returns. Tech vendors unveiled a variety of solutions enabled by cloud/edge, AI, computer vision, and IoT/RFID to allow retailers to effectively measure and record their environmental efforts, with the goal of reducing their impact.

Several cloud and digital infrastructure providers showcased sustainability clouds and other technology aimed at asset management with the goal of reducing energy consumption, water usage, waste. Examples included using IoT sensors to reduce water usage, optimizing re-use of store assets, and dashboards that allow retailers to accurately monitor and measure carbon output. However, such sustainability solutions can be most successful when running on the next-generation digital infrastructure that helps retailers better compete and differentiate in today’s omni-channel world.

Physical and Digital Security


According to a 2021 NRF survey, 57% of U.S. retailers reported the pandemic led to an increase in organized retail crime, while 50% reported an increase in shoplifting. When IDC’s Future Enterprise Resiliency & Spending Survey, Wave 10 (November 2021) asked retailers which digital infrastructure investments would provide the greatest strategic advantage in 2022, their #1 response was “cybersecurity and recovery investments.”

A wide range of technology vendors acknowledged retailer concerns with regards to security, fraud, and loss prevention:

  • Networking, connectivity, and edge vendors highlighted multilayer security solutions that promise to protect data from a range of IoT applications that utilize customer and associate data. Many offer security consulting services to address varied threats including ransomware, retail crime, and loss prevention.
  • Security and e-commerce security vendors showcased solutions to prevent fraud and abuse in e-commerce applications as well as omni-channel applications such as BOPIS and curbside pickup, using AI-based analysis for identifying “bad”/risky customers and mitigating risk.
  • Cloud vendors highlighted how retail clouds provide consistent, reliable identity management and data security.
  • POS/payments/store technology vendors emphasized their ability to handle payments securely from any platform with multifactor tokenization, improved identity techniques such as biometrics and voice authentication, as well as AI-enabled and computer vision solutions for loss prevention at checkout and at the door.

The Agility and Adaptability Imperative


On display at the show were multiple flavors of the digital infrastructure technology that retailers need to achieve agile, personalized, data-driven, integrated seamless operations across the many channels of today’s retail landscape. The emphasis was apt. More than half of retailers plan to boost investment in business agility and operational agility over the next 12 months, according to IDC’s Future Enterprise Resiliency & Spending Survey, Wave 10 (November 2021).

Technology vendors highlighted their connectivity investments to enable business and operational agility and their technology investments for better ease of integration, scalability, and the ability to more easily swap out or mix and match applications with integrated platforms, open systems, hybrid cloud, and retail industry clouds.

Vendors also showed off infrastructure to better harness data while enabling its visibility, maximizing its value, and providing the data-driven personalization essential for competitive advantage and differentiation. Highlights included fast, secure connectivity, 5G and Wifi-6, and edge- and cloud-enabled data and AI platforms to generate real-time insights – all designed to enable today’s omni-channel retail.

Advice for the technology buyer


Retailers should consider these key themes from NRF 2022 when making technology investment decisions for 2022 and beyond. To avoid lagging behind those retailers already moving toward thriving into the future, take action to:

  • Enable the seamless, contactless omni-channel approach that today’s consumers want and expect.
  • Replace legacy infrastructure that was not built to handle the modern retail environment that requires the agility and adaptability to seamlessly connect rapidly increasing volumes of data securely and more quickly than ever.

Whether sustainability, adaptability, the metaverse, or security are top concerns, addressing business needs holistically and strategically should be job #1.

Continue the conversation by downloading our Transforming retail and CPG markets whitepaper today.

Case Study

This Chart, from Home Depot, Dramatically Demonstrates the Power of a Cloud Data Warehouse

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When Home Depot moved it's gigantic enterprise data warehouse to Google Cloud, it could not have imagined how much faster it could crunch data--for a variety of uses cases.

The Home Depot (THD) is the world’s largest home-improvement chain, growing to more than 2,200 stores and 700,000 products in four decades. Much of that success was driven through the analysis of data. This included developing sales forecasts, replenishing inventory through the supply chain network, and providing timely performance scorecards.

However, to compete in today’s business world, THD has taken this data-driven approach to an entirely new level of success on Google Cloud, providing capabilities not practical on legacy technologies.

The Home Depot BigQuery installation performance table
Percent reduction in time that specific workloads took using BigQuery versus on-premises data warehousing.

