NVIDIA CloudXR Streaming from Cloud to Transform Gaming and Enterprise AR/VR Experience
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The Opportunity for Streamed AR/VR Content
What if you could get a high quality AR/VR experience without a dedicated physical computer—or even without a physical tether?
In the past, interacting with VR required a dedicated, high-end workstation and, depending on the headset, wall-mounted sensors and a dedicated physical space. Complex tasks in VR can push the limits of sensor reach, cable-length, and spatial boundaries, entangling the artist and restricting their movement. This solution was not scalable beyond a handful of advanced use cases.
Recently, tetherless VR headsets from manufacturers such as HTC and Oculus have emerged that free the user from these odious restrictions, enabling a new freedom to experience VR and AR from just about anywhere. The enhanced portability and reduced cost has led to substantially increased adoption among consumers and opened up many new exploratory use cases in enterprise.
However, while these headsets are more accessible and portable, a tradeoff in compute power was required in order to achieve these goals. The limited on-device compute power of this new generation of Head Mounted Displays (HMDs) is acceptable for many consumer applications such as casual gaming. However, advanced enterprise workloads with heavy graphics, compute, or memory requirements can be difficult or even impossible to run on these lightweight devices.
By combining NVIDIA CloudXR with their powerful GPUs running NVIDIA RTX Virtual Workstations (vWS) in Google Cloud data centers, you can experience high-fidelity VR and AR applications from just about anywhere with a good internet connection. The heavy computations are performed in the cloud on a GPU-attached VM and the content streams to any CloudXR compatible headset.
The combination of Google Cloud’s private fiber optic network — the same network we built for global delivery of YouTube content — and CloudXR’s QoS technologies provides the user with the highest possible quality of service. In fact, the streaming experience is comparable to that of a headset tethered to a powerful physical workstation, but without the friction of hardware and cables.
This combination of power and portability sets the stage to unlock the potential of high-quality gaming and enterprise AR/VR experiences anywhere on Earth.
Case Study: Creating a Masterpiece
Digital character creation is a core skill for many 3D artists today. One of the preferred methods of 3D character creation is digital sculpting, which lets artists create both hard-surface and organic shapes with high levels of accuracy and control.
Sculpting is one of the many tasks in the character designer’s skillset. Artists must also master the texturing, rigging, and posing of characters as part of the digital character creation pipeline.
Mastering all these tasks can be challenging, and often, the technology gets in the way; working in multiple applications requires switching contexts and workflows, breaking the artist’s creative flow. The traditional user experience can also be unintuitive, forcing the creator to translate what they want to do with their hands and head into mouse movement and keyboard presses.
Masterpiece Studio Pro revolutionizes this character creation workflow by giving artists the first fully immersive 3D creation pipeline. Artists work in VR, giving them a far more intuitive and seamless way to work which combines the best of the digital and physical worlds.
In Masterpiece Studio Pro, the artist can work on the character or object at any scale, using familiar tools and hand gestures to sculpt a model, much as they would a real clay figure. Performing other tasks such as skeleton creation is simple, allowing the artist to work directly with the limbs of a character to place and adjust the joints.
Bringing It All Together
NVIDIA CloudXR streaming from the cloud provides tremendous opportunities for new creative use cases within gaming and across the enterprise. This solution joins Virtual Studio for Gaming as the latest in our series to help developers build better games.
The Masterpiece Studio use case is a powerful demonstration of new modalities for content creation and collaboration. To try CloudXR with NVIDIA RTX vWS on Google Cloud for yourself, see this tutorial. Masterpiece Studio Pro also offers extensive learning materials and a free trial.
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With a growing number of enterprises across industries making the move from on-premise infrastructure to on-demand cloud services, there has been a major shift from CapEx to OpEx spending. As a result, budgeting can no longer be a one-time operational process completed annually. Instead, spending must be monitored and controlled on an ongoing basis due to the dynamic nature of cloud use within organizations.
Hence, yesterday’s solutions for control and predictability of infrastructure expenditures don’t work well in this new era of cloud services. No wonder, a recent Google study on cloud financial governance among IT and Finance professionals found that lack of predictability is the single greatest cloud cost management pain point.
What is needed by organizations are cloud financial governance tools — that are easy to use and help uncover opportunities for optimizing costs and usage — to make cloud costs more predictable.
Download this handy guide on financial governance in the cloud to learn how you can get on the path to predictable cloud costs.
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Rethinking Financial Services with Google Cloud
The Opportunity for Streamed AR/VR Content
What if you could get a high quality AR/VR experience without a dedicated physical computer—or even without a physical tether?
