Daily Archives: June 29, 2022

What is cloud computing?

Cloud computing is a general term for anything that involves delivering hosted services over the internet. These services are divided into three main categories or types of cloud computing: infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS).

A cloud can be private or public. A public cloud sells services to anyone on the internet. A private cloud is a proprietary network or a data center that supplies hosted services to a limited number of people, with certain access and permissions settings. Private or public, the goal of cloud computing is to provide easy, scalable access to computing resources and IT services.

Cloud infrastructure involves the hardware and software components required for proper implementation of a cloud computing model. Cloud computing can also be thought of as utility computing or on-demand computing.

The name cloud computing was inspired by the cloud symbol that's often used to represent the internet in flowcharts and diagrams.

Cloud computing works by enabling client devices to access data and cloud applications over the internet from remote physical servers, databases and computers.

An internet network connection links the front end, which includes the accessing client device, browser, network and cloud software applications, with the back end, which consists of databases, servers and computers. The back end functions as a repository, storing data that is accessed by the front end.

Communications between the front and back ends are managed by a central server. The central server relies on protocols to facilitate the exchange of data. The central server uses both software and middleware to manage connectivity between different client devices and cloud servers. Typically, there is a dedicated server for each individual application or workload.

Cloud computing relies heavily on virtualization and automation technologies. Virtualization enables the easy abstraction and provisioning of services and underlying cloud systems into logical entities that users can request and utilize. Automation and accompanying orchestration capabilities provide users with a high degree of self-service to provision resources, connect services and deploy workloads without direct intervention from the cloud provider's IT staff.

Cloud computing can be separated into three general service delivery categories or forms of cloud computing:

Private cloud services are delivered from a business's data center to internal users. With a private cloud, an organization builds and maintains its own underlying cloud infrastructure. This model offers the versatility and convenience of the cloud, while preserving the management, control and security common to local data centers. Internal users might or might not be billed for services through IT chargeback. Common private cloud technologies and vendors include VMware and OpenStack.

In the public cloud model, a third-party cloud service provider (CSP) delivers the cloud service over the internet. Public cloud services are sold on demand, typically by the minute or hour, though long-term commitments are available for many services. Customers only pay for the central processing unit cycles, storage or bandwidth they consume. Leading public CSPs include AWS, Microsoft Azure, IBM and Google Cloud Platform (GCP), as well as IBM, Oracle and Tencent.

A hybrid cloud is a combination of public cloud services and an on-premises private cloud, with orchestration and automation between the two. Companies can run mission-critical workloads or sensitive applications on the private cloud and use the public cloud to handle workload bursts or spikes in demand. The goal of a hybrid cloud is to create a unified, automated, scalable environment that takes advantage of all that a public cloud infrastructure can provide, while still maintaining control over mission-critical data.

In addition, organizations are increasingly embracing a multi-cloud model, or the use of multiple IaaS providers. This enables applications to migrate between different cloud providers or to even operate concurrently across two or more cloud providers.

Organizations adopt multi-cloud for various reasons. For example, they could do so to minimize the risk of a cloud service outage or to take advantage of more competitive pricing from a particular provider. Multi-cloud implementation and application development can be a challenge because of the differences between cloud providers' services and APIs.

Multi-cloud deployments should become easier, however, as providers' services and APIs converge and become more standardized through industry initiatives such as the Open Cloud Computing Interface.

A community cloud, which is shared by several organizations, supports a particular community that shares the same concerns -- e.g., the same mission, policy, security requirements and compliance considerations. A community cloud is either managed by these organizations or a third-party vendor and can be on or off premises.

Cloud computing has been around for several decades now, and today's cloud computing infrastructure demonstrates an array of characteristics that have brought meaningful benefits for businesses of all sizes. Some of the main characteristics of cloud computing are the following:

These characteristics support a variety of important benefits for modern business, including the following:

Despite the clear upsides to relying on cloud services, cloud computing carries its own challenges for IT professionals:

Cloud computing has evolved and diversified into a wide array of offerings and capabilities designed to suit almost any conceivable business need. Examples of cloud computing capabilities and diversity include the following:

So, how is the cloud actually used? The myriad services and capabilities found in modern public clouds have been applied across countless use cases, such as the following:

Given the many different services and capabilities of the public cloud, there has been some confusion between cloud computing and major uses, such as web hosting. While the public cloud is often used for web hosting, the two are quite different. A cloud service has three distinct characteristics that differentiate it from traditional web hosting:

The cloud service market has no shortage of providers. The three largest public CSPs that have established themselves as dominant fixtures in the industry are the following:

Other major CSPs include the following:

When considering a cloud service vendor, certain considerations should be taken. First, the actual suite of services can vary between providers, and business users must select a provider that offers services -- such as big data analytics or artificial intelligence (AI) services -- that support the intended use case.

