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Titanium: A Robust Foundation for Workload-optimized Cloud Computing

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Introducing Titanium: Google Cloud's groundbreaking infrastructure innovation, redefining cloud computing with unrivaled performance, security, and scalability. Explore how Titanium is poised to reshape the future of cloud workloads.

Google Cloud is built on world-class technical infrastructure that supports services that are loved and relied on by billions of people across the globe: Google Search, YouTube, Gmail, Google Maps and more. A core tenet at Google Cloud is to leverage Google’s experience building and operating highly available and highly reliable planetary-scale compute, storage and networking systems and data centers. 

Google takes a workload-optimized approach to building its infrastructure, employing a combination of dedicated hardware and software components to meet its workloads’ ever-growing demands. Underpinning this infrastructure is Titanium, a system of purpose-built, custom silicon and multiple tiers of scale-out offloads that together power improvements in the performance, reliability, and security of our customers’ workloads (for example, 25% faster block storage IOPS/instance compared to the other two leading hyperscalers). Unveiled today at Google Cloud Next, you’ll find Titanium technology in many of Google Cloud’s recent infrastructure offerings.

10x demands of tomorrow 

Meeting the growing performance, reliability, and security demands of both legacy and emerging workloads is a constant challenge for cloud infrastructure providers. And now, these demands are multiplying with the heightened adoption of generative AI across almost every industry. Meanwhile, the benefits of Moore’s law have been declining in recent years. We can’t rely on silicon advances alone to meet tomorrow’s needs.

As just one example, this chart shows the exponential computing demands of large language models.

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It was clear to us a long time ago that we needed to rethink our infrastructure designs to meet these demands. This is why, for several years, we’ve adopted workload-optimization and intentional design as central principles for our infrastructure platform. We engineer golden paths from silicon to the customer workload, using a combination of purpose-built infrastructure, prescriptive architectures, and an open ecosystem to deliver workload-optimized infrastructure

Offloads play a pivotal role

Central to this strategy are offload technologies. Traditionally, the CPU wears many hats: It runs the hypervisor, the virtualization stack to enable your workloads, and manages storage and networking I/O; it’s responsible for security isolation for virtual interfaces and physical hardware, etc. In this model, customer workloads running on the CPU contend for resources with these platform tasks.

Offloads on dedicated hardware perform behind-the-scenes security, networking, and storage functions that were previously performed by the host CPU, allowing the CPU to focus on maximizing performance for customer workloads.

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A recent example of an on-host offload or accelerator is the Infrastructure Processing Unit (IPU), a system-on-chip that we co-designed with Intel to enable better security isolation and performance on our 3rd gen compute instances. The IPU enables:

  • Predictable and efficient compute
  • Programmable packet processing for low latency, 200 Gbps networking with 3x the packets per second compared to our previous-generation compute instances
  • In-transit encryption with the PSP protocol

Another important example of Google’s on-host hardware is Titan, a secure, low-power microcontroller that helps ensure that every machine in Google Cloud boots from a trusted state.

But we did not stop there. To meet tomorrow’s demands, we knew we needed to go past the performance that could be achieved using the host’s dedicated offload hardware.

A tiered system of offloads

A key component of Titanium is its modern offload architecture, which combines capabilities whose scale and performance are well-established within Google, as well as new capabilities tailored for cloud use cases. 

Just as modern workloads scale out horizontally in the cloud, with Titanium, we’ve extended the architecture to augment on-host offloads with an additional tier of scale-out offloads that run outside the host. This system of offloads is deployed fleet-wide and dynamically adjusts to changing workload needs to continually deliver the best performance.

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Example 1: Block storage
Titanium scale-out offload enables Hyperdisk block storage to deliver stellar I/O performance. Hyperdisk’s Titanium offload on the host IPU works in tandem with the Titanium scale-out offload tier that distributes I/O across Google’s massive cluster-level filesystem, Colossus.

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With traditional offload architectures, higher block storage IOPS requires purchasing larger compute instances. For example, you may need to deploy a data-intensive workload on a compute instance with many more vCPUs than the workload needs just to get sufficient storage performance. This tight coupling results in wasted resources and higher costs for customers. Further, even with large instances, storage performance in the cloud may be inadequate relative to what customers are used to with on-prem storage systems.     