In the past, interacting with VR required a dedicated, high-end workstation and, depending on the headset, wall-mounted sensors and a dedicated physical space. Complex tasks in VR can push the limits of sensor reach, cable-length, and spatial boundaries, entangling the artist and restricting their movement. This solution was not scalable beyond a handful of advanced use cases.
Recently, tetherless VR headsets from manufacturers such as HTC and Oculus have emerged that free the user from these odious restrictions, enabling a new freedom to experience VR and AR from just about anywhere. The enhanced portability and reduced cost has led to substantially increased adoption among consumers and opened up many new exploratory use cases in enterprise.
However, while these headsets are more accessible and portable, a tradeoff in compute power was required in order to achieve these goals. The limited on-device compute power of this new generation of Head Mounted Displays (HMDs) is acceptable for many consumer applications such as casual gaming. However, advanced enterprise workloads with heavy graphics, compute, or memory requirements can be difficult or even impossible to run on these lightweight devices.
By combining NVIDIA CloudXR with their powerful GPUs running NVIDIA RTX Virtual Workstations (vWS) in Google Cloud data centers, you can experience high-fidelity VR and AR applications from just about anywhere with a good internet connection. The heavy computations are performed in the cloud on a GPU-attached VM and the content streams to any CloudXR compatible headset.
The combination of Google Cloud’s private fiber optic network — the same network we built for global delivery of YouTube content — and CloudXR’s QoS technologies provides the user with the highest possible quality of service. In fact, the streaming experience is comparable to that of a headset tethered to a powerful physical workstation, but without the friction of hardware and cables.
This combination of power and portability sets the stage to unlock the potential of high-quality gaming and enterprise AR/VR experiences anywhere on Earth.
Case Study: Creating a Masterpiece
Digital character creation is a core skill for many 3D artists today. One of the preferred methods of 3D character creation is digital sculpting, which lets artists create both hard-surface and organic shapes with high levels of accuracy and control.
Sculpting is one of the many tasks in the character designer’s skillset. Artists must also master the texturing, rigging, and posing of characters as part of the digital character creation pipeline.
Mastering all these tasks can be challenging, and often, the technology gets in the way; working in multiple applications requires switching contexts and workflows, breaking the artist’s creative flow. The traditional user experience can also be unintuitive, forcing the creator to translate what they want to do with their hands and head into mouse movement and keyboard presses.
Masterpiece Studio Pro revolutionizes this character creation workflow by giving artists the first fully immersive 3D creation pipeline. Artists work in VR, giving them a far more intuitive and seamless way to work which combines the best of the digital and physical worlds.
In Masterpiece Studio Pro, the artist can work on the character or object at any scale, using familiar tools and hand gestures to sculpt a model, much as they would a real clay figure. Performing other tasks such as skeleton creation is simple, allowing the artist to work directly with the limbs of a character to place and adjust the joints.
Bringing It All Together
NVIDIA CloudXR streaming from the cloud provides tremendous opportunities for new creative use cases within gaming and across the enterprise. This solution joins Virtual Studio for Gaming as the latest in our series to help developers build better games.
The Masterpiece Studio use case is a powerful demonstration of new modalities for content creation and collaboration. To try CloudXR with NVIDIA RTX vWS on Google Cloud for yourself, see this tutorial. Masterpiece Studio Pro also offers extensive learning materials and a free trial.
Dataflow Guarantees 50+% Increase in Developer Productivity and Infrastructure Cost Savings: Read More
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In our conversations with technology leaders about data-driven transformation using Google Data Cloud – industry’s leading unified data and AI solution – , one important topic is incorporating continuous intelligence to move from answering questions such as “What has happened? to questions like “What is happening?” and “What might happen?”. The core to this evolution is the need for an underlying data processing that not only provides powerful real-time capabilities for events happening close to origination, but also brings together existing data sources under one unified data platform to enable organizations to draw insights and take actions holistically. Dataflow, Google’s cloud-native data processing and streaming analytics platform, is a key component of any modern data and AI architecture and data transformation journey, along with BigQuery, Google’s internet-scale warehouse with built-in streaming, BI engine and ML; Pub/Sub, a global no-ops event delivery service; and Looker, a modern BI and embedded analytics platform. One of the key evaluation factors is potential economic value of Dataflow to their organization, particularly in the context of engaging other stakeholders is key for many of the leaders that we engage with. So we commissioned Forrester Consulting to conduct a comprehensive study on the impact that Dataflow had on their organization by interviewing actual customers .