Though cloud services typically rely on a pay-per-use model, different providers often have variations in their pricing plans to consider. Furthermore, if the cloud provider will be storing sensitive data, physical location of the provider's servers should also be considered.

Naturally, reliability and security should be top priorities. A provider's service-level agreement should specify a level of service uptime that is satisfactory to client business needs. When considering different cloud vendors, close attention should be given to what technologies and configuration settings are used to secure sensitive information.

Security remains a primary concern for businesses contemplating cloud adoption -- especially public cloud adoption. Public CSPs share their underlying hardware infrastructure between numerous customers, as the public cloud is a multi-tenant environment. This environment demands significant isolation between logical compute resources. At the same time, access to public cloud storage and compute resources is guarded by account login credentials.

Many organizations bound by complex regulatory obligations and governance standards are still hesitant to place data or workloads in the public cloud for fear of outages, loss or theft. However, this resistance is fading, as logical isolation has proven reliable and the addition of data encryption and various identity and access management tools have improved security within the public cloud.

Ultimately, the responsibility for establishing and maintaining a secure cloud environment falls to the individual business user that is responsible for building the workload's architecture -- the combination of cloud resources and services in which the workload runs -- and implementing the security features that the cloud provider offers.

The history and evolution of cloud computing date back to the 1950s and 1960s.

In the 1950s, companies started to use large mainframe computers, but it was too expensive to buy a computer for each user. So, during the late 1950s and early 1960s, a process called time sharing was developed to make more efficient use of expensive processor time on the central mainframe.

Time sharing enabled users to access numerous instances of computing mainframes simultaneously, maximizing processing power and minimizing downtime. This idea represents the first use of shared computing resources, the foundation of modern cloud computing.

The origins of delivering computing resources using a global network are, for the most part, rooted in 1969 when American computer scientist J.C.R. Licklider helped create the Advanced Research Projects Agency Network, the so-called precursor to the internet. Licklider's goal was to connect computers across the globe in a way that would enable users to access programs and information from any location.

In the 1970s, cloud computing began taking a more tangible shape with the introduction of the first VMs, enabling users to run more than one computing system within a single physical setup. The functionality of these VMs led to the concept of virtualization, which had a major influence on the progress of cloud computing.

In the 1970s and 1980s, Microsoft, Apple and IBM developed technologies that enhanced the cloud environment and advanced the use of the cloud server and server hosting. Then, in 1999, Salesforce became the first company to deliver business applications from a website.

In 2006, Amazon launched AWS, providing such services as computing and storage in the cloud. Following suit, the other major tech players, including Microsoft and Google, subsequently launched their own cloud offerings to compete with AWS.

Over 30% of enterprise IT decision-makers identified public cloud as their top priority in 2019, according to the "RightScale 2019 State of the Cloud Report." Still, enterprise adoption of the public cloud, especially for mission-critical applications, hasn't been happening as quickly as many experts predicted.

Today, however, organizations are more likely to migrate mission-critical workloads to public clouds. One of the reasons for this shift is that business executives who want to ensure that their companies can compete in the new world of digital transformation are demanding the public cloud.

Business leaders are also looking to the public cloud to take advantage of its elasticity, modernize internal computer systems, and empower critical business units and their DevOps teams.

Additionally, cloud providers, such as IBM and VMware, are concentrating on meeting the needs of enterprise IT, in part by removing the barriers to public cloud adoption that caused IT decision-makers to shy away from fully embracing the public cloud previously.

Generally, when contemplating cloud adoption, many enterprises have been mainly focused on new cloud-native applications -- that is, designing and building applications specifically intended to use cloud services. They haven't been willing to move their most mission-critical apps into the public cloud. However, these enterprises are now beginning to realize that the cloud is ready for the enterprise if they select the right cloud platforms, i.e., those that have a history of serving the needs of the enterprise.

Cloud providers are locked in ongoing competition for cloud market share, so the public cloud continues to evolve, expand and diversify its range of services. This has led public IaaS providers to offer far more than common compute and storage instances.

For example, serverless, or event-driven, computing is a cloud service that executes specific functions, such as image processing and database updates. Traditional cloud deployments require users to establish a compute instance and load code into that instance. Then, the user decides how long to run -- and pay for -- that instance.

