When you choose to run your business on Google Cloud you benefit from the same planet-scale infrastructure that powers Google’s products such as Maps, YouTube, and Workspace. 

We have picked 10 ways in which Google Cloud Infrastructure services outshine alternatives in the market in how they simplify your operations, save money, and secure your data. 

1. Custom Machine Types means no wasted resources

Compute Engine offers predefined machine types that you can use when you create a VM instance. A predefined machine type has a preset number of vCPUs and a preset amount of memory; each type is billed at a set price as described on the Compute Engine pricing page. 

If predefined machine types don’t meet your needs, you can create a VM instance with a custom number of vCPUs and custom amount of memory, effectively building a custom machine type. Custom machine types are available only for general-purpose machine families. When you create a custom machine type, you are deploying a custom machine type from the E2, N2, N2D, or N1 machine family on GCP.  No other leading cloud vendor offers custom machine types so extensively.

Custom machine types are a good idea for workloads that aren’t a good fit for the predefined machine types and for workloads that require more processing power or memory but don’t need all of the upgrades provided by the next machine type level. This translates into lower operating costs.   They are also useful for controlling software licensing costs that are based on the number of underlying compute cores. 

Jeremy Lloyd, Infrastructure and Application Modernization Lead at Appsbroker, a Google partner: 

“Custom machine types coupled with Google’s StratoZone data center discovery tool provides Appsbroker with the flexibility we need to provide cost efficient virtual machines matched to a virtual machine’s actual utilization. As a result, we are able to keep our customers’ operating costs low while still providing the ability to scale as needed.”

2. Compute Engine Virtual Machines are optimized for scale-out workloads 

For scale-out workloads, T2D, the first instance type in the Tau VM family, is based on 3rd Gen AMD EPYC processors and leapfrogs VMs for scale-out workloads of any leading public cloud provider today, both in terms of performance and price-performance. Tau VMs offer 56% higher absolute performance and 42% higher price-performance compared to general-purpose VMs from any leading public cloud vendor (source). The x86 compatibility provided by these AMD EPYC processor-based VMs gives you market-leading performance improvements and cost savings, without having to port your applications to a new processor architecture. Sign up here  if you are interested in trying out T2D instances in Preview. 

For SAP HANA, Google Cloud has demonstrated with SAP how we can run the world’s largest scale-out HANA system in the public cloud (96TB).   With such innovation, you are covered as your business grows exponentially.

3. Largest single node GPU-enabled VM

Google is the only public cloud provider to offer up to 16 NVIDIA A100 GPUs in a single VM, making it possible to train very large AI models. Users can start with one NVIDIA A100 GPU and scale to 16 GPUs without configuring multiple VMs for single-node ML training, without crossing the VM layer. 

Additionally, customers can choose smaller GPU configurations—1, 2, 4 and 8 GPUs per VM—providing the flexibility to scale their workload as needed. 

The A2 VM family was designed to meet today’s most demanding applications—workloads like CUDA-enabled machine learning (ML) training and inference, for example. This family is built on the A100 GPU which offers up to 20x the compute performance compared to the previous generation GPU and comes with 40 GB of high-performance HBM2 GPU memory. To speed up multi-GPU workloads, the A2 VMs use NVIDIA’s HGX A100 systems to offer high-speed NVLink GPU-to-GPU bandwidth that delivers up to 600 GB/s. A2 VMs come with up to 96 Intel Cascade Lake vCPUs, optional Local SSD for workloads requiring faster data feeds into the GPUs and up to 100 Gbps of networking. A2 VMs provide full vNUMA transparency into the architecture of underlying GPU server platforms, enabling advanced performance tuning. Google Cloud offers these GPUs globally. 

4. ​​Non-disruptive maintenance means you worry less about planned downtime

Compute Engine offers live migration (non-disruptive maintenance) to keep your virtual machine instances running even when a host system event, such as a software or hardware update, occurs. Google’s Compute Engine live migrates your running instances to another host in the same zone without requiring your VMs to be rebooted. Live migration enables Google to perform maintenance that is integral to keeping infrastructure protected and reliable without interrupting any of your VMs. When a VM is scheduled to be live-migrated, Google provides a notification to the guest that a migration is imminent. 