With our new block storage, Hyperdisk powered by Titanium, we have decoupled compute-instance size from storage performance. Hyperdisk uses a tier of offloads in our cloud fabric to offload storage I/O from the customer hosts to achieve higher storage performance even with a general-purpose VM.   

In fact, today we are announcing that Titanium-powered C3 VMs with Hyperdisk Extreme now support 500K IOPS per compute instance in preview to meet the needs of the most demanding workloads. This is 25% faster IOPS/instance compared to the other two leading hyperscalers, courtesy of the Titanium system. 

Example 2: Network routing
Virtual network routing is another example of using a second tier of scale-out offloads (“hoverboards”). With Titanium, Google’s Andromeda virtual networking stack on the IPU offload device sends all packets for which it does not have a route to Hoverboard gateways, which have forwarding information for all virtual networks. Hoverboards are standalone software switches that act as default routers for some flows.

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Unlike the traditional gateway model, the control plane dynamically detects flows that exceed a specified usage threshold and programs them to be direct host-to-host flows, bypassing the hoverboards allowing hoverboards to focus on the long tail of less frequent flows. Typically, only a small subset of possible VM pairs in a network communicate with one another, so the VMs only have to store and process a small fraction of the usual network configuration on an individual VM host, improving per-server memory utilization and control-plane CPU scalability.

Titanium already powers your workloads

The Titanium journey began years ago with the component technologies described above. Many of our products already benefit from this architecture, and the newest elements of this architecture are now available with our 3rd gen Compute Engine instances such as C3 and the new Hyperdisk block storage. 

Going forward, look for the Titanium architecture to underpin all future generations of our infrastructure offerings, in the process enabling new classes of infrastructure capabilities that move well beyond the confines of a single server.

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Confused about Cloud? Here is a Primer to get all Your Doubts Answered

When you have decided on moving workloads to the cloud, the task of choosing the right cloud platform can be a tough one with many questions looming in your mind. From which specific product to choose from the plethora of options available to how and where to store your data in the cloud to how secure is your data to how to get started on new and interesting projects like artificial Intelligence and machine learning, the questions can be endless.

However, what you need are answers for making a decision.

Get answers to some of the most commonly asked questions by customers from the Google Cloud Customer Engineers directy. From understanding the role of a Google Customer Engineer and how they can help you in your cloud journey to understanding the various products within the Google Cloud Platform for Infrastructure as a Service for hosting and running both managed VMs and containerized applications and Platform as a Service for building applications to the various fully managed data storage options for structured, unstructured, transactional or relational data, they have the answers to all your questions.

Watch this video to get answers to all your questions.

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Google Cloud and Ericsson to Deliver 5G and Edge Cloud Solutions

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Google Cloud and Ericsson announced partnership to transform user experiences across industry applications with 5G and edge solutions for CSPs and enterprises. This combo will serve as single pane of glass to manage and look beyond connectivity!

Editor’s note: 5G is much more than a network—it’s a platform for innovation with the ability to provide immediate global scale and enable use cases that we haven’t even dreamed of yet. But to achieve this, industry players must come together to drive this growing ecosystem. Today, Erik Ekudden, CTO of Ericsson, and Bikash Koley, VP of Global Networking at Google Cloud, share their insights into the potential of edge and 5G.

Experts consider 2021 to be the year that serves as the inflection point between network readiness and 5G availability. However, communications service providers (CSPs) are still faced with the task of modernizing their networks, systems, and infrastructure to maximize the potential of 5G for themselves and for the enterprise customers they serve. As you weigh whether to tackle this challenge, let’s first examine what’s different about 5G and how CSPs can best leverage 5G and the edge together as an even stronger platform for innovation than just 5G alone.

With 5G, applications and mobile networks are no longer isolated

Let’s first address what 5G brings to the table. Faster speeds and lower latency are expected of course, and throughout the evolution from 2G to 3G to 4G, there’s been a step function in performance improvements with each of these. However, with every generation, applications and networks have been like ships passing in the night. Networks have been unaware of what the applications have been doing and applications have been guessing what the network was capable of. 

What’s different this time around is that there is some real innovation happening with the development and rollout of 5G itself. The network is on a path to become more accessible via APIs so that applications can call on and consume what they need from the networks in a more programmable way. This sets us up for more open architectures and ecosystems.