With serverless computing, developers simply create code, and the cloud provider loads and executes that code in response to real-world events so users don't have to worry about the server or instance aspect of the cloud deployment. Users only pay for the number of transactions that the function executes. AWS Lambda, Google Cloud Functions and Azure Functions are examples of serverless computing services.

Public cloud computing also lends itself well to big data processing, which demands enormous compute resources for relatively short durations. Cloud providers have responded with big data services, including Google BigQuery for large-scale data warehousing and Microsoft Azure Data Lake Analytics for processing huge data sets.

Another crop of emerging cloud technologies and services relates to AI and machine learning. These technologies provide a range of cloud-based, ready-to-use AI and machine learning services for client needs. Amazon Machine Learning, Amazon Lex, Amazon Polly, Google Cloud Machine Learning Engine and Google Cloud Speech API are examples of these services.

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What is Cloud Computing? Everything You Need to Know

Cloud computing is in its beginning stages and will only continue to grow, Amazon Web Services CEO Adam Selipsky told CNBC's Jim Cramer on Tuesday.

"It's possible that AWS could become the largest business at Amazon. Now, Amazon has other large and great businesses, and so it could take a while for us to get there," Selipsky said in an interview on "Mad Money."

"Essentially, IT is going to move to the cloud. And it's going to take a while. You've seen maybe only, call it 10% of IT today move. So it's still day 1. It's still early. Most of it's still yet to come," he added.

The cloud business' revenue in the first quarter beat the consensus among analysts polled by StreetAccount, accounting for roughly 16% of Amazon's total revenue. AWS grew faster from the same period a year before than analysts expected.

AWS was launched in 2006, before competitors Microsoft's Azure or Alphabet's Google Cloud Platform, and has notable collaborations with Goldman Sachs, Stellantis and Best Buy.

Selipsky said that despite the heightened competition in the industry and the threat of a recession, AWS is continuing to do well.

"Demand continues to be strong, with lots of new customers signing up and existing customers expanding," he said.

Disclosure: Cramer's Charitable Trust owns shares of Alphabet, Amazon and Microsoft.

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AWS CEO says the move to cloud computing is only just getting started - CNBC

DUBLIN--(BUSINESS WIRE)--The "Growth Opportunities in Cloud, Artificial Intelligence, and Edge Computing" report has been added to ResearchAndMarkets.com's offering.

This edition of IT, Computing and Communications (ITCC) Technology Opportunity Engine (TOE) provides a snapshot of the emerging ICT led innovations in Cloud, Artificial Intelligence and Edge Computing.

This issue focuses on the application of information and communication technologies in alleviating the challenges faced across industry sectors in areas such as retail, industrial, BFSI, and automotive.

ITCC TOE's mission is to investigate emerging wireless communication and computing technology areas including 3G, 4G, Wi-Fi, Bluetooth, Big Data, cloud computing, augmented reality, virtual reality, artificial intelligence, virtualization and the Internet of Things and their new applications; unearth new products and service offerings; highlight trends in the wireless networking, data management and computing spaces; provide updates on technology funding; evaluate intellectual property; follow technology transfer and solution deployment/integration; track development of standards and software; and report on legislative and policy issues and many more.

Innovations in Cloud, Artificial Intelligence, and Edge Computing

For more information about this report visit https://www.researchandmarkets.com/r/37mrl6

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IT, Computing and Communications (ITCC) Technology Innovations/Growth Opportunities Report 2022 with Focus on Cloud, Artificial Intelligence, and Edge...

As organizations harness digital technologies to reimagine both customer and employee experiences, theres been an exponential rise in the adoption of a multi-cloud strategy. Recent years have seen cloud computing gaining almost universal adoption. In fact, by 2025, the Indian public cloud services market is expected to reach $10.8 billion and is growing at a CAGR from 24.1% for 2020-25 .

While multi-cloud delivers greater efficiency, agility and scalability to organizations, it can come with certain trade-offs for businesses. Given the increasing dominance of cloud solutions in modern workplaces, unfortunately several half-truths and misconceptions about multi-cloud have been widely accepted. Here are a few myths surrounding multi-cloud that need to be debunked:

Myth 1. Most enterprises rely on one cloud providerNot really, but know why you need a multi-cloud approach

Enterprises have realized that relying on a single cloud infrastructure provider for all their applications and workloads is not the right strategy. As per a research on public cloud users, 81% of enterprises said they are working with two or more providers.Most enterprises have diversified their multi-cloud strategy to utilize the best-of-breed solutions. Having a choice of multi-cloud providers is best opted for meeting business needs. The research also suggests that enterprise buyers choose multiple cloud providers for hybrid deployment and another cloud provider for managing workloads to avoid limitations.