Live migration keeps your instances running during:

• Regular infrastructure maintenance and upgrades
• Network and power grid maintenance in the data centers
• Failed hardware such as memory, CPU, network interface cards, disks, power, and so on. This is done on a best-effort basis; if a hardware component fails completely or otherwise prevents live migration, the VM crashes and restarts automatically and a hostError is logged.
• Host OS and BIOS upgrades
• Security-related updates
• System configuration changes, including changing the size of the host root partition, for storage of the host image and packages

Live migration does not change any attributes or properties of the VM itself. The live migration process transfers a running VM from one host machine to another host machine within the same zone. All VM properties and attributes remain unchanged, including internal and external IP addresses, instance metadata, block storage data and volumes, OS and application state, network settings, network connections, and so on. This has the benefit of reducing operational and maintenance overhead, helps you build a more robust security posture where infrastructure can be consciously revamped from a known good state and minimizes risks for advanced persistent threats. 

Refer to Lessons learned from a year of using live migration in production on Google Cloud from the Google engineering team.

5. Trusted Computing: Shielded VMs guard you against advanced, persistent attacks

Establishing trust in your environment is multifaceted, involving hardware and firmware, as well as host and guest operating systems. Unfortunately, threats like boot malware or firmware rootkits can stay undetected for a long time, and an infected virtual machine can continue to boot in a compromised state even after you’ve installed legitimate software. 

Shielded VMs can help you protect your system from attack vectors like:

• Malicious guest OS firmware, including malicious UEFI extensions
• Boot and kernel vulnerabilities in the guest OS
• Malicious insiders within your organization

To guard against these kinds of advanced persistent attacks, Shielded VMs use:

• Unified Extensible Firmware Interface (UEFI) BIOS: Helps ensure that firmware is signed and verified
• Secure and Measured Boot: Helps ensure that a VM boots an expected, healthy kernel
• Virtual Trusted Platform Module (vTPM): Establishes root-of-trust, underpins Measured Boot, and prevents exfiltration of vTPM-sealed secrets
• Integrity Monitoring: Provides tamper-evident logging, integrated with Stackdriver, to help you quickly identify and remediate changes to a known integrity state

The Google approach allows customers to deploy Shielded VMs with only a simple click, thereby easing implementation. 

6. Confidential Computing encrypts data while in use

Google Cloud was a founding member of the Confidential Computing Consortium. Along with encryption of data in transit and at rest using customer-managed encryption keys (CMEK) and customer-supplied encryption keys (CSEK), Confidential VM adds a “third pillar” to the end-to-end encryption story by encrypting data while in use. Confidential Computing uses processor-based technology that allows data to be encrypted in use while it is being processed in the public cloud. Confidential VM allows you to to encrypt memory in use on a Google Compute Engine VM by checking a single checkbox. 

All Confidential VMs support the previously mentioned Shielded VM features under the covers—you can think of Shielded VM as helping to address VM integrity, while Confidential VM addresses the memory encryption aspect which relies on CPU features. With the confidential execution environments provided by Confidential VM and AMD Secure Encrypted Virtualization (SEV), Google Cloud keeps customers’ sensitive code and other data encrypted in memory during processing. Google does not have access to the encryption keys. In addition, Confidential VM can help alleviate concerns about risk related to either dependency on Google infrastructure or Google insiders’ access to customer data in the clear. 

See what Google Cloud partners say about Confidential Computing here. 

7. Advanced networking delivers full-stack networking and security services with fast, consistent, and scalable performance

Google Cloud’s network delivers low latency, reduces operational costs and ensures business continuity, enabling organizations to seamlessly scale up or down in any region to meet business needs. Our planet-scale network uses advanced software-defined networking and security with edge caching services to deliver fast, consistent, and scalable performance. With 28 regions, 85 zones, and 146 PoPs connected by 16 subsea fiber cables around the world, Google Cloud’s network offers a full stack of layer 1 to layer 7 services for enterprises to run their workloads anywhere. Enterprises can be assured that they have best-in-class networking and security services connecting their VMs, containers, and bare metal resources in hybrid and multi-cloud environments with simplicity, visibility, and control. 

Google Cloud’s network has protected customers from one of the world’s largest DDoS attacks at 2.54 Tbps. With our multi-layer security architecture and products such as Cloud Armor, our customers ran their business with no disruptions. Furthermore, our recent integration of Cloud Armor with reCAPTCHA Enterprise adds best-in-class bot and fraud management to prevent volumetric attacks. Cloud Armor is deployed with our Cloud Load Balancer and Cloud CDN, extending the secure benefits at the network edge for traffic coming into Google Cloud so customers have security, performance, and reliability all built in. Furthermore, we are excited to offer Cloud IDS in preview, which was co-developed with security industry leader, Palo Alto Networks, to run natively in Google Cloud. 