The pressures of contemporary growth that drove much of the work are familiar to many businesses. In addition to everything it was doing, THD needed to better integrate the complexities in its related businesses, like tool rental and home services. It needed to better empower teams, including a fast-growing data analysis staff and store associates with mobile computing devices. It wanted to better use online commerce and artificial intelligence to meet customer needs, while maintaining better security.

Even before addressing these new challenges, THD’s existing on-premises data warehouse was under stress as more data was required for analytics and data analysts were utilizing the data with increasingly complex use cases. This drove rapid growth of the data warehouse, but also created constant challenges for the team in managing priorities, performance, and cost.

In order to add capacity to the environment, it was a major planning, architecture, and testing effort. In one case, adding on-premises capacity took six months of planning and a three-day service outage. Within a year, capacity was again scarce, impacting performance and ability to execute all the reporting and analytics workloads required. The capacity refresh cycles were shrinking, and the expecations for data were growing. There had to be a better way.

Still, THD did not take its move to the cloud lightly. A large-scale enterprise data warehouse migration involves tremendous effort among people, process, and technology. After careful consideration, THD chose Google Cloud’s BigQuery for its cloud enterprise data warehouse.

BigQuery, a scalable serverless data warehouse, was better on cost, infrastructure agility, and analytics capability, driving better insights with improved performance. There are no service interruptions when capacity is added, and that capacity can be added within a week (and soon same day). It doesn’t require complex system administration, and its standard SQL support means people can easily ramp up quickly. Valuable BigQuery products like Identity and Access Management meant THD could create many separate Google Cloud projects, while ensuring that different teams weren’t interfering with each other or accessing protected data.

THD also utilizes BigQuery’s flat-rate monthly pricing model that allows teams to budget their capacity based on need and provides billing predictability. The capacity not being used by a given project is available for enterprise use. This ensures no surprises when the monthly bill arrives and provides all analytical users access to significant computing power.

While THD’s legacy data warehouse contained 450 terabytes of data, the BigQuery enterprise data warehouse has over 15 petabytes. That means better decision-making by utilizing new datasets like website clickstream data and by analyzing additional years of data.

As for performance, look at this chart:

With the cloud EDW migration complete, and the legacy on-premises data warehouse retired, analysts now execute more complex and demanding workloads that they would not have been able to complete before, such as utilizing Datalab for orchestrating analytics through Python Notebooks, utilizing BigQuery ML for machine learning directly against the BigQuery data (no movement of large datasets), and AutoML to help determine the best model for predictions.

Additionally, engineers at THD have adapted BigQuery to monitor, analyze, and act on application performance data across all its stores and warehouses in real time, something that was not practical in the on-premises system.

With over 600 projects that THD now has on Google Cloud, the BigQuery story is just one of the many ways that Google Cloud is working with THD to deliver meaningful business results, every day.

Blog

Google Cloud Leads the Landscape for Unstructured Data Security Platform: Forrester

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Google Cloud has led the frontline for helping move sensitive data to the cloud and build customers' trust. Read more from The Forrester Wave™: Unstructured Data Security Platforms, Q2 2021 report to learn why Google Cloud leads this landscape.

As organizations expand their use of cloud computing services, more of their sensitive data inevitably moves to and lives in the cloud. Much of this sensitive data is unstructured and can be challenging to secure. Despite this potential challenge, the usefulness of cloud for data storage and processing is too big for most organizations to ignore and has in turn led to data sprawl, where their sensitive data is spread over many resources, both in the cloud and on-premise. Addressing data sprawl requires solutions that can discover, manage, and secure sensitive data, especially unstructured data, as it spreads.

To help organizations confidently move their sensitive data to the cloud, Google Cloud works diligently to earn and maintain customer trust. Control and transparency are pillars of our approach to offering a trusted cloud. Therefore, we’ve been expanding our capabilities to act on unstructured data as sprawl increases.

Given the importance of these capabilities to our strategy, we are happy to announce today that Forrester Research has named Google Cloud a Leader in The Forrester Wave™: Unstructured Data Security Platforms, Q2 2021 report, and rated Google Cloud highest in the current offering category among the providers evaluated.

gcp forrester security.jpg

The report evaluates the 11 most significant providers with platform solutions to secure and protect unstructured data, spanning from cloud providers to data security-focused vendors. The report notes that “Google offers breadth and depth with built-in data security in the cloud. Google Cloud Platform, Google Workspace, and BeyondCorp Enterprise have underlying data security products and features for protecting customer data.”

