The Global Cloud Computing in Industrial IOT Market is expected to grow from USD 3,966.66 Million in 2019 to USD 7,078.35 Million by the end of 2025…

New York, June 11, 2020 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Cloud Computing in Industrial IOT Market Research Report by Sensor Type, by Model, by Cloud Type, by End User - Global Forecast to 2025 - Cumulative Impact of COVID-19" - https://www.reportlinker.com/p05913858/?utm_source=GNW

On the basis of Sensor Type, the Cloud Computing in Industrial IOT Market is studied across Optical Sensors, Pressure Sensors, Proximity Sensor, and Temperature Sensors.

On the basis of Model, the Cloud Computing in Industrial IOT Market is studied across Infrastructure As A Service (IaaS), Platform As A Service (PaaS), and Software As A Service (SaaS).

On the basis of Cloud Type, the Cloud Computing in Industrial IOT Market is studied across Hybrid, Private, and Public.

On the basis of End User, the Cloud Computing in Industrial IOT Market is studied across Energy, Healthcare, Manufacturing, Minning And Agriculture, Oil And Gas, and Transportation.

On the basis of Geography, the Cloud Computing in Industrial IOT Market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas region is studied across Argentina, Brazil, Canada, Mexico, and United States. The Asia-Pacific region is studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, South Korea, and Thailand. The Europe, Middle East & Africa region is studied across France, Germany, Italy, Netherlands, Qatar, Russia, Saudi Arabia, South Africa, Spain, United Arab Emirates, and United Kingdom.

Company Usability Profiles:The report deeply explores the recent significant developments by the leading vendors and innovation profiles in the Global Cloud Computing in Industrial IOT Market including Amazon Web Services, Inc., Cisco, Fujitsu, Honeywell International Inc., Ibm, Intel Corporation, Iron Mountain Incorporated, Irootech, LosantIOT, Inc., and Microsoft Corporation.

FPNV Positioning Matrix:The FPNV Positioning Matrix evaluates and categorizes the vendors in the Cloud Computing in Industrial IOT Market on the basis of Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) that aids businesses in better decision making and understanding the competitive landscape.

Competitive Strategic Window:The Competitive Strategic Window analyses the competitive landscape in terms of markets, applications, and geographies. The Competitive Strategic Window helps the vendor define an alignment or fit between their capabilities and opportunities for future growth prospects. During a forecast period, it defines the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth.

Cumulative Impact of COVID-19:COVID-19 is an incomparable global public health emergency that has affected almost every industry, so for and, the long-term effects projected to impact the industry growth during the forecast period. Our ongoing research amplifies our research framework to ensure the inclusion of underlaying COVID-19 issues and potential paths forward. The report is delivering insights on COVID-19 considering the changes in consumer behavior and demand, purchasing patterns, re-routing of the supply chain, dynamics of current market forces, and the significant interventions of governments. The updated study provides insights, analysis, estimations, and forecast, considering the COVID-19 impact on the market.

The report provides insights on the following pointers:1. Market Penetration: Provides comprehensive information on sulfuric acid offered by the key players2. Market Development: Provides in-depth information about lucrative emerging markets and analyzes the markets3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, and manufacturing capabilities of the leading players5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and new product developments

The report answers questions such as:1. What is the market size and forecast of the Global Cloud Computing in Industrial IOT Market?2. What are the inhibiting factors and impact of COVID-19 shaping the Global Cloud Computing in Industrial IOT Market during the forecast period?3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Cloud Computing in Industrial IOT Market?4. What is the competitive strategic window for opportunities in the Global Cloud Computing in Industrial IOT Market?5. What are the technology trends and regulatory frameworks in the Global Cloud Computing in Industrial IOT Market?6. What are the modes and strategic moves considered suitable for entering the Global Cloud Computing in Industrial IOT Market?Read the full report: https://www.reportlinker.com/p05913858/?utm_source=GNW

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The Global Cloud Computing in Industrial IOT Market is expected to grow from USD 3,966.66 Million in 2019 to USD 7,078.35 Million by the end of 2025...

Here’s Why Several Cloud Computing Stocks Surged in May – The Motley Fool

What happened

Many cloud computing companies saw their share prices rise in May, according to data from S&P Global Market Intelligence. I'm going to focus on non-SQL database veteran MongoDB (NASDAQ:MDB), infrastructure-as-a-service expert Nutanix (NASDAQ:NTNX), and software management specialist New Relic (NYSE:NEWR). Here's how these stocks performed last month:

^SPX data by YCharts.