Our advanced networking capabilities also extends to GKE and Anthos networking. With the GKE Gateway controller, customers can manage internal and external HTTPS load balancing for a GKE cluster or a fleet of GKE clusters with multi-tenancy while maintaining centralized admin policy and control. Unlike other Kubernetes offerings, we offer eBPF dataplane which brings powerful tooling such as Kubernetes network policy and logging to GKE. eBPF is known to kernel engineers as a “superpower” for its unique architecture to load and unload modules in kernel space, and now this capability is built in with Google Cloud networking. 

For observability and monitoring, our customers deploy Network Intelligence Center, Google Cloud’s comprehensive network monitoring, verification and optimization platform. With four key modules in Network Intelligence Center, and several more to come, we are working towards realizing our vision of proactive network operations that can predict and heal network failures, driven by AI/ML recommendations and remediation. Network Intelligence Center provides unmatched visibility into your network in the cloud along with proactive network verification. Centralized monitoring cuts down troubleshooting time and effort, increases network security and improves the overall user experience.  

8. Regional Persistent Disk for High Availability

Regional Persistent Disk is a storage option that provides synchronous replication of data between two zones in a region. Regional Persistent Disks can be a great building block if you need to ensure high availability of your critical applications as they offer cost-effective durable storage and replication of data between two zones in the same region. 

Regional Persistent Disks are also easy to set up within the Google Cloud Console. If you are designing robust systems or high availability services on Compute Engine, Regional Persistent Disks combined with other best practices such as backing up your data using snapshots enable you to build an infrastructure that is highly available and recoverable in a disaster. Regional Persistent Disks are also designed to work with regional managed instance groups. In the unlikely event of a zonal outage, Regional Persistent Disks allow continued I/O through failover of your workloads to another zone. Regional Persistent Disks can help meet zero RPO and near-zero RTO requirements and other stringent SLAs that your critical applications might require by maximizing application availability and protection of data during events such as host/VM failures and zonal outages. 

9. Cloud Storage’s single namespace for dual-region and multi-region means managing regional replication is incredibly simple

Similar to how Persistent Disk makes data more available by replicating data across zones, Cloud Storage provides similar benefits for object storage. Cloud Storage within a region is cross-zone by definition, reducing the risk that a zonal outage would take down your application. Cloud Storage adds to this by also providing a cross-region option that can protect against a regional outage and gets your data closer to distributed users. This comes in the form of Dual-region or Multi-region settings for a bucket. These are the simplest to implement cross-region replication offerings in the industry—just a simple button or API call to enable them. In addition to being simple to implement, they offer an added advantage of using a single bucket name that spans regions. 

This is unique in the industry. Competitive offerings currently require setting up and managing two distinct buckets, one in each region and they don’t offer the strong consistency properties Cloud Storage offers across regions. Operations and app development are burdened by this design. Google’s single namespace approach dramatically simplifies application development (the app runs on single region or dual/multi-region without any changes), and provides simpler application restarts and testing for DR.

10. Predictive autoscaling 

Customers use predictive autoscaling to improve response times for applications with long initialization times or for applications with workloads that vary predictably with daily or weekly cycles. When you enable predictive autoscaling, Compute Engine forecasts future load based on your Managed Instance Group’s history and scales out the MIG’s in advance of predicted load, so that new instances are ready to serve when the load arrives. Without predictive autoscaling, an autoscaler can only scale a group reactively, based on observed changes in load in real time. 

With predictive autoscaling enabled, the autoscaler works with real-time data as well as with historical data to cover both the current and forecasted load. Forecasts are refreshed every few minutes (faster than competing clouds) and consider daily and weekly seasonality, leading to more accurate forecasts of load patterns.

For more information, see How predictive autoscaling works and Checking if predictive autoscaling is suitable for your workload.

These are just a few examples of customer-centric innovation that set Google Cloud infrastructure apart.  Bring your applications and let the platform work for you.   

Get started by learning about your options for migration, or talk to our sales team to join the thousands of customers who have embarked upon this journey.

Acknowledgement

Special thanks to Dheeraj Konidena (Google) for contributing to this article.