Google Cloud tools focused on protecting unstructured data were developed and battle-tested internally at Google to alleviate some of our own data security challenges. This brings the best of Google security to the organizations utilizing Google Cloud and our security tools. The report highlights that “Google productizes capabilities originally developed to secure its own business, and brings a disciplined approach to product enhancements for enterprise requirements. It serves a wide range of enterprise and mid-market, with a focus on emphasizing data protection needs by industry. ”

Google Cloud’s data security strategy focuses on meeting customers wherever they are in their cloud migration journey. The report highlights that “Google further enables a Zero Trust approach with third-party integrations through its BeyondCorp Alliance of partners in device management, endpoint security and gateways.”

Google Cloud received the highest possible score in sixteen criteria, in total receiving the most 5 out of 5 ratings among all vendors assessed. These criteria include: Data Intelligence, Access Control, Deletion, Obfuscation-Scope, Obfuscation-Key Management, Deployment, Security and Risk, APIs and Integration, Data Security Platform Vision, Data Security Execution Roadmap, Performance, Planned Enhancements, Zero Trust Enabling Partner Ecosystem, Diversity, Equity and Inclusion, Installed Base, and Revenue. 

Notably, Google Cloud received the highest possible score in the Obfuscation criteria. Obfuscation can help protect sensitive data, like personally identifiable information (PII), which is critical to many enterprise workflows. Cloud DLP helps customers inspect and mask this sensitive data with techniques like redaction, bucketing, and tokenization, which help strike the balance between risk and utility. This is especially crucial when dealing with unstructured or free-text workloads, in which it can be challenging to know what data to redact. More than 150 detectors combine to power Cloud DLP’s masking, which can be deployed in data migrations and business workloads like real-time data collection and processing. For Obfuscation specifically, the report mentioned that Google “takes a broad view of DLP, which includes in-line redaction of sensitive elements in unstructured data and DLP APIs that extend support to additional data types like images or other media.”

We are honored to be a Leader in The Forrester Wave™ Unstructured Data Security Platforms Q2 2021 report, and look forward to continuing to innovate and partner with you on ways to make your digital transformation journey safer as we work to become your most trusted Cloud.

A copy of the full report can be viewed here.

Blog

Transforming Canadian Healthcare and Medical Research with Google Cloud

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Explore the transformative journey of Canadian healthcare's adoption of Google Cloud. Learn about key challenges, mitigation strategies, and the critical role of security assessments in ensuring a safe, modernization process.

Is Cloud an option for Canadian Healthcare healthcare and medical research organizations?

Yes, Canadian healthcare and medical research organizations are moving to the cloud. The cloud market is expected to grow in Canada significantly through 2027.

There are several reasons why Canadian healthcare and medical research organizations are moving to the cloud. 

  • Reduce costs by eliminating the need to invest in and maintain on-premises infrastructure. 
  • Enable the healthcare research community to drive their research more expediently to clinical outcomes
  • Improve patient satisfaction by making it easier for patients to access their health information and communicate with their providers.
  • Improve the quality of care by providing access to patient data and records from anywhere in the country. 

Overall, the transition to the cloud is a positive development for Canadian healthcare and medical research organizations. 

Canadian healthcare providers face many challenges before they can move to the cloud, such as addressing security and privacy concerns, data sovereignty issues, and ensuring interoperability. To help them overcome these challenges, it is important to provide Healthcare Data Custodians, Infrastructure Architects, and Research Leads with clear guidance on how the cloud can align with Canadian Healthcare Regulations. This will allow them to have a practical understanding of what is required to enhance their cloud journey and facilitate a smoother transition to the cloud.

iSecurity and MD+A Health are actively assisting Canadian healthcare and medical research organizations in comprehending the risks and exploring pathways to embrace the cloud. Through extensive research and analysis, iSecurity and MD+A Health have evaluated Google Cloud as a suitable platform for healthcare. Their diligent efforts have resulted in the production of comprehensive documents that detail their findings via a Threat Risk Assessment (TRA) and a Privacy Impact Report (PIA).

Why a Threat Risk Assessment? 

A threat risk assessment is a process of identifying and evaluating threats to an organization and then determining the likelihood and impact of those threats. The goal of a threat risk assessment is to identify the most serious threats and develop mitigation strategies to reduce the likelihood and impact of those threats.