Large organizations are turning to create a multi-cloud strategy to enhance agility and reduce vendor lock-in, cost and flexibility. With cloud infrastructure evolving rapidly, its not a wise step to depend on a single cloud provider. Adopting a multi-cloud approach that prioritizes application development and workloads, where each works best, allows you to optimize with the speed, agility and security you need.

Myth 2. Multi-cloud is expensiveOr is it a cost-effective solution to help you reap more benefits?

A study revealed that 53% of users said multi-cloud has helped them achieve their business goals.When fully optimized, multi-cloud architectures can help businesses accelerate service delivery while reducing costs and business risk. Companies can deliver transformational apps more quickly to customers and employees, thereby strengthening their competitive positions.

Organizations with multi-cloud architectures have:

Myth 3. Multi-cloud complexity outweighs its benefitsCan visibility across clouds simplify operations?

Multi-cloud architectures are complex today and the complexity is likely to increase in the future as companies deploy more workloads to the cloud, sometimes spread across multiple clouds. There will be new cloud offerings from 5G telco providers, more clouds in edge locations, and an increased focus on security and spend. One significant limitation of managing multiple clouds is that the toolsets that providers offer typically can only function within their own cloud. This requires multiple teams to manage individual clouds in parallel, reducing efficiency and increasing cost and complexity.

Consistency with visibility across clouds at infrastructure and management level can overcome these complexities and can turn into an opportunity. It can help enterprises gain a competitive advantage in todays evolving economy while enabling organizations to map out well-crafted strategies and innovate at speed. Its no wonder, that 91% of executives want to improve consistency across their public cloud environments. According to IDC, around 30% of Indian enterprises will deploy unified Virtual Machines, Kubernetes, and multi-cloud management processes and tools to support robust multi-cloud management and governance across on-premises and public clouds.

Views expressed above are the author's own.

END OF ARTICLE

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Debunking the top 3 myths around multi-cloud computing - Times of India

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Worldwide Hybrid Cloud Computing Market is expected to grow at a CAGR of 34.3% during the forecast period 2016-2022.

The digital economy affects the worlds trajectory and the societal well-being of common citizens. In addition, it influences everything from resource assignment to income allocation and economic growth. The adoption of the Internet of Things is pushing significant market growth. Additionally, in 5-10 years, the latest technologies such as robotics, AI, and augmented reality can illustrate around 27% of ICT spending. Consumer demand for access to content and products at any time and from any location is propelling the ICT market forward. The ICT sector is lucrative for vendors since it has about 7 billion mobile subscribers and 3 billion Internet, users.

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Key Players Covered in the ReportDell Inc.Amazon Web Services Inc.VMware Inc.Rackspace Hosting Inc.RightScale Inc.Cisco Systems Inc.EMC CorporationComputer Sciences CorporationAT&T Inc.Equinix Inc.Citrix Systems Inc.Oracle CorporationMicrosoft CorporationInternational Business Machines CorporationGreen House DataAtlantic.NetVelostrata

Market Overview

Globally enterprises are opting for hybrid cloud technologies to leverage cost savings and technical expertise to focus on its core business. Organizations can easily shift their non-critical data and applications from private to the public cloud to reduce the web traffic. The next five years will see an explosion in the use of hybrid cloud as it helps organizations to save cost on infrastructure and application support. Nearly 82% of the enterprises have hybrid cloud strategy for 2018. Hybrid cloud provides a single solution to organizations involved in multiple verticals. It can be applied to any industries including power media & entertainment complex computing healthcare government education analytics and much more. More than 60% of the large enterprises are planning to implement hybrid clouds by 2020.

A rapid increase in the private cloud adoption is driving the hybrid cloud market with nearly 82% of the enterprises planning to have a hybrid cloud strategy by 2017. The pay per use model is useful and affordable to the enterprises across all the verticals and regions. Cloud governance has witnessed a rapid growth with nearly 30% of the enterprises having established approval policies and by 2018 more than 50% will have approved cloud policies. According to Reportocean research the Worldwide Hybrid Cloud Computing Market is expected to grow at a CAGR of 34.3% during the forecast period 2016-2022.

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Banking & financial services consumer goods & retail healthcare manufacturing media & entertainment energy & utilities government telecommunication and IT transportation & logistics and others. The manufacturing industry is set to be the leading vertical for hybrid cloud computing market and telecommunication and IT industry is set to be the emerging vertical for the market growth. The regions covered are North America Latin America Western Europe Central Eastern Europe Asia Pacific Latin America and the Middle East & Africa. North America is expected to outperform in the market growth along with Asia Pacific which is expected to provide huge opportunities in hybrid cloud computing market space.

