Organizations across industries are looking to AI to turn troves of data into intelligence, powered by the latest advances in generative AI. Yet for many organizations, there is a barrier to adopting the latest models because they can be costly to train or serve. A new class of cloud GPUs is needed to lower the cost of entry for businesses that want to tap the power of AI. 

Today, we’re introducing G2, the newest addition to the Compute Engine GPU family in Google Cloud. G2 is the industry’s first cloud VM powered by the newly announced NVIDIA L4 Tensor Core GPU, and is purpose-built for large inference AI workloads like generative AI. G2 delivers cutting-edge performance-per-dollar for AI inference workloads that run on GPUs in the cloud. By switching from NVIDIA A10G GPUs to G2 instances with L4 GPUs, organizations can lower their production infrastructure costs up to 40%. We also found that customers switching from NVIDIA T4 GPUs to L4 GPUs can achieve 2x-4x better performance. As a universal GPU offering, G2 instances also help accelerate other workloads, offering significant performance improvements on HPC, graphics, and video transcoding. Currently in private preview, G2 VMs are both powerful and flexible, and scale easily from one up to eight GPUs. 

Currently organizations require end-to-end enterprise ready infrastructure that will future proof their AI and HPC initiatives for a new era. G2s will be ready to be deployed on Vertex AI, GKE, and GCE, giving customers the freedom to architect their own custom software stack to meet their performance requirements and budget. With optimized Vertex AI support for G2 VMs, AI users can tap the latest generative AI models and technologies. With an easy to use UI and automated workflows, customers can access, tune and serve modern models for video, text, images, and audio without the toil of manual optimizations. The combination of these services with the power of G2 will help customers harness the power of complex machine models for their business.

NVIDIA L4 GPUs with Ada Lovelace Architecture

G2 machine families enable machine learning customers to run their production infrastructure in the cloud for a variety of applications such as language models, image classification, object detection, automated speech recognition, and language translation. Built on the Ada Lovelace architecture with fourth-generation Tensor Cores, the NVIDIA L4 GPU provides up to 30 TFLOPS of performance for FP32, and 242 TFLOPs for FP16. Newly added FP8 support, on top of existing INT8, BFLOAT16 and TF32 capabilities, makes the L4 ideal for ML inference. 

With the latest third-generation RT Cores and DLSS 3.0 technology, G2 instances are also great for graphics-intensive workloads such as rendering and remote workstations when paired with NVIDIA RTX Virtual Workstation. NVIDIA L4 provides 3x video encoding and decoding performance, and adds new AV1 hardware-encoding capabilities. For example, G2 can enable gaming customers running game engines such as Unreal and Unity with modern graphics cards to run real-time applications. Likewise, media and entertainment customers that need GPU-enabled virtual workstations can use the L4 to create photo-realistic, high-resolution 3D content for movies, games, and AR/VR experiences using applications such as Autodesk Maya or 3D Studio Max.

What customers are saying

A handful of early customers have been testing G2 and have seen great results in real-world applications. Here are what some of them have to say about the benefits that G2 with NVIDIA L4 GPUs bring:

AppLovin

AppLovin enables developers and marketers to grow with market leading technologies. Businesses rely on AppLovin to solve their mission-critical functions with a powerful, full stack solution including user acquisition, retention, monetization and measurement.

“AppLovin serves billions of AI powered recommendations per day, so scalability and value are essential to our business,” said Omer Hasan, Vice President, Operations at AppLovin. “With Google Cloud’s G2 we’re seeing that NVIDIA L4 GPUs offer a significant increase in the scalability of our business, giving us the power to grow faster than ever before.”

WOMBO

WOMBO aims to unleash everyone’s creativity through the magic of AI, transforming the way content is created, consumed, and distributed. 

“WOMBO relies upon the latest AI technology for people to create immersive digital artwork from users’ prompts, letting them create high-quality, realistic art in any style with just an idea,” said Ben-Zion Benkhin, Co-Founder and CEO of WOMBO. “Google Cloud’s G2 instances powered by NVIDIA’s L4 GPUs will enable us to offer a better, more efficient image-generation experience for users seeking to create and share unique artwork.”

Descript

Descript’s AI-powered features and intuitive interface fuel YouTube and TikTok channels, top podcasts, and businesses using video for marketing, sales, and internal training and collaboration. Descript aims to make video a staple of every communicator’s toolkit, alongside docs and slides. 