A threat risk assessment typically involves the following steps:

  1. Identify threats: The first step is to identify all potential threats to the organization. This can be done by brainstorming, interviewing experts, or reviewing historical data.
  2. Evaluate threats: Once the threats have been identified, they need to be evaluated in terms of their likelihood and impact. The likelihood of a threat is the probability that it will occur, while the impact of a threat is the severity of the consequences if it does occur.
  3. Prioritize threats: The threats need to be prioritized based on their likelihood and impact. The most serious threats should be addressed first.
  4. Develop mitigation strategies: Once the threats have been prioritized, mitigation strategies need to be developed to reduce the likelihood and impact of those threats. Mitigation strategies can include things like implementing security controls, training employees, and developing contingency plans.
  5. Implement mitigation strategies: The mitigation strategies need to be implemented and tested to ensure that they are effective.
  6. Monitor and review: The threat risk assessment should be monitored and reviewed regularly to ensure that it is still effective.

Why a Privacy Impact Assessment?

A Privacy Impact Assessment (PIA) is a process that organizations use to identify and assess the privacy risks associated with a new or changed information technology (IT) system or project. The goal of a PIA is to help organizations protect the privacy of individuals whose personal information is collected, used, or disclosed by the IT system or project.

PIAs typically include the following steps:

  1. Identifying the purpose of the IT system or project and the types of personal information that will be collected, used, or disclosed.
  2. Identifying the privacy risks associated with the IT system or project.
  3. Assessing the likelihood and severity of the risks.
  4. Developing and implementing controls to mitigate the risks.
  5. Monitoring the effectiveness of the controls.

PIAs are an important tool for organizations to help them follow privacy laws and regulations. They can also help organizations build trust with their patients, employees and the research community by demonstrating their commitment to protecting privacy.

The benefits of conducting a PIA:

  • Helps organizations identify and assess privacy risks
  • Helps organizations develop and implement controls to mitigate privacy risks
  • Helps organizations comply with privacy laws and regulations
  • Helps organizations build trust with customers and employees

Why Google Cloud?

Google Cloud is committed to providing Canadian healthcare organisations with an environment to expand both their clinical and research environments. Google Cloud has invested significant resources into building out a cloud environment based on best practices coming from Google’s experience running some of the world’s largest platforms.  

Some highlights include:

  • Built-in security features that help protect your data and applications from unauthorized access, use, disclosure, disruption, modification, or destruction.
  • A comprehensive security management platform that helps you assess, prioritize, and address security risks across your organization.
  • A team of security experts who can help you design, implement, and manage your security solutions.
  • A wide range of security training and resources to help you learn about and stay up-to-date on the latest security threats and best practices.
iSecurity’s thorough, independent PIA and TRA assessments of Google Cloud will help Canadian healthcare organisations, such as ours, review the effectiveness of Google Cloud’s security and privacy controls. These assessments provide additional confidence in the validation of Google Cloud’s critical controls, a clear understanding of customer responsibilities and ultimately will help accelerate the migration of patient and research data to the cloud.
-Kashif Parvaiz, Regional CISO, University Health Network (UHN)
Blog

Accelerating Success: Tips and Techniques for Optimizing and Scaling Your Startup

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Maximize the impact of your startup by learning from the Build Series. In this series, we'll cover the key elements of growth and show you how to optimize and scale your business for success. Read more.

At Google Cloud, we want to provide you with the access to all the tools you need to grow your business. Through the Google Cloud Technical Guides for Startups, leverage industry leading solutions with how-to video guides and resources curated for startups.

This multi-series contains 3 chapters: Start, Build and Grow, which matches your startup’s journey:

  • The Start Series: Begin by building, deploying and managing new applications on Google Cloud from start to finish.
  • The Build Series: Optimize and scale existing deployments to reach your target audiences.
  • The Grow Series: Grow and attain scale with deployments on Google Cloud.

Additionally, at Google we have the Google for Startups Cloud Program, which is designed to help your business get off the ground and enable a sustainable growth plan for the future. The start of the Build Series delineates the benefits of the program, the application process, and more to help your business get started on Google Cloud.

A quick recap of the Build Series

Once you have applied for the Google for Startups Cloud Program, there’s so much to explore and try out on Google Cloud.

Figuring out a rapid but solid application development process can be key to many businesses in reducing time to market. Furthermore, learning what database to use to handle application data can be tricky. Deep dive into our Firestore video which walks through how Firestore can help you unlock application innovation with simplicity and speed.

We then move on to a deep dive into BigQuery and how it can help businesses. BigQuery is designed to support analysis over petabytes of data regardless of whether it’s structured or unstructured. This video is the goto video for getting started on BigQuery!