The report provides a complete picture (vertical market opportunity regional market opportunity challenges current market trends future market trends evolution technology roadmap etc.) of the hybrid cloud computing market.

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Region/Country Cover in the Report

RegionsNorth America (US Canada)Western Europe (UK Germany France Italy Spain)Asia Pacific (Japan South Korea China India)Central Eastern Europe (Poland Russia Turkey)Latin America (Brazil Mexico Argentina)Middle East & Africa (GCC Africa)

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The main objective of this study is to understand the world hybrid cloud market. The focus is on different hybrid cloud services and applications available in the market with a keen focus on Application Architecture Network Integration and Management Systems. The report explains in detail about the industry structure of the hybrid cloud penetration across the various industry sectors the total market size of the world hybrid cloud industry and its segments. One of the important aspects of the report is the future outlook which gives a fair idea of how the industry is going to perform in the coming years. In addition the report also discusses the key players in the market how hybrid cloud technology supports organisations to shift data and applications from private to the public cloud to reduce the web traffic.

The world hybrid cloud market estimate in 2016 is $41.15 billion and the estimated market for 2022 is $241.13 billion driven by all segments of the industry. The high growth is mainly from Manufacturing and Telecommunication & IT industries. The Software as a Service (SaaS) sector is expected to grow at a fast pace in the next five years with the expected compound annual growth rate (CAGR) of 34.1% by 2022.

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Table of Content:

What is the goal of the report?

The market report presents the estimated size of the Industrial automation market at the end of the forecast period. The report also examines historical and current market sizes. During the forecast period, the report analyzes the growth rate, market size, and market valuation. The report presents current trends in the industry and the future potential of the North America, Asia Pacific, Europe, Latin America, and the Middle East and Africa markets. The report offers a comprehensive view of the market based on geographic scope, market segmentation, and key player financial performance.

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Hybrid Cloud Computing Market 2022 Report, Analysis from Perspective of Segmentation, New Technology and Forecast till 2030 Designer Women - Designer...

When Thomas Kurian landed the CEO role at Google Cloud, he was welcomed as a respected technologist and executive bringing 22 years of needed enterprise chops from Oracle for a substantial undertaking: turning an underdog into a heavyweight contender for meeting major corporations cloud needs.

At the Google Cloud Next conference in early 2019, Alphabet and Google CEO Sundar Pichai introduced Kurian, then about three months into his tenure, as a tremendous leader with a powerful vision who already had met with hundreds of customers and partners and whose personal productivity is testing the limits of G Suite and Calendar.

Before leaving Oracle, Kurian had been its product development president since 2008, reporting directly to founder and chairman Larry Ellison. In early 2018, it was Kurian who unveiled Oracles ambitious plan to build up its own cloud capabilities with a massive buildout of its data center footprint and services using machine learning to automate routine operations. Growing differences with Ellison over Oracles cloud direction including Kurians desire for a multicloud approach reportedly led to his departure.

Three and a half years into his tenure at Google Cloud, the bet on multicloud has been a key foundation of Kurians reshaping of the No. 3 cloud provider around infrastructure, data analytics, cybersecurity, collaboration and communication, and industry-specific products and services. In his view, the next decade of cloud computing is likely to look very different from the first 16 years of its evolution.

Google Clouds success can be seen in its financial results revenue has increased some 230% since Kurian joined Google Cloud, and is on track to exceed $23 billion this year and customer adoption from the likes of Deutsche Bank, Ford Motor Company, Mayo Clinic, Univision and the U.S. Air Force, Kurian told Protocol in a recent interview.

There's always more to be done at all times, but clearly we've had a lot of success these last three years, he said.

This interview has been edited and condensed for clarity. Read our other story on the evolution of Google Cloud here.

Is Google Cloud enterprise-ready or is it still a work in progress, and what are the indicators of that?

It's the customers who indicate that. And given the number of very large customers from stock exchanges, to large telecommunications companies, to big banks, to hospital systems, manufacturing companies that are running large systems and using our cloud to run the core parts of their business I would say, yes, the answer is yes. We've really, really transformed, and most of our largest customers have been super successful in adopting and using cloud through the work they've done with us. So we definitely feel very confident we're doing that.

Where do we have more work to do? Obviously, we have a certain size and scale. We want to expand to more countries, to more industries, and there's a lot of work going on to expand both our data center footprint around the world, as well as our sales, distribution and service organizations around the world. So there is more expansion that we want to do globally to bring our technology to more countries, more places.