“G2 with L4’s AI Video capabilities allow us to deploy new features augmented by natural-language processing and generative AI to create studio-quality media with excellent performance and energy efficiency” said Kundan Kumar, Head of Artificial Intelligence at Descript.

Workspot

Workspot believes that the software-as-a-service (SaaS) model is the most secure, accessible and cost-effective way to deliver an enterprise desktop and should be central to accelerating the digital transformation of the modern enterprise.

“The Workspot team looks forward to continuing to evolve our partnership with Google Cloud and NVIDIA. Our customers have been seeing incredible performance leveraging NVIDIA’s T4 GPUs. The new G2 instances with L4 GPUS through Workspot’s remote Cloud PC workstations provide 2x and higher frame rates at 1280×711 and higher resolutions” said Jimmy Chang, Chief Product Officer at Workspot.

Pricing and availability

G2 instances are currently in private preview in the following regions: us-central1, asia-southeast1 and europe-west4. Submit your request here to join the private preview, or to receive a notification as when the public preview begins. Support will be coming to Google Kubernetes Engine (GKE), Vertex AI, and other Google Cloud services as well. We’ll share G2 public availability and pricing information later in the year.

Over the past decade, cybersecurity has posed an increasing risk for organizations. In fact, cyber incidents topped the recent Allianz Risk Barometer for only the second time in the survey’s history. The challenges in combating these risks only continue to grow. Adversaries tend to be agile and are consistently looking for new ways to land within your digital environments. They also drive attack vectors that work, which means enterprise risk leaders are now forced to look for new ways of securing infrastructure and data.

Cloud comes of age in the modern day cybersecurity threat landscape

When cloud, in its various delivery models, was first introduced, it didn’t fit neatly into the security frameworks that had seemingly protected networks for many decades. Public cloud was the answer to ongoing IT challenges: scale, resources, security capabilities, and budget cycle limitations. Now, public cloud is meeting the increasing challenge of implementing cybersecurity controls and frameworks that are capable of protecting today’s global enterprise.

Cloud adoption – with all its scale and redistribution of longstanding security paradigms – is the optimal choice for infrastructure and security, particularly as organizations grapple with the need to engage in digital transformation. We assert that successful digital transformation is impossible without incorporating the use of the scale, security architecture, and resiliency of the cloud.

Consequently, cloud adoption becomes a necessary component of roadmap discussions and planning as your organization looks to reduce overall risk. Risk leaders and enterprise cybersecurity leaders must consider that moving data, digital processes, and priority workloads to the public cloud is a crucial step for meeting the current and future digital needs of the enterprise. Going forward, this digital transformation increasingly will include hybrid infrastructure environments composed of a combination of on-premises and cloud solutions.

Pinpointing where threats thrive

As digital environments become more complex within a given organization, proactively countering adversaries becomes all the more difficult. It’s harder to implement, scale, and adhere to existing security and control frameworks. It’s also increasingly challenging to apply framework guidance to new applications, build and support infrastructure within a secure foundation, and maintain good cyber hygiene through the digital lifecycle.

As reported by TechTarget, the 2020 hack of the SolarWinds Orion IT performance monitoring system is a prime example. It grabbed headlines “not because a single company was breached, but because it triggered a much larger software supply chain incident.” This vulnerability in popular, commercially available, and widely utilized software compromised the data, networks, and systems of thousands of companies when a routine software update turned out to be backdoor malware.

A close look at the root problems behind high-profile security breaches reveals that it’s a lack of agility and an inability to scale resources that prohibit the modern security organization’s ability to respond quickly enough to counter new challenges. Look even closer and you’ll often find an insufficient implementation of best practices and ineffective solutions, leaving an organization continually chasing the next tool or solution and scrambling to stay ahead of emerging threats.

While the cost to individual businesses is high, most organizations struggle with the needed skills and resources to rigorously maintain data security basics and ensure readiness for inevitable attacks. The previous sentence is especially true when you consider that maintaining an effective state of cybersecurity readiness is a costly practice that requires the continual development of expertise, the evaluation of new tools, and an ongoing element of vigilance.

Threat visibility is a big part of the problem. You can’t protect your company from what you can’t see. For individual enterprises – with critical data workloads housed in a combination of on-premises servers, a variety of endpoints, and both private and public cloud instances – staying ahead in the ongoing battle requires a new approach.