If you are someone looking to run your Spark and Hadoop jobs faster and on the cloud, look to Dataproc. To learn more about Dataproc and how this has helped other customers with their Hadoop clusters, click the video below to learn all things Dataproc related.


Next, we find out what Dataflow can bring to your business; some advantages, sample architectures, demos on the console, and how other customers are using Dataflow.

We also talked about Machine Learning, starting from selecting the right ML solution to Machine Learning APIs on cloud to exploring Vertex AI. Following that we look into API management in Google Cloud and how Apigee helps operate your APIs with enhanced scale, security, and automation.


We ended the series with the last two episodes focusing around security deep-dive and using Cloud Tasks and Cloud Scheduler.

Coming up next – The Grow Series

Dive into the next chapter of this multi-series, with our upcoming Grow Series, where we will be focusing on growing and attaining scale with deployments on Google Cloud.

Check out our website and join us by checking out the video series on the Google Cloud Tech channel, and subscribe to stay up to date. 

See you in the cloud!

Blog

Taking Partnership forward: Google Cloud VMware Engine Now in VMware Cloud Universal

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Google Cloud is the go-to place to many organizations looking to safely migrate VMware workloads. Nearly 2 years since the launch of Google Cloud VMware Engine, we have taken the partnership a step ahead by making it a part of VMware Universal Cloud!

As the pace of digital transformation accelerates, our partnership with VMware continues to focus on helping customers successfully navigate their cloud journey and achieve their business objectives through seamless and rapid migration of business critical VMware workloads.

We announced the general availability of Google Cloud VMware Engine in May 2020. Since then we have worked closely with VMware to make it easier for customers to quickly migrate and run business-critical, VMware-based workloads on Google Cloud. Customers are already leveraging the service across a variety of use cases including application migration, datacenter exit, virtual desktop infrastructure, disaster recovery, and spinning up new capacity quickly to meet business needs.

For example, retailer Carrefour migrated its on-premises VMware workloads to Google Cloud without disruption to shoppers or employees while reducing operating costs by 40% and energy consumption by 45%. Once in the cloud, Carrefour was able to leverage its data and AI to deliver innovative customer experiences across online and in-store channels. Similarly, telecommunications provider Mitel migrated thousands of VMware instances across 30 data centers to Google Cloud in less than 90 days, quickly achieving increased stability, scale, and security.

Today, we announced the continued growth of the Google Cloud and VMware partnership with the addition of Google Cloud VMware Engine within VMware Cloud Universal. Google Cloud VMware Engine delivers a cloud-native VMware experience and enables you to rapidly migrate to the cloud without changes to your apps, policies, or tools. Once you migrate your VMware workloads to Google Cloud, you can accelerate digital transformation through seamless access to services such as BigQuery for real-time data analytics and cloud-native container-based architectures on Kubernetes.

With VMware Cloud Universal, you will be able to accelerate migrations of your workloads and applications to Google Cloud through purchase of Google Cloud VMware Engine from VMware and its partners, allowing you to flexibly purchase credits, and leverage existing spend and unused VMware Cloud Universal credits. The program will offer the following benefits:

  • Financial flexibility by letting you redeem VMware Cloud Universal credits for Google Cloud VMware Engine
  • Streamlined consumption by enabling you to burn down your Google Cloud commits while purchasing from VMware
  • Use of existing VMware licensing investments through the VMware Cloud Universal program for Google Cloud VMware Engine

With Google Cloud VMware Engine, you can take advantage of Google Cloud’s highly performant, scalable infrastructure with fully redundant and dedicated 100 Gbps networking, providing 99.99% availability to meet the needs of the most demanding workloads at very low costs. By providing a consistent VMware environment natively in Google Cloud, you can quickly migrate your VMware workloads to Google Cloud without changes. Deep and unique networking integrations and capabilities such as multi-region and multi-VPC connectivity, further ease the migration of complex enterprise networking topologies to Google Cloud. With rapid provisioning of private clouds across 13 global regions, you can also take advantage of on-demand capacity to serve your infrastructure needs with a cloud-native VMware environment in Google Cloud.Once in the cloud, you can take advantage of other Google Cloud services such as BigQuery and Cloud Operations to gain data-driven insights and unify operations.

Getting started


With Google Cloud VMware Engine as part of VMware Cloud Universal, Google Cloud is a compelling cloud destination for your VMware workloads. You can learn more about how to get started with the service and get additional detail around use cases and pricing on our website.

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