Editor’s note: Coming out of Mobile World Congress 2022, we are excited to share key learnings from our partner ecosystem on how to leverage advancements in 5G technologies to power customer experiences that seamlessly blend our physical and virtual world into one. The original version of this blog was published by Optiva, Inc. Please enjoy this updated entry from our partner.

Telecom operators and communications service providers (CSPs) are elevating customer experiences (CX) across the customer lifecycle. Today’s digital customers’ expectations, needs, usage behaviors and choices are growing and evolving exponentially. Therefore, it is critical to deliver superior and personalized digital customer experiences at each customer lifecycle touchpoint.

To succeed, you need to deliver a dynamic customer experience. Operators are embracing the mantra — next-level CX is the new currency — from onboarding and instant offer provisioning to delivering enhanced self service and supporting subscription renewals, queries and billing actions, and in-session improved experiences. There are commercial benefits to adapting to this paradigm, too, as key customer segments may see added value in enhanced experiences. With 5G, the Ericsson “5G consumer potential” report found that half of early adopters would be willing to pay 32% more for 5G services. Consider the advanced experiences that 5G is able to support, such as:

• Low-latency connectivity and real-time network slicing capabilities, delivering an immersive yet reliable augmented and virtual reality (AR/VR) experience. Imagine a soccer match with a rich 360-degree stadium experience from the customer’s choice of location that immerses a fan in the game excitement.
• AI-driven insights enabling operators to predict customer behavior patterns in real time and leveraging available network capacity to provide customers with personalized, just-in-time discounts and offers that can increase ARPU, enhance the customer experience and reduce churn.
• Proactive action, such as instantly optimizing 5G connectivity network slice bandwidth when the quality of service does not meet its promised level. This could include delivering assured, lag-free network performance to an online gamer for next-level gaming intensity or it could be about providing proactive, transparent reimbursements to end customers on the fly, preventing dissatisfaction complaints. Further, 5G with dedicated network slices also enables business applications that exceed an end-to-end SLA essential to a business-to-business (B2B) subscriber.
• Enabling immersive experiences across all services and touchpoints by redefining how consumers interact with offerings from anywhere, whether that’s a smartphone or tablet. What’s more, it’s about feeding intelligence gleaned from those customer interactions into a single view across all ecosystems in real time to gain a full picture of the customer.

How cloud shapes the future of telecom customer experience

Through cloud technology and cloud-native architectures, telecom operators and service providers have the opportunity to deliver such 5G use cases and differentiated offerings. Cloud maximizes the benefits and enables delivery, thereby dramatically improving and reimagining the possibilities for CX. This includes how customers connect, consume and buy services, and it strengthens customer affinity and loyalty.

Cloud and the technologies it maximizes, such as 5G, also present a wide range of innovative monetization opportunities beyond traditional telecom revenue streams and beyond connectivity. Thus, the highest priority for telecom must be on effectively and efficiently harnessing the potential capabilities for launching personalized service offerings for consumer and enterprise at a high velocity. As a result, the new customer engagement model requires agility, responsiveness and reliability to deliver these services across all touchpoints of the customer’s journey.

As such, Optiva and Google Cloud are engaging in a multi-year partnership to help CSPs enable faster time to innovation, flexible 5G monetization and operational cost savings, while driving strong customer experience. Leveraging the Google Cloud platform enabled by Anthos, which supports the deployment and operation of business support system (BSS) applications across public clouds, on-premises data centers and at the network edge, Optiva’s distributed solution deployment offers telecom operators new ways to monetize 5G networks through use cases such as private 5G, IoT and ultra-low latency edge solutions.

Gaining a competitive edge on the new playing field

The solution to these new BSS and monetization requirements lies in the cloud’s unique advantages. For example, to achieve agility, an essential cloud tool, the sandbox, allows operators to accelerate iterations to find optimal solutions. The sandbox shortens product cycles to a fraction of traditional timelines and empowers operators to reinvent their functionalities and service capabilities — lowering business risk and driving dramatic cost savings.

As a result, operators can increasingly explore, experiment, learn, launch and relaunch rapidly. This allows for the fast introduction of new and differentiated offerings, increased service velocity and cost-effective go-to-market opportunities. For that reason, a new competitive playing field is emerging and making the days of traditional and full digital transformations a thing of the past.