5G leverages a more open architecture 

One key difference with 5G as compared to prior generations is that it’s the most open and flexible network architecture the CSP industry has seen. This is thanks to its service-based approach and the decoupling of hardware and software components. CSPs are now running core network elements in the public cloud, private cloud, hybrid cloud, and even multi-cloud, which was unthinkable even five years ago.

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The flexibility of this more open architecture allows us to push the cloud to the edge while still being able to manage it from a single pane of glass. This is a huge leap forward from traditional networks, which have been domain-specific, managed in silos, and with slow service creation and delivery. Now, hyperscale cloud vendors and network equipment providers are offering solutions that help CSPs break down these silos to enable more flexible, automated networks with improved orchestration, visibility, and control across multi-vendor, multi-cloud and hyperscale cloud-provider environments. In addition, the separation of hardware and software provides a much more flexible and cost-effective way to upgrade from one network generation to the next.

To provide solutions that are relevant to enterprises, CSPs must offer capabilities beyond connectivity. Enterprise service orchestration, including exposure of network assets and network slicing, are foundational capabilities to provide value to the application ecosystem and be in control of the network and the delivered services.

Combining 5G and edge to help industries reimagine user experiences

This convergence of compute, storage and networking at the edge coming together for the first time will enable CSPs and enterprises to offer their customers completely reimagined user experiences. Consider, for example, how the automotive industry might enhance how customers shop for a car. As part of Fiat Chrysler Automobiles’ Virtual Showroom at the recent CES 2021 event, consumers were able to experience the innovative new 2021 Jeep Wrangler 4xe by scanning a QR code with their phones, and then see an Augmented Reality (AR) model of the Wrangler right in front of them—virtually placed on their own driveway or in any open space.

By rendering the model in Google Cloud, then streaming it to mobile devices, visitors could also see what the car looked like from any angle, in different colors, and even step inside to see the interior in incredible detail. That is the true digitization of an industry segment and highlights the device-to-network-to-edge-to-cloud application relationship and how it can impact the user experience.

A programmable network unlocks more application use cases

The programmability of the 5G network will truly enable application developers to utilize all the benefits of the underlying network. Programmability supports ease of use and enables CSPs, integrated software vendors (ISVs) and the ecosystem to have the right network-level APIs exposed so that applications can be optimized based on the network behavior and vice versa. Imagine, for instance, automatically pushing applications from a cloud region to the edge based on network latency and performance metrics.

Finally, 5G’s programmability is also about having the right tools available for developers to build and integrate applications on the network with zero-touch onboarding and validation. With this, we’ve come to the point where the network is now a “platform” for application innovation. 

5G and edge will be all about the ecosystem

One thing is for certain: the shift to 5G will place tremendous focus on the ecosystem, and it needs to be an ecosystem that includes CSPs, public cloud providers, application developers and technology providers, all coming together to optimize the user experiences across industry applications. For instance, Google Cloud and Ericsson recently announced our partnership to deliver 5G and edge cloud solutions for CSPs and enterprise.  In addition, Google Cloud is also teaming up with popular ISVs to deliver more than 200 edge applications from 30-plus partners, all running on our cloud.  

With collaboration across ISVs, cloud providers and network equipment providers, we are enabling the rapid delivery and deployment of new vertical services and applications, leveraging capabilities like Anthos, artificial intelligence (AI), and machine learning (ML), as well as multi-vendor, multi-cloud and hyperscale cloud provider service orchestration and global edge networks such as those provided by Google and telecom service providers.

As members of the technology ecosystem, we talk about compute, storage and networking, but when it comes down to it, it’s about optimally placing these resources—whether in the cloud, at the provider core, at the edge or anywhere in between—to maximize the end-user experience. The openness and programmability of 5G lends itself to collaboration like never before. We predict that in 2022 and beyond, it will be all about the ecosystem coming together to leverage 5G and the edge to build innovations that we can’t yet imagine.

To learn more, watch the full Ericsson 5G Things CTO Focus fireside chat, where we discuss these topics and more.

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Navigating the Next Wave of B2B Digital Commerce: Trends and Insights for 2023

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B2B eCommerce is expanding with consumer-like experiences, omnichannel sales, and automation. As demand grows, Commercetools predicts continued digital transformation in B2B commerce in 2023, driven by new technologies and evolving customer needs.

Editor’s note: Google Cloud partner commercetools shares how modern technologies like composable commerce, cloud-native infrastructure and artificial intelligence/machine learning (AI/ML) will lead the way in business-to-business (B2B) digital commerce this year.