Today we’re excited to share our commissioned study conducted by Forrester Consulting, the Total Economic Impact™ of Google Cloud Dataflow, which allows data leaders to understand and quantify the benefits of Dataflow, and use cases it enables. Forrester conducted interviews with Dataflow customers to evaluate the benefits, costs, and risks of investing in Dataflow across an organization. Based on their interviews, Forrester identified major financial benefits across four different areas: business growth, infrastructure cost savings, data engineer productivity, and administration efficiency. In fact, Forrester found that customers adopting Dataflow can achieve a 55% boost in developer productivity and a 50% reduction in infrastructure costs. In fact, Forrester projects that customers adopting Dataflow can achieve a range of up to 171% Return on Investment (ROI) and a less than six months payback period. Customers can now use figures in the report to compute their own Return on Investment (ROI) and payback period.
“Dataflow is integral to accelerating time-to-market, decreasing time-to-production, reducing time to figure out how to use data for use cases, focusing time on value-add tasks, streamlining ingestion, and reducing total cost of ownership.” – Lead technical architect, CPG
Let’s take a deeper look at the ways that Forrester found that Dataflow can help you achieve your goals and unlock your business potential.
Benefit #1: Increase data engineer productivity by 55%
Developers can choose among a variety of programming languages to define and execute data workflows. Dataflow also seamlessly integrates with other Google Cloud Platform and open source technologies to maximize value and applicability to a wide variety of use cases. Dataflow streamlined workflows with code reusability,dynamic templates, and the simplicity of a managed service. Engineers trusted pipelines to run correctly and adhere to governance. Data engineers avoided laborious issue-monitoring and remediation tasks that were common in the legacy environments such as poor performance, lack of availability, and failed jobs. Teams valued the language flexibility and open source base.
“Dataflow provided us with ETL replacement that opened limitless potential use cases and enabled us to do smarter data enhancement while data remains in motion.” — Director of data projects, financial services
Benefit #2: Reduce infrastructure costs by up-to 50% for batch and streaming workloads
Dataflow’s serverless autoscaling and discrete control of job needs, scheduling, and regions eliminated overhead and optimized technology spending. Consolidating global data processing solutions to Dataflow further eliminated excess costs while ensuring performance, resilience, and governance across environments. Dataflow’s unified streaming and batch data platform gives organizations the flexibility to define either workload in the same programming model, run it on the same infrastructure, and manage it from a single operational management tool.
“Our costs with our cloud data platform using Dataflow are just a fraction of the costs we faced before. Now we only pay for cloud infrastructure consumption because the open source base helps us avoid licensing costs. We spend about $120,000 per year with Dataflow, but we’d be spending millions with our old technologies.” – Lead technical architect, CPG
Benefit #3: Increase top-line revenue by improving customer experience and retention with payback time of < 6 months
Streaming analytics is an essential capability in today’s digital world to gain real-time actionable insights. Likewise, organizations must also have flexible, high- performance batch environments to analyze historical data for building machine learning models, business intelligence, and advanced analytics. Dataflow enabled real-time streaming use cases, improved data enrichment, encouraged data exploration,improved performance and resiliency, reduced errors, increased trust, and eliminated barriers to scale. As a result, organizations provided customers with more accurate, relevant, and in-the-moment data-backed services and insights — boosting customer experience, creating new revenue streams, and improving acquisition, retention, and enrichment.
“It’s already been proven that we are getting more business [with Dataflow] because we can turn around results faster for customers.” – VP of technology, financial services technology
“When we provide data to our customers and partners with Dataflow, we are much more confident in those numbers and can provide accurate data within a minute. Our customers and partners have taken note and commented on this. It’s reduced complaints and prevented churn.” – Senior software engineer, media
Other benefits
Eliminated administrative overhead and toil
As a cloud-native managed service, all administration tasks such as provisioning, scaling, and updates are automatically handled by Google Cloud. Teams no longer need to manage servers and related software for legacy data processing solutions. Admins also streamlined processes for setting up data sources, adding pipelines, and enforcing governance.
Saved business operations costs for support teams and data end users
Dataflow improved the speed, quality, reliability, and ease of access to data for insights for general business users, saving time and empowering users to drive better data-backed outcomes. It also reduced support inquiry volume while automating manual job creation.
What’s next?
Download the Forrester Total Economic Impact study today to dive deep into the economic impact Dataflow can deliver your organization. We would love to partner with you to explore the potential Dataflow can unlock in your teams. Please reach out to our sales team to start a conversation about your data transformation with Google Cloud.
Multi-cloud Adoption Empowers GCCs to be Resilient, Scalable and Future-proof: Whitepaper
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India has emerged as the Technology capital for the world – there are now at least 55 unicorns in India, nearly 600 funding rounds in just the last 30 months and 200+ GCCs expected in the next 2 years. There has been a rapid acceleration not just in the number of startups being launched, but also in the variety of technologies they are experimenting with.