Instead, by leveraging cloud technologies, customer lifecycle opportunities and possibilities are born, such as:

• End-to-end digital onboarding experiences: Hassle-free digital customer onboarding in little time by leveraging next-gen BSS with embedded automation across the different modules. This digitizes the customer registration and ordering process, including customer verification, SIM allocation, and the selection and activation of a user’s choice of plans and more.
• Real-time offer optimization based on customer insights: On-the-fly optimization of offers based on AI-driven real-time insights to predict usage behavior.
• Handling ultra-low latency service quality with distributed systems: Delivering and charging for ultra-fast services from the edge rather than sending and processing them at a central cloud. This enables new business opportunities by leveraging new private 5G offerings.
• Assured service quality and complaint reduction through automated real-time network configuration: By consistently monitoring the network quality and application and taking corrective actions to match the SLA requirements, we can boost the user experience (e.g., if a user subscribes to an 8K video plan). Thus, if the bandwidth level drops below the agreed-upon resolution level, the service can push an update to the user and potentially offer them a complimentary added data bundle leveraging analytics, churn prediction models and insights.
• Maintaining a real-time single source of truth for customer data: Having a single, distributed repository of real-time updated customer data allows CSPs to deliver customer services more smoothly across all touchpoints.
• Expanding product catalog with a partner ecosystem: Leveraging open APIs to build and expand partner ecosystems to launch new products and services that enable CSPs to expand the services they provide customers and help increase their market relevance.

Cloud momentum accelerates, enabling revolutionized BSS and revenue models

Service providers are forging their paths and investing in and adopting cloud technologies. Cloud empowers operators beyond connectivity and volume offerings on data, text and voice. The technology offers more and unlocks the operator’s ability to meet specific user segment experience requirements in real time and differentiate offerings based on latency, capacity, throughput, speed and device type.

As a result, operators can shift to new product-driven monetization capabilities, allowing them to configure their BSS without heavy customizations or necessitating the expertise of their IT teams. Instead, they can now empower, for example, marketing teams — with minimal steps and product-specific expertise needed — to optimize rate plans in real time based on usage and experience analytics, roll out promotions and satisfy customer demand for a delightful experience.

The new currency across the customer lifecycle — next-level telecom BSS and CX

Operators need the capability to learn fast, fail fast, launch, and relaunch in quick cycles. This capability is growing more critical as Capex and Opex become challenged and protecting ARPU and increasing subscribers becomes harder in a cloud economy. Telecom operators are picking up speed for cloudification and reimagining the potential of their BSS systems. And with 5G, innovation driven by cloud-native capabilities and automation via machine learning, operators have a genuine opportunity to revolutionize customer engagement and deliver a next-level hyper-personalized CX — the new currency of 5G cloud.

As Google Cloud has become a choice for more startups, I’ve experienced an increase in founders asking how they should think about cloud services. Though each startup is different and requirements may vary across industries and regions, I’ve seen a few core best practices that help startups to succeed—as well as several traps to avoid. 

For example, If you go with a public cloud provider, you’re ideally not starting from ground zero like you would running your own data center, but it’s important not to introduce similar complexity in a virtualized environment. Just because you’re using public cloud infrastructure doesn’t mean you want to manage it.

Instead, you want to leverage platforms that abstract away complexity so your team can focus on delivering value to customers. That’s where serverless comes in. Serverless platforms are fully managed by the provider, offering automatic scaling for workloads, as well as provisioning, configuring, patching, and management of servers and clusters. Freed from these resource-intensive tasks, your technical talent can focus on the things that differentiate your business, not on IT curation. 

This applies to not only running stateless applications, but also managing and analyzing data. You should be collecting data points about which features are most popular on your platform, what people are buying, the types of activities that help your customers get their jobs done, and so on. This information is essential to building and executing on a product roadmap that will serve your customers. However, it’s not enough to collect this data, you need to make your data accessible, secure, and easy for your team to analyze—so where do you run and host it? 

On Google Cloud, this is where options like Spanner and Cloud SQL can play a large role, as can BigQuery for analysis. You won’t have to worry about standing up infrastructure or patching servers—you can just stream your data to our data management platforms, where it’s available whenever someone needs to run a query. By leveraging a serverless architecture, your startup can be data-driven without having to invest in the traditional complexity of database administration and management—and that can significantly change your playing field. 