The identification of actionable alerts and other data contributes to a better overall state of readiness. Thought leadership and discussions related to Autonomic Security Operations provide a promising outlook for security organizations willing to lean into the changing technology landscape – a landscape that now benefits from leveraging automation and machine learning currently used in security stacks. Reducing the chance of introducing vulnerabilities or missing-critical alerts starts with ensuring full visibility into an increasingly expanding and complex environment.

The evolution of a shared responsibility to a shared fate

Industry megatrends are driving cloud adoption and with it a path to improved cybersecurity. Among these trends is the concept of shared fate as an evolution of the historical shared-responsibility model. Shared fate drives a flywheel of increasing trust which develops as more enterprises transition to the cloud. This compels an even higher security investment and a more vested interest from cloud service providers.

At Google Cloud, shared fate means we take an active stake in our customers’ security posture, offering capabilities and defaults that help ensure secure deployments and configurations in the public cloud. We also offer experience-based guidance on how to configure cloud workloads for security, and can assist with risk management, reduction, and transfer.

The Google Cloud Risk Protection Program represents the continuing evolution of the shared-fate model. The program offers a practical solution that provides the modern enterprise a snapshot comparison of its current security state against well-adopted cloud-security frameworks. It also give you an opportunity to explore cyber insurance designed to meet your needs from our partners Allianz and Munich Re.

When performed with diligence, cloud adoption can help increase your overall cybersecurity effectiveness. Using a hybrid approach – and steadily reducing which data assets remain on premises – can strengthen your overall security posture and reduce risks to the organization.

Cloud security and the ability to reduce risk

In comparison to the enterprise-by-enterprise security scramble to protect data and workloads in individual private clouds, global public cloud solutions like Google Cloud can be a force multiplier when adhering to established best practices. By that, we mean, quite literally, that you get more security at every touchpoint – from infrastructure and software to access and data security.

Strong security in the public cloud starts with the foundational pieces: the hardware and design elements. At Google, for example, we take a security-by-design approach within both the data center and purpose-built components themselves. Within Google Cloud, data is encrypted by default – both at rest and in transit. Google’s baseline security architecture adheres to the zero trust principles, meaning that every network, device, person, or service initially cannot be trusted.

Embarking on a zero trust architecture journey gives modern security practitioners the ability to methodically shut down traditional attack vectors. Zero trust also provides more granular visibility and control of rapidly expanding environments. The recent emphasis of its benefits, as the U.S. White House set forth through an executive order on increasing cybersecurity resilience, is an example of the wide-scale recognition by both government and industry on the benefits of this approach.

Since adopting a zero trust approach more than a decade ago, Google has achieved a recognizable level of maturity, reflected by our internal infrastructure and multiple enterprise offerings, enabling different aspects of the zero trust security journey.

Compliance and privacy drive critical elements of the cloud adoption cycle

Privacy frameworks, regulatory compliance, and data sovereignty are driving critical elements of the cloud adoption cycle. Cloud providers must ensure they have the necessary controls, attestations, and abilities to audit in order to provide organizations with the tools to preemptively satisfy regulatory and compliance mandates across the globe.

Now consistently expected to be part of a design feature that’s built into the cloud journey, it cannot simply be an add-on capability. The direction of this evolution promises to play more of a role in the future of cloud adoption, not less. Because this is an ongoing component of enterprise risk evaluation, your business must consider cloud providers that can partner on this critical aspect of the journey – and not leave you without the resources to respond to this growing critical need.

Building trust into your digital transformation journey

Digital transformation is difficult because the modern enterprise must build and design for both today and tomorrow. From a security perspective, the challenge has often been that security industry practitioners cannot always predict what the future will look like. That said, there are clear steps you can take to mitigate all-around risk throughout the process.

How you approach the cloud is, of course, integral to your journey, but it doesn’t need to be an all-or-nothing proposition. And although technology debt continues to persist with legacy systems, that doesn’t mean you shouldn’t begin to move forward.

Google Cloud enables you to modernize at your own pace and understand what’s realistic. We recommend you move what data you can to a more secure public cloud today, followed by a phased approach to move more in the months and years that follow. The key tenets of our approach to security in the public cloud include:

• The security-by-design posture of Google Cloud can help modern-day enterprises scale security capabilities and reduce risk with an architecture built on zero trust principles.
• The Google Cloud approach to security and resiliency includes a framework to help you protect against adverse cyber events by using our comprehensive suite of solutions.
• Google Cloud can help ensure your organization adheres to the requirements of a growing and increasingly complex regulatory and compliance environment.
• The ideal model of a future organization is one where cloud plays a major role in infrastructure design and architecture. Your organization should begin to view public cloud as an enabler of the business and a core component of digital transformation.