Digital commerce in B2B has been predicted as the next big thing for years; yet, at the start of COVID-19, 60% of B2B companies had zero or limited eCommerce capabilities. The pandemic accelerated digitization and eCommerce has finally taken off: As of February 2022, 65% of B2B companies offered eCommerce capabilities.

The behavior of B2B buyers is also changing: Consumer-like expectations are at the heart of successful B2B commerce, and this is how manufacturers, distributors and wholesalers will shape their customer experiences. Today, 73% of B2B buyers want a personalized business-to-consumer or B2C-like experience. 83% prefer ordering or paying through digital commerce and 72% are eager to purchase across channels.

With digital commerce dictating how B2Bs will grow in 2023 and beyond, what trends will spur digital transformations across this business model? Here’s what the team at commercetools expects to unfold in B2B eCommerce this year.

#1 B2B firms are switching to cloud-native, composable commerce

B2B players still plagued with manual processes and siloed backend systems will move away from monolithic platforms and choose composable commerce. In a nutshell, composability enables businesses to select best-of-breed components, such as search, cart or checkout, and “compose” them into a custom application.


B2B firms will modernize their commerce backend, interoperating siloed systems like Configure Price Quote solutions (CPQs) for sales and enterprise resource planning solutions (ERPs) for order entry with an API-first and composable commerce stack. They will also pivot from on-premise deployments to cloud-native architectures as the baseline for auto-scaling capabilities instead of pre-provisioning online capacity during traffic peaks. That way, B2Bs can customize customer-centric experiences to boost revenue while reducing the complexity and cost of in-house IT infrastructure, as well as gaining operational efficiencies

B2Bs will maximize the cross-section of composable commerce and cloud-native infrastructure by leveraging a commerce backend like commercetools Composable Commerce hosted on Google Cloud. This combined solution provides commercetools’ ready-to-use components built as microservices and exposed as APIs, such as product information management (PIM) and unified cart, integrated through the Google Cloud Marketplace.

#2 Strong focus on data quality and personalization

Focusing on data quality continues to be a big trend in 2023. B2B buyers expect product, pricing, inventory and shipping data points to be accurate across every touchpoint so they can make better purchasing decisions, such as when to order products and calculate quantities.

With so many data points to capture throughout the customer journey — product, inventory, pricing and customer data — we’ll see more B2B companies reorganizing their vast information pools to elevate customer experiences. They will pivot to modular and API-first solutions, plus flexible data models, so they can break data silos from legacy monolithic platforms and access such data when needed.

We also expect to see more customer analytics to unlock data on buyer behavior. By understanding what customers see, click and add to their shopping lists, B2B businesses get valuable insights into how buyers behave, using this data in the shopping journey according to product interests. That way, it’s possible to offer personalized experiences across touchpoints without hassle.

“It is important for B2B companies to look at their data as if it is one of their products; invest in its upkeep and integrity while finding ways to continuously improve it. Using advanced analytics powered by AI and ML to identify patterns from large amounts of data, B2B companies can activate insights into customer decision journeys to maintain loyalty, personalize experiences to improve satisfaction and boost revenue, while also finding ways to optimize costs. For example, with analytics, enterprises can streamline spend to focus on the highest-performing channels and reduce waste.”Carrie Tharp, Google Cloud VP of Retail and Consumer

With data-driven tools coming into play like Google Cloud’s Discovery AI, Recommendations AI and Vision Product Search connected with composable commerce, B2B players can boost customer analytics to personalize experiences, improve customer satisfaction and reduce churn.

#3 The B2B customer experience will be redesigned

B2B players are taking a page out of the B2C playbook to elevate experiences throughout the customer journey. While intense work needs to happen in the backend commerce engine, B2B players will also redesign their digital frontends. That means boosting website performance, while mobile responsiveness and personalization will be at the forefront of these advanced digital initiatives.

More than ever, B2B companies are looking for digital storefronts delivered as progressive web applications (PWAs) for optimized performance and responsiveness across devices, as well as fast-loading and responsive experiences to boost your digital presence, SEO rankings and conversion rate. B2Bs can further streamline frontend development with solutions natively connecting to Google Cloud Marketplace, which supports a variety of storefront providers, including commercetools Frontend.