For the most part, these gains were part of a larger rebound from the depth of the COVID-19 shutdown in March. The S&P 500has climbed 34% since March 18, and my three tickers simply amplified that gain. New Relic is up by 90% over this period, MongoDB gained 94%, and Nutanix posted a 98% return.

New Relic accelerated its upward trajectory with a solid fourth-quarter report on May 14. The company beat Wall Street's estimates across the board but also issued slightly pessimistic next-quarter guidance. Many of New Relic's customers fall into the small-business sector, and some of them are having trouble paying their bills at the moment. The company is also knee-deep in closing down its physical data centers and moving into public cloud services instead, which will weigh on profit margins for the next couple of quarters. That being said, management said that these issues should be short-lived and the long-term growth opportunity in 2021 and beyond remains exciting.

Image source: Getty Images.

MongoDB didn't have much news to share in May, but investors and analysts expected an impressive showing in early June's first-quarter report. The company absolutely demolished Wall Street's official expectations, but MongoDB's stock still fell more than 7% the next day. The pre-earnings market momentum turned out to be just a little bit too strong, so some MongoDB investors felt that it was time to take some profits off the table.

As for Nutanix, the cloud-based infrastructure specialist also crushed analysts' estimates in a late-May third-quarter report. The road to that impressive financial report was somewhat bumpy, including a couple of significant drops along the way as management withdrew its full-year guidance and furloughed 1,465 workers in the San Francisco area. It expects that the cost-saving habits the company is acquiring during the coronavirus crisis will stick around for years to come, herding Nutanix toward more efficient and more profitable operations.

I'm talking about three well-managed companies here, all in the red-hot cloud computing sector, where strong revenue growth should be easy to find for years to come. All of them are trading double-digit percentages below their 52-week highs, which counts as a serious discount in the high-growth corner of Wall Street. Importantly, I believe that all three should be able to shrug off a second wave of COVID-19 infections if it turns out that states started reopening a bit too early.

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Here's Why Several Cloud Computing Stocks Surged in May - The Motley Fool

Healthcare Cloud Computing Market Outlook, Strategies, Manufacturers, Countries, Type and Application, Global Forecast To 2025 – 3rd Watch News

Market Study Report, LLC, has added an exhaustive research study of the Healthcare Cloud Computing market, detailing every single market driver and intricately analyzing the business vertical. This Healthcare Cloud Computing market study will aid in seeking out new business opportunities and fine-tuning existing marketing strategies through insights regarding SWOT analysis, market valuation, competitive spectrum, regional share, and revenue predictions.

The latest report on the Healthcare Cloud Computing market is an all-inclusive assessment of the business sphere and highlights the vital parameters of the industry including current trends, industry size, market share, present renumeration, periodic deliverables, and profit estimates over the forecast timeline.

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The report provides a comprehensive evaluation of the Healthcare Cloud Computing market performance during the study period. Insights pertaining to drivers that affect the market dynamics, as well as the growth pattern over the predicted timeframe are documented in the report. It further elaborates the challenges of the market and define the growth prospects in the forthcoming years.

Key pointers of the Healthcare Cloud Computing market report:

Unveiling the geographical landscape of the Healthcare Cloud Computing market:

Healthcare Cloud Computing Market bifurcation:

Summary of the regional landscape examined in the report:

An exhaustive review of the Healthcare Cloud Computing market with respect to product type and application scope:

Product scope:

Product types: Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS

Key highlights of the report:

Applications scope:

Application segmentation: Hospital, Clinics and Others

Vital data entailed in the report:

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Other takeaways from the Healthcare Cloud Computing market report:

Elucidating details regarding the competitive terrain of the Healthcare Cloud Computing market:

Major players of the industry: MicroSoft, Dell, IBM, Amazon Web Services, GE healthcare, Oracle, Agfa-Gevaert, Carestream Health, Google Cloud Platform, Alibaba Cloud and Athenahealth

Key parameters included in the report:

For More Details On this Report: https://www.marketstudyreport.com/reports/global-healthcare-cloud-computing-market-growth-status-and-outlook-2020-2025

Some of the Major Highlights of TOC covers:

Development Trend of Analysis of Healthcare Cloud Computing Market

Marketing Channel

Market Dynamics

Methodology/Research Approach

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Healthcare Cloud Computing Market Outlook, Strategies, Manufacturers, Countries, Type and Application, Global Forecast To 2025 - 3rd Watch News

Honeywell, SAP are teaming in the cloud to remake commercial real estate in the age of COVID-19 – MarketWatch

As the country slowly reopens, life for Americans will take on myriad wrinkles perhaps none more so than through corporate real estate.