As you transition more data to the public cloud, it’s paramount that trust is ingrained in every step you take with your cloud service provider. Many service providers readily take on a shared responsibility with your organization when it comes to security. At Google, we take it several steps further with our shared fate model to help ensure data security in the public cloud. Your future and our’s are part of the same data security journey.

Introduction

The Google Cloud Professional Services Organization’s (PSO) mission is to help our customers get the most out of Google products. PSO is responsible for customer success by sharing our technical expertise in order to unlock business value from the cloud by providing cloud strategy and best practice advice, implementation guidance, and training using our proven methodology. 

In this blog post, we want to focus specifically on Operational Health Reviews and how PSO engages in a myriad of activities to ensure the overall success and health of a customer engagement while ensuring we are meeting customer expectations and objectives, managing risk, and ultimately delivering value during or after the Google Cloud migration. We will discuss the assets, methodology, and tools that we leverage to ensure this success.

What is an Operational Health Review and what purpose does it serve?

Operational Health Reviews (OHR) are regular reviews to proactively address the below topics: 

• A customer’s support experience
• Analysis of trends in key operational metrics
• Analysis of trends in Google Cloud usage
• Status reports for high-priority cloud projects
• Discussion of upcoming events
• Discussion of potential opportunities for training
• Review of feature requests

The core aim of an OHR is to measure progress and advise customers on the overall health of the account and migration progress while providing recommendations as a team on what adjustments should be considered to ensure continued success. During the OHR, we will address any pain points as well as identify and remediate any negative trends in support interfaces and usage metrics. 

The intention of the activity is to also perform a blameless reflection for continuous improvement. This supports the effort to maintain common ground and obtain mutual optimism for the next phase of the customer’s journey on Google Cloud. 

Let’s dive a little deeper into some of the activities that go into an OHR. 

Support experience

One of the Google Cloud’s Support Organization’s goals is to simplify and streamline our customer’s support experience with a scalable and flexible set of offerings built with the customer needs at the center. This includes supporting an ongoing partnership model, with a proactive and collaborative approach. Premium Support is our top-tier support model which is a paid support offering designed for enterprises that run mission critical workloads and require fast response times, platform stability, and increased operational efficiencies. As part of this offering, customers are provided with a Technical Account Manager (TAM) who is in charge of delivering frequent touchpoints, including OHRs. 

During the support experience section of an OHR, some of the following topics may be reviewed:

• Case volume by priority
• Case volume by product
• Cases linked to Google Cloud incidents
• Escalated cases or incidents
• Case initial response time (IRT)
• Case IRT SLO Met Rate
• Case total resolution time (TRT) hours

The purpose of this activity is to better understand the efficiency of both the customer’s and Google’s cloud operations from a support trend perspective. The goal is to celebrate any positive trends, but also to identify potential negative trends and proactively determine a remediation strategy. 

Status reports for high-priority cloud projects

The purpose of this part of the OHR is to ensure the senior management stakeholders have continued visibility into the status of all their high-priority cloud initiatives with an easy-to-read, sometimes color-coded assessment on the status of each project. The assessment [Figure 1] may include, but is not limited to potential identified risks, key next steps, key stakeholders, and a mitigation plan for any high priority issues that may occur during their migration engagement. Additionally, the TAM may also cover any upcoming milestones or events, as well as any potential anticipated future blockers [Figure 2]. 

Review trends in Google Cloud usage

This part of the OHR is meant to provide the customer with a holistic view of their overall Google Cloud usage. The purpose is to provide understanding around what products are being used on Google Cloud and also where cost is generally being allocated for overall cost management and budget tracking purposes. This can help customers with their overall cost optimization efforts. Some of the metrics we may cover in this section are:

• Current Google Cloud usage by service
• Google Cloud growth trends
• Google Cloud growth trends by service
• Google Cloud growth trends by project
• Review of used and available service credits

Feature request review and advocacy

TAMs will work with customers to help identify product needs and advocate for feature requests with Google Product Management and Engineering teams. While feature request advocacy is an ongoing activity, during the OHR, the TAM will review any high priority feature requests that have previously been submitted, providing updates on status including potential release dates. 

When a feature is coming up for the release, the TAM can help the customer prepare for implementation (providing early Preview access, coordinating a meeting with the Product Manager to review the feature, etc.) and then continue to provide support until the feature is successfully implemented in the customer environment. Similarly, if a high priority or technical blocking feature is not yet coming available, the TAM can help offer an alternative solution that can unblock the customer in the short term. 