India GCC’s are leading the transformation agenda for the enterprise and the pandemic has accelerated the inevitable. Technology now underpins every facet of a business: products, services, business processes, and how customers and businesses interact. As organizations are investing and progressing on their digital journey, they are increasingly relying on talent and teams across the globe to help them navigate the changes and build strategic capacity.
How is Cloud enabling this strategic change? This whitepaper compiled by ANSR and Google Cloud aims to expand on the following,
What is the cloud adoption story and how can it empower GCCs to be resilient, scalable and future-proof?
How have global teams or Global Capability Centers enabled the strategic and accelerated adoption of technology?
What are the key Cloud considerations for building an innovative, collaborative ecosystem for a thriving organization?
Ease Your Migration and Modernization Journey with Microsoft and Windows on Google Cloud Demo Center
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If you’re looking to migrate and modernize your Microsoft and Windows workloads, Google Cloud is your premiere destination. No matter what migration strategy you’ve selected or what value you’re looking to achieve, with Google Cloud you’re able to:
- simplify your migration and modernization journey
- reduce your on-prem footprint and increase agility
- optimize license usage to reduce costs
- modernize to reduce single-vendor dependencies
- rely on enterprise-class support backed by Microsoft
Whether you’re looking to migrate applications running on Windows virtual machines, adopt Windows containers in Google Kubernetes Engine (GKE), convert SQL databases to Cloud SQL, or something else, Google Cloud offers you the first-class experience you need.
But we don’t want you to take our word for it. Try it out yourself with our new online Microsoft and Windows on Google Cloud Demo Center without any commitment or friction.
The demo center uses hands-on guided simulations to walk you through several scenarios for solving business critical challenges with Google Cloud’s Microsoft and Windows solutions. Because these are all simulated, you’ll see how it works without any deployment, configuration, or commitment. It’s a seamless way for you to see exactly how Google Cloud can help you.
Run dedicated hardware and optimize with sole tenant
Sometimes you might want to run your workloads on dedicated hardware (with oversubscription options) for compliance, licensing, and management. Google Cloud provides sole-tenant nodes that allow you to easily deploy your virtual machines onto dedicated machines to avoid “noisy neighbor” issues, address regulatory or licensing constraints, and optimize inter-VM communications.
Plus, the CPU Overcommit option allows oversubscribing sole-tenant node resources by up to 2x, therefore helping save on per-physical core licensing for many licensed workloads like SQL Server.
Learn how to set up a sole tenant group and node.
Optimize license costs with premium images & custom VMs
One of the easiest ways to optimize your cloud experience with virtual machines (VM) is to pick the right VM image. Google Cloud provides premium license-included VM images that are thoroughly tested and optimized, including SQL Server options with pay-as-you-go licensing. These are great for workloads that don’t need to run all the time or when you do not have spare licenses for bring your own license (BYOL).
Explore some Windows & SQL images and learn how CPU/Memory options can help optimize deployment and save on licensing.
Modernize your databases with Managed SQL Server
Sometimes you need to manage your SQL Server instance to achieve certain business or operational goals. But more often, managing SQL Server deployments can be undifferentiated: backups, high-availability, updates, and patching are just some of the many things you have to take care of when going the do-it-yourself route. One way to modernize your database tier is to migrate to a managed service like Cloud SQL, which is a fully managed Relational Database service for SQL.
Explore the process of creating an instance in just a few clicks!
Extract apps from VMs and move to containers in GKE with Migrate for Anthos
Many Windows workloads running on virtual machines such as Internet Information Services (IIS) are ideal candidates for migrating to containers without major changes like rewriting or rearchitecting. However, doing this migration manually can be tedious, which is why Migrate for Anthos can help easily re-platform a .NET app running on IIS into a container-based app.
Simulate intelligently extracting, migrating, and modernizing applications to run natively on containers in GKE and Anthos clusters.
Move .NET applications to GKE on Windows without code changes
When you’re looking to go fully cloud native, you can leverage Windows containers in GKE without rewriting your .NET applications. Simply create clusters with Windows nodes and deploy containerized Windows workloads in a few clicks, even alongside Linux containers. These deployments reduce operational overhead with features such as auto-upgrade, auto-repair, and release channels.
Learn how easy it is to build a GKE cluster with a Windows node and deploy an app.
Now that you’ve gotten a feel for what’s available, go check out the Demo Center. You can also visit us at Windows and Microsoft on Google Cloud to learn more.
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Total Economic Impact of Running SAP on Google Cloud: Forrester’s Report
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