Safety issues in a COVID-19 world will require significant changes at offices, hospitals, hotels and other venues via up-to-the-minute data.

Two significant cloud-computing companies are working to make it happen. Honeywell International Inc. HON, +0.74% and SAP SAP, +0.49% on Thursday announced they are teaming on a joint cloud-based solution combining technologies to streamline business operations based on data, starting with commercial real estate.

Returning to work offers a tantalizing challenge, as millions of people will need to navigate elevators, bathrooms, kitchens and desk space. Office managers, in turn, are poring over data from different sources to drive cost-reduction and elimination of waste in terms of energy consumption and other resources, Que Dallara, chief executive of Honeywell Connected Enterprise, told MarketWatch in a phone interview Tuesday.

For example, one potential customer, Transwestern the nations largest privately held real-estate company owns and manages office buildings through 34 offices in the U.S. Its task is onerous: As some employees return to offices it oversees in Denver, Phoenix, Atlanta and Houston, it must calculate changes in cleaning, lighting, temperature, air circulation and social distancing.

There is definitely a giant bucket of things to consider, Kevin Boltz, national director of engineering, asset services, at Transwestern, told MarketWatch. Plus, we must manage data from sources such as local and state health officials and the [World Health Organization], as well as consider so much technology on the market.

See also: Honeywells latest pivot is into quantum computing

Ultimately, it decided on a cloud-based system, which is where Honeywell-SAP come in, according to Boltz. It affords additional flexibility in security, building automation and energy efficiency.

Analysts briefed on the Honeywell-SAP partnership believe it could establish a new baseline as building owners and tenants grapple with a whole new dynamic.

I think it is especially important in the current environment that tenants and real-estate owners together have confidence in the quality of the experience in their offices, and through this partnership they can now be more confident in what that experience is, Scott Morey of One11 Advisors told MarketWatch in an email Wednesday.

Honeywells partnership with SAP is part of a dramatic pivot to an industrial-software company that has drawn comparisons to the business models of Salesforce.com Inc. CRM, +1.77% and SAP, while bolstering Honeywells bottom line and stock price.

As its hundreds of customers migrate to the Industrial Internet of Things, or IIoT, to connect everything to the internet, Honeywell is accelerating its software efforts to capture a slice of the multibillion-dollar market. Its software is used to enhance output, cut maintenance costs and improve reliability.

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Honeywell, SAP are teaming in the cloud to remake commercial real estate in the age of COVID-19 - MarketWatch

Healthcare Cloud Computing Market Overview, Major Manufacturers and Production Price, Cost Revenue, Healthcare Cloud Computing Market Forecast 2025 -…

The research report on Healthcare Cloud Computing market provides with a granular evaluation of the business space and contains information regarding the market tendencies such as the prevailing remuneration, revenue estimations, market valuation and market size during the estimated timeframe.

An overview of the performance assessment of the Healthcare Cloud Computing market is mentioned in the report. The document also comprises of insights pertaining to the major market trends and its predicted growth rate. Additional details such as growth avenues as well as hindering factors for this industry landscape are enlisted.

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COVID-19, the disease it causes, surfaced in late 2019, and now had become a full-blown crisis worldwide. Over fifty key countries had declared a national emergency to combat coronavirus. With cases spreading, and the epicentre of the outbreak shifting to Europe, North America, India and Latin America, life in these regions has been upended the way it had been in Asia earlier in the developing crisis. As the coronavirus pandemic has worsened, the entertainment industry has been upended along with most every other facet of life. As experts work toward a better understanding, the world shudders in fear of the unknown, a worry that has rocked global financial markets, leading to daily volatility in the U.S. stock markets.