Serverless is just one of the factors you should consider as you build out your tech stack. To hear my thoughts on a range of other topics relevant to startups — such as security, cloud credits, and the differences among managed services — check out the below video or visit our Build and Grow page.

https://www.youtube.com/embed/gn4RjLbs8Hc?enablejsapi=1&

COVID-19 drastically changed the way consumers purchased goods and services, but these changes merely accelerated trends that were well underway. While many retailers were caught off guard with the suddenness of the transition, most are stepping up their cloud transformation initiatives in response to changes in consumer behavior and expectations — changes that are likely to be permanent. These retailers realize they need to migrate on-premises workloads to the cloud to achieve the speed and responsiveness required to better promote their products, expand customer support, predict demand levels, and meet ever-rising customer expectations. The trick will be to do so as quickly, efficiently and cost-effectively as possible while minimizing disruption.  By leveraging solutions such as Google Cloud VMware Engine, retailers can move their on-premises applications to the cloud, where they can achieve the scale, intelligence, and speed required to stay relevant and competitive. 

Gaining the cloud advantage

In a recent survey from MIT¹, 75% of retail IT leaders said the pandemic had accelerated their digital transformation projects to improve business processes, increase operational efficiency, and enhance customer experience. Cloud computing is at the heart of digital transformation. It gives retailers the scale, analytical power, and agility they need to respond to the increasing pace of change. By migrating IT resources to the cloud, retailers can develop and deploy innovative mobile apps, virtualize costly services such as call centers, automate business processes, and analyze massive volumes of data to improve the speed and accuracy of demand forecasts. Running applications in the cloud enables business managers and IT departments to replicate the functions of their on-premises system without changes, so that employees, customers, and partners can access those systems from anywhere and at any time. Operating in the cloud also allows retailers to avoid many of the limitations of legacy systems that may have been holding them back. 

These are just some of the capabilities that retailers gain when they migrate their applications and data to the cloud: 

• Build new revenue streams with omnichannel shopping that runs on the speed and reliability of cloud infrastructure.
• Leverage artificial intelligence and data analytics available in the cloud. Use Google Cloud’s BigQuery to run AI-powered forecasting models to predict demand and plan sales, orders, and other activities with greater precision. Deploy Recommendations AI, to deliver highly personalized product recommendations to your customers at scale.
• Improve operational efficiency with a highly scalable and elastic environment that lets you pay for the compute and storage you need instead of making major investments in physical infrastructure up front.
• Improve customer experience by analyzing behavior and other data to offer customers what they want, when they want it; build personalized mobile and web applications and provide real-time information to customer service and floor staff so they can address customer concerns quickly and effectively.
• Reduce costs by deploying AI-powered agents to help customers solve straightforward issues on their own and automate mundane back-office processes to let your team focus on more value-add work. 
• Safeguard customer data with Google Cloud’s multi-layer, secure-by-design infrastructure, built-in protection, and global network.
• Improve control with integrated cloud management tools that enable IT staff to oversee the whole stack — across on-premises systems and cloud in a single location.

Easy lift and shift with Google Cloud VMware Engine

Retailers do not need to deploy entirely new applications to take advantage of Google Cloud. Rather, they can move their back-office applications and other business systems into the cloud as-is, without the need to rewrite a line of code. 

Google Cloud VMware Engine enables businesses to migrate or extend their on-premises workloads and applications seamlessly to the cloud. This means that IT managers can move their existing applications into the cloud in just a few minutes without having to rebuild them. From there, retailers can run their existing applications — including point-of-sale (POS) systems, virtual desktops, and other devices — just as they did when those applications were installed in the store or office. 

Google Cloud VMware Engine creates a software-defined infrastructure that natively runs VMware workloads without any changes to current tools. That infrastructure includes computing power, storage, network connections, and security services that are dedicated to the individual customer.

Cloud infrastructure for new retail realities

COVID-19 was a wakeup call for many retailers who realized they needed to energize their transformation initiatives in response to permanent shifts in consumer behavior and expectations. Essential to this transformation is getting to the cloud as quickly, efficiently, and cost-effectively as possible, without creating costly disruptions or downtime. Google Cloud VMware Engine lets retailers do exactly that with a straightforward lift-and-shift process that takes just a few minutes. Once in the cloud, retailers can take advantage of the many capabilities Google Cloud offers, including sophisticated data analytics, improved customer experience, enterprise-grade security, and reduced cost.

Read our retail white paper to learn more about how easy it is to migrate your retail IT systems to the cloud with Google Cloud VMware Engine

^{1. MIT Technology Review Insights’ survey on COVID-19 and its impact on technology, in association with VMware; N=100 Retail Senior Technology and Business leaders Worldwide.}