Leveraging Google Cloud’s unique capabilities, such as PWA web app development, Google Cloud Discovery AI solutions that include Retail Search and Vision API Product Search, among many others, B2B companies are well positioned to boost digital commerce in the years to come.

What’s next in 2023?

2022 was already a turbulent year; for better or worse, 2023 is expected to have a similar fate. For B2Bs, even the ones with tight budgets, investing in digital commerce can help future-proof businesses for whatever’s happening this year. To dive deeper into all predictions and insights by commercetools in collaboration with Google Cloud, read the guide Pivotal Trends and Predictions in B2B Digital Commerce in 2023.

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Transitioning from Amazon Glacier to Google Cloud

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This comprehensive guide provides a detailed process for migrating archival workloads from Amazon Glacier to Google Cloud Storage Nearline in the Indian context. The process involves carefully planning data retrieval and staging strategies to ensure an efficient and cost-effective migration.

The whitepaper includes:

  • Different storage methods on Amazon Glacier and their respective retrieval processes.
  • Recommendations on managing retrieval costs to avoid high charges from Amazon Web Services.
  • The recommended rate for data availability and download to prevent unnecessary repetition of the process.
  • Utilization of Google Compute Engine for data staging, if stored directly in Amazon Glacier.
  • Use of command-line utility, gsutil, or the Storage Transfer Service for transferring data from the staging location to Google Cloud Storage Nearline.
  • Insights to achieve a streamlined and economical migration process from Amazon Glacier to Google Cloud Storage Nearline.
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LearningMate & Google Cloud Partnership to Aid Equitable Educational Opportunities

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Google Cloud and LearningMate designed, Student Success Services closes the digital gap among students and helps them learn with intelligent, user-friendly and personalized experiences built on AI and analytics tools. Explore more!

A “one size fits all” approach to education no longer works in today’s classrooms. Using cloud-based technologies, schools and educators can take a more personalized approach to education–one that suits each student’s unique learning style, abilities, and needs. 

Taking the lead toward more equitable educational opportunities worldwide, education technology pioneer, LearningMate, is partnering with Google Cloud to offer intelligent, personalized learning via Google Cloud’s Student Success Services.

In a student survey by EDUCAUSE, a nonprofit association whose mission is to advance higher education through the use of information technology, nearly all respondents asked for more digital learning and study options. Given a list of educational material types, such as study guides and recorded lessons, 93 percent said they would like to have online access to at least two options and more than half (56 percent) chose seven or more. 

The trend towards student choice challenges educators to reconsider how they teach and support learners. Students expect the same qualities in their lessons as they encounter in their other, non-school related digital experiences: personalization; user-friendliness; and engagement. Educators who are used to a more top-down education model can struggle to meet these new expectations. 

Google Cloud created Student Success Services to help education institutions meet learners where they are—in the digital age. This suite of tools and services uses Google’s advanced artificial intelligence (AI) and analytic tools to:

  • Engage with students via an AI-powered learning platform and interactive tutor
  • Help educators and learners collaborate more effectively
  • Provide current, actionable data on student progress 

To bring our Student Success Services to more schools and organizations worldwide, we’re partnering with LearningMate — a global leader in digital learning infrastructure. LearningMate is a key go-to-market partner, helping schools design, launch, and maintain their own learning infrastructure. To start, LearningMate is adding Google’s AI-powered learning platform to its Frost platform, a popular content management for education. 

As the education model continues to change and digital learning becomes the norm, disadvantaged students risk getting left behind. For these learners, the “digital divide” is very real, and stands to hinder them further–not only in school, but in society and the workplace in later life. 

“The gap will only widen between those with digital advantages and those who struggle to gain access to devices and network necessities,” EDUCAUSE states. To meet all these challenges, schools need a diverse mix of tools, methods, and partnerships.

To help close the digital divide among students, digital tools need to be able to scale up or down so institutions and districts of any size and budget can use them. Google Cloud designed Student Success Services with this ability in mind. By offering these services, LearningMate aims to ensure that even schools with smaller teams and fewer resources can offer individualized learning experiences to their students. 

With LearningMate and Google’s nearly 40 years of combined experience in education, this partnership aims to help educators better understand their students’ engagement, performance, and preferences. To learn more about Student Success Services and our collaboration with LearningMate, watch this session from our Government and Education Summit.

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Confidential Computing: Google Cloud Security, Project Zero and AMD Come Together to Secure Sensitive Workloads

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