The OHR is also a great time for the TAM to work with the customer to ensure they have early access to new and exciting features that are in Alpha or Beta, and that would be beneficial to the customer and their environment. 

Training strategy

Training is a primary component to ensuring the overall success in adopting Google Cloud. During the OHR, a review of training metrics will be provided. This may include tracking metrics to determine how the customer is tracking towards an initially agreed upon learning plan or coming up with additional upskilling strategies as necessary. Additionally, throughout an engagement, the customer’s TAM will provide opportunities for both free and paid Google Cloud training. 

Conclusion 

PSO is the voice of customer health, maintaining priority to proactively and strategically guide large enterprise customers to operate effectively and efficiently in the cloud, both during and after the migration process. The OHR is an efficient and effective way to maintain alignment, ensure expectations and objectives are being met, manage risk, and overall ensure the success of the customer.

Learn more about our methodology and get started with Google Cloud by completing a free discovery and assessment of your migration. Alternatively, if you’d like to engage directly with our PSO team on your migration, contact us!

If your organization is one of the 52% of SAP customers whose top analytics pain point is data integration¹, Google Cloud has got you covered. By working with partners like Qlik, we are expanding our integration options and bringing real-time replication capability for SAP to BigQuery.

Integrated data for accelerated insights

BigQuery—our fully managed, enterprise data warehouse that can scale up to petabytes on demand and execute queries in seconds—allows SAP customers to consolidate enterprise data silos and confidently derive more use and value from their data.  Customers can accelerate and simplify the delivery of SAP data on BigQuery with the latest Qlik Data Integration platform offering for Google Cloud which allows data integration using an automated, near real-time data pipeline through Qlik Replicate, whether data originates from legacy SAP environments, SAP HANA, or SAP application servers. Additionally, Qlik Compose for Data Warehouses can be used to easily generate and automate logical data models from SAP directly in BigQuery freeing up more time for data analysts to leverage advanced built-in capabilities such as BigQuery ML to derive greater value and insights using standard SQL without the need for advanced programming expertise.

Delivering faster results with real-time 

Traditional extract-transform-load (ETL) solutions operate on a batch basis, pulling data sets from SAP daily, hourly, or every minute. These tools often require manual mapping of multiple data fields so that data flows accurately. Given SAP’s highly complex table relationships, in which a single transaction can result in multiple changes, this can be a time consuming and tedious process. ETL can also increase the burden on your SAP systems.

Qlik Replicate simplifies this with its intuitive user interface where you can set up real-time data replication between SAP and BigQuery, eliminating the need for manual coding. And, to prevent system overhead, as soon as a new transaction is entered into SAP, the resulting data is replicated into BigQuery in a process known as change data capture (CDC) from SAP’s log layer. This means that data transfer can benefit from high performance with minimal impact on the source system’s resources. Read our latest white paper to learn how to extract SAP data into BigQuery leveraging Qlik Replicate. 

Solution expertise for all core SAP workloads

It doesn’t matter what database your SAP system runs on, Qlik Replicate supports all core SAP systems. It automates real-time data replication and decodes SAP’s complex, application-specific data structures into formats that flow smoothly into BigQuery. This ensures that anyone who depends on data analytics has the most current and relevant SAP data they need. For its robust solution capabilities Qlik has received a new “SAP on Google Cloud Expertise” designation for supporting:

• Fast onboarding and accelerated replication of SAP data into Google Cloud
• Real-time and continuous data replication from SAP applications to BigQuery
• Support for all core SAP modules and a broad set of data sources
• Automated data integration, which cuts resource requirements for initial delivery and ongoing maintenance

Proven customer results

Many SAP customers have experienced the benefits of leveraging Qlik alongside BigQuery for data analytics and AI at scale, including German luxury department store chain Breuninger. In order to meet its customers’ growing and changing expectations,Breuninger needed to accelerate its time to insight from data sources across a highly dispersed landscape of on-premises databases and systems, including SAP. The company uses Qlik Replicate to feed corporate data from modules in its SAP system into BigQuery and integrate its varying on-premises databases with the Google Cloud environment. This has yielded game-changing, real-time customer insights for the retailer.

What could your business do with faster, more integrated insights? Learn more about BigQuery for SAP customers and also how Qlik and Google Cloud can help you modernize and automate data integration and analytics.