Where do you see the most opportunity to expand globally?

We've expanded significantly overseas in Europe. We are growing very quickly in Latin America. We're expanding in Asia to many more markets. We are quite strong in the big markets, which is India, Australia, New Zealand, Korea, greater China and ASEAN, but there's always more places in Asia, whether that's in Thailand, Vietnam, etc. Similarly, in Latin America, there's a lot of potential for growth. There's more that we want to grow in Japan. We are expanding our presence in Africa. So there's a lot more other geographies that we want to go to in addition to expanding in our core geos, whether that's the U.K., France, Germany, United States, Canada, etc.

How market-share-oriented is Alphabet when it comes to Google Cloud? And if not market share, what is it using as a metric for success?

Despite the growth that people have seen so far, the market is very early in its transition, and so we see the market potential in three different ways. First of all, many customers have not yet transitioned [to the cloud]. Secondly if you look at surveys from Gartner, IDC, the analyst firms, they will tell you that almost all large customers plan to use multiple cloud providers, which was not true a few years ago.

So when you look at the market, whether that's new solutions like analytics or cybersecurity, these are all new segments that are opening up for cloud. We think the market is in its early stages. So we're investing for growth and investing in terms of both our investments in capital, data centers and our global network, in products and in go to market. And we're doing it in a thoughtful way. I think you've seen our financial results, and both the growth and the improvement of profitability because of the growth speaks for itself.

Sundar Pichai and Alphabet CFO Ruth Porat have said that Alphabet is in it for the long term with Google Cloud. Is there any timeframe under which you have to meet a certain measure?

No, when we say long term, five to 10 years. If you look at the cloud market data today versus five years ago, it's vastly different.

Five years ago, if you talked to customers, there was a lot of anxiety that if you go to the cloud, will it be less secure, as an example. Today, cybersecurity tools that we offer in our cloud are being used by large retailers, large financial institutions, large telecommunications companies. A market segment that did not exist in the cloud five years ago cybersecurity tools is now being created in the cloud as a new opportunity for people to go after. So in our view, we are looking at growing our business, diversifying the product portfolio in a thoughtful way. And how the market looks in five years or 10 years will be quite different than the way it looks like today.

Is Google Cloud's embrace of multicloud a big selling point, and what are customers with a multicloud strategy coming to Google Cloud for?

If you went back and looked at our announcement in April 2019, where we said we are going to enable multicloud and what we mean by that is you can build applications that can co-exist across clouds, you can do analytics that spans data that sits across clouds, you can use our machine-learning tools to access information and get better insights from data and inference across clouds that was not possible before then. It's become almost a norm now in large companies, where they want to use the best of the best from different cloud providers.

People come to us for our infrastructure. Many people come to us for our analytics and large-scale data processing and databases. Others come to us to protect their systems with cybersecurity. It really depends on the customer and which part of the journey they're on. Infrastructure, analytics and data, and cybersecurity are typically the top three that people choose us for.

Do you see any holes in your technology or areas that you want to beef up?

We're always looking at where we have areas for potential growth and where the market itself is changing, and then either we organically build new capability or we acquire.

As an example, if you look at our rationale for Mandiant [a detection-and-response cybersecurity company that Google Cloud announced it was buying for $5.4 billion in March]. There are two primary challenges we see that organizations have with cybersecurity.

First of all, very few organizations, if any, know whether they're truly secure. Almost every cyber breach for most organizations are black swan events. They thought they were secure prior to it; after it occurred, they realized they were not secure.

Infrastructure, analytics and data, and cybersecurity are typically the top three that people choose us for.

The second is people want a platform. Today, the challenge most organizations have is they don't have the capability to understand what occurred to cause a cyber breach, [to] analyze which of your systems have been compromised, [to] remediate that through workflow and then test whether you, in fact, are secure. We have two of the pieces. We have the analyze whether you're being compromised [piece] and then remediate the breach through workflow.

We realized in the front, we needed really great threat detection and response capability. Mandiant brought us that. And then at the end, after you've gone through all of this, you have to actually be able to test whether you are secure from the breach if it were to happen again. Mandiant also has the capability to do that. So recognizing that combination would complement what we had, we chose in this particular instance to say, Let's acquire a company that will complement our products and fill it out.

We wanted customers to have a very high-end, relational database transaction-processing platform based on an open platform. [In May,] we announced a new product at [Google] I/O called AlloyDB. It's designed to allow people who are running large-scale transaction systems, but to use a much [more] open platform database to process large-scale transactions with great performance and reliability.

The second thing we saw was people really love our BigQuery [serverless data warehouse] technology. They like the fact not only is it a very scalable, analytical platform, but it also allows them to access and analyze data across clouds, meaning you could have your data in another cloud, and you can still analyze that using BigQuery. You don't have to move all your data to our cloud for the purpose of analysis. We then felt that you would want the equivalent capability for something called a data lake, and so we announced a product called BigLake, an evolution of our analytic platform to support the notion of a large-scale, very scalable data lake that can run across data stored in multiple environments.

So these are all areas where we look at the needs of customers, we look at what we can help them solve. In the case of Mandiant, we chose to acquire because we think they're an exceptional team, and they have exceptional technology and exceptional expertise. In the case of these other two products we've chosen to build out ourselves.

Which vertical industries are getting the most traction for Google Cloud?

We have traction in many industries. If you look at financial services, we have a lot of traction with our data platform, analytics, machine-learning tools and AI. If you look at retail, we are a huge part of the ecommerce infrastructure as well as the retail store transformations that are going on. If you look at health care, many pharmaceutical and biomedical companies use our platforms for molecular modeling, genetic analysis of all kinds, etc. what's sometimes called high-performance computing. If you look at public-sector agencies, many state governments, for example, in the United States are using us to transform health and human services, transformation of their mobility and transportation departments, etc.

Telecommunications is another one. We have a lot of capability in media, given our expertise in streaming and other things from the work we've done historically with YouTube and how we're bringing that to customers. A lot of people during the pandemic spent a lot of time gaming, and our platforms have helped some of the largest games in the world.

What's behind Google Clouds recent reorganization of its sales and customer success teams? Was the previous setup built in 2019 under former global sales president Rob Enslin not working? And when you reorganize these teams again, are you worried about the signal its sending the customers?

We've talked to many customers and partners. I've talked to over 100 of them in the last week alone, and over 200 in the last two weeks. Customers' and partners' feedback are the rationale for [why] the changes make sense.

When we started in 2019, we were largely focused on acquiring customers. When I say acquiring customers [I mean] winning new customers, because we had very few. As we have ramped our business, increasingly, the sales organization that's working with the customer to identify new opportunities in the account, and the customer success team that ensures the projects are going well, and the team that works with partners like Accenture, Deloitte, etc., all need to come together, because the salesperson is identifying the opportunity, the customer success coordinates the engagement with the partners, etc. So they all need to work in one coherent fashion, right at the point of client engagement.

We integrated the two organizations in each geography so that they could be much more effective working with customers. The feedback internally from our own teams and the feedback from customers and partners has been, we really like what you've done. So we're very confident in the quality of our leadership, in what the changes have been, how the changes have been made. And we remain committed to making sure that this change will help our customers grow and mature their relationships with us.

What are top customer complaints or challenges that you're trying to address?

Our biggest challenge right now is expanding globally. There's demand in many countries where we don't have presence. There are lots of places we'd like to take it to, and building an organization to support those expansions is obviously something that we spend a lot of time on.

Are any of your enterprise customers asking for more help to cut costs given inflationary pressures, and what are you doing to address that?

We have a team from our professional services that works with customers and our technical account managers to do what's called cost optimization. Cost optimization is, you're running your workload on our cloud, you have a certain pattern of usage, [and] we observe the pattern of usage after you've got to some steady state and then we teach you how best to modify the way in which you're using the cloud to be much more efficient in cost. We have tools that show people how to do that. It's a methodology that we offer, and it's also something we make available through our services teams to support customers. It's something that's been ongoing for the last two years, and certainly for an ongoing basis.

Throughout the pandemic as well as now, [customers have] come to us saying, Hey, I'd like to have you help me reduce my costs in this area or that area, and we work with them. It's part of getting them to be efficient in using our cloud. We think the more effective we can be at teaching them how to optimize, the more they will use in the future.

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Google Cloud CEO Thomas Kurian: Cloud computing is on the brink of a new era - Protocol

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Cloud adoption has rocketed as companies seek computing and storage resources that can be scaled up and down in response to changing business needs. But even given the cost and agility upsides to cloud, theres rising interest in yet another deployment model edge computing, which is computing thats done at or near the source of the data. It can empower new use cases, especially the innovative artificial intelligence and machine learning applications that are critical to modern business success.

The promise of the edge comes down to data, according to three industrial technologists who spoke at the recent Future Compute conference hosted by MIT Technology Review. Specifically, there is a need to gather, process, and analyze data closest to where its being generated, whether thats on the factory floor, in an autonomous vehicle, or in a smart building system.

The ability to run artificial intelligence models directly on data at the edge without the extra step of moving workloads to the cloud reduces latency and costs. Most important, it is the key to unlocking the real-time insights that separate the leaders from the laggards, the panelists agreed.

Companies are starting to recognize the role edge computing can play in driving successful data-driven business transformation. Gartner estimates that while only 10% of enterprise data was created and processed outside the data center and cloud in 2018, this number will be 75% by 2025.

George Small, the chief technology officer of Moog Inc., a $3 billion motion control solutions company, said hes seen measurable progress from edge applications.

There's real use cases. We're now seeing where value's being created, he said. It's actually making significant improvements in productivity.

As companies move ahead with data-driven business, they need to create an IT landscape that includes both edge and cloud computing. Data collected and analyzed at the edge can initiate a real-time response to troubleshoot a piece of industrial equipment to prevent machinery downtime or to redirect a self-driving car out of harms way.

At the same time, device data from that machine or vehicle can be sent to the cloud and aggregated with other data for more in-depth analysis that can drive smarter decision making and future business strategy.

Gartner estimates that 10% of enterprise data was created and processed outside the data center and cloud in 2018.

Connectivity has gotten to the point that its a baseline, which is feeding this idea of an intelligent edge, Small said.Intelligence starts at a sensing level at the edge and spans to a networked system of systems that ultimately gets to cloud. We look at it as a continuum.

Moog is experimenting with edge computing for a variety of applications, Small said. In the agricultural space, the company is using edge capabilities and machine learning recognition for almond and apple farming, helping harvesting equipment autonomously navigate terrain and improve crop yields. In construction, Moogs edge and AI-based automation efforts are focused on material movement for example, turning a piece of an excavator into a robotic platform to enable automation, Small said.

Ongoing labor and productivity challenges drove Moog to experiment with edge-based automation in the agriculture sector, Small said.

There are opportunities where you dont have as much of a structured environment or people need to interact with the actual work site, he said. That was our introduction to this definition of edge. We came at it from the point of view of automating a vehicle.

Another potential use case combines edge computing, 3D printing, and blockchain to orchestrate on-demand, on-location output of spare parts. Moog customers in sectors like aerospace and defense could create spare parts for critical equipment on-site, using blockchain as a means to verify the providence and integrity of the part, Small said.

At Honeywell Building Technologies, edge computing is a key part of transforming building operations to improve quality of life, said Manish Sharma, vice president and general manager of Honeywells sustainable building technologies. Smart edge sensors monitor temperature, humidity, and CO2 levels, helping to create an intelligent building system that can automatically adjust energy and lighting use to keep costs down while optimizing for carbon neutrality and maintaining building comfort.

Connecting heating, cooling, and air filtering systems to edge devices creates an intelligent network that facilitates data sharing and makes smarter decisions closer to where they have the most impact.

Youre building a system of systems and to do the right computation, you need to have a common network where data can be shared and decisions can be made at the edge level in a matter of milliseconds, Sharma said.

The panelists outlined some best practices that can help companies identify the right candidates for edge deployments while avoiding some of the more common deployment challenges.

Move computing power to where the data is. Determining whether edge or cloud is optimal for a particular workflow or use case can cause analysis paralysis. Yet the truth is the models are complementary, not competing.

The general rule of thumb is that youre far better moving compute to the data than vice versa, said Robert Blumofe, executive vice president and chief technology officer at Akamai. By doing so, you avoid back hauling, which hurts performance and is expensive.

Consider an e-commerce application that orchestrates actions like searching a product catalog, making recommendations based on history, or tracking and updating orders.

It makes sense to do the compute where that data is stored, in a cloud data warehouse or data lake, Blumofe said. The edge, on the other hand, lends itself to computing on data thats in motion analyzing traffic flow to initiate a security action, for example.

Go heavy on experimentation. Its still early days in edge computing, and most companies are at the beginning of the maturity curve, evaluating how and where the model can have the most impact. Yet capabilities are improving rapidly and companies cant afford to remain on the sidelines.

You really need to start pushing because there is value to be created, Small said. You have to be out there looking for new opportunities youre not just going to think them up, you have to find them.

Dont skip over ROI. Edge-enabled automation can help companies do more with less labor and free up people to do higher value-added work, noted Moogs Small. But in addition to those obvious first-order productivity gains, there are other, harder to quantify benefits from automation at the edge, including repeatability, he said.

Read next: What Satya Nadella thinks about work of the future

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The promise of edge computing comes down to data - MIT Sloan News