Request Sample Copy of this Report @ https://www.cuereport.com/request-sample/449

Pivotal details highlighted in the Healthcare Cloud Computing market report:

In terms of regional frame of reference of the Healthcare Cloud Computing market:

Healthcare Cloud Computing Market Segmentation: Americas, APAC, Europe, Middle East & Africa

A summary of the information enlisted in the Healthcare Cloud Computing market report:

A gist of the Healthcare Cloud Computing market based on the product landscape and application spectrum:

Product landscape:

Product types:

Major aspects included in the report:

Application Landscape:

Application segmentation:

Details mentioned in report:

Additional information offered in the report:

Other details regarding the competitive spectrum of the Healthcare Cloud Computing market:

Vendor base of Healthcare Cloud Computing market:

Major aspects as per the report:

Research objectives:

The report answers important questions that companies may have when operating in the global Healthcare Cloud Computing market. Some of the questions are given below:

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Healthcare Cloud Computing Market Overview, Major Manufacturers and Production Price, Cost Revenue, Healthcare Cloud Computing Market Forecast 2025 -...

Cloud Computing Market Growth Trends, Key Players, Competitive Strategies and Forecasts to 2026 – Jewish Life News

Cloud Computing Market Overview

The Cloud Computing market report presents a detailed evaluation of the market. The report focuses on providing a holistic overview with a forecast period of the report extending from 2018 to 2026. The Cloud Computing market report includes analysis in terms of both quantitative and qualitative data, taking into factors such as Product pricing, Product penetration, Country GDP, movement of parent market & child markets, End application industries, etc. The report is defined by bifurcating various parts of the market into segments which provide an understanding of different aspects of the market.

The overall report is divided into the following primary sections: segments, market outlook, competitive landscape and company profiles. The segments cover various aspects of the market, from the trends that are affecting the market to major market players, in turn providing a well-rounded assessment of the market. In terms of the market outlook section, the report provides a study of the major market dynamics that are playing a substantial role in the market. The market outlook section is further categorized into sections; drivers, restraints, opportunities and challenges. The drivers and restraints cover the internal factors of the market whereas opportunities and challenges are the external factors that are affecting the market. The market outlook section also comprises Porters Five Forces analysis (which explains buyers bargaining power, suppliers bargaining power, threat of new entrants, threat of substitutes, and degree of competition in the Cloud Computing) in addition to the market dynamics.

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Leading Cloud Computing manufacturers/companies operating at both regional and global levels:

Cloud Computing Market Scope Of The Report

This report offers past, present as well as future analysis and estimates for the Cloud Computing market. The market estimates that are provided in the report are calculated through an exhaustive research methodology. The research methodology that is adopted involves multiple channels of research, chiefly primary interviews, secondary research and subject matter expert advice. The market estimates are calculated on the basis of the degree of impact of the current market dynamics along with various economic, social and political factors on the Cloud Computing market. Both positive as well as negative changes to the market are taken into consideration for the market estimates.

Cloud Computing Market Competitive Landscape & Company Profiles

The competitive landscape and company profile chapters of the market report are dedicated to the major players in the Cloud Computing market. An evaluation of these market players through their product benchmarking, key developments and financial statements sheds a light into the overall market evaluation. The company profile section also includes a SWOT analysis (top three companies) of these players. In addition, the companies that are provided in this section can be customized according to the clients requirements.

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Cloud Computing Market Research Methodology

The research methodology adopted for the analysis of the market involves the consolidation of various research considerations such as subject matter expert advice, primary and secondary research. Primary research involves the extraction of information through various aspects such as numerous telephonic interviews, industry experts, questionnaires and in some cases face-to-face interactions. Primary interviews are usually carried out on a continuous basis with industry experts in order to acquire a topical understanding of the market as well as to be able to substantiate the existing analysis of the data.

Subject matter expertise involves the validation of the key research findings that were attained from primary and secondary research. The subject matter experts that are consulted have extensive experience in the market research industry and the specific requirements of the clients are reviewed by the experts to check for completion of the market study. Secondary research used for the Cloud Computing market report includes sources such as press releases, company annual reports, and research papers that are related to the industry. Other sources can include government websites, industry magazines and associations for gathering more meticulous data. These multiple channels of research help to find as well as substantiate research findings.

Table of Content

1 Introduction of Cloud Computing Market

1.1 Overview of the Market1.2 Scope of Report1.3 Assumptions

2 Executive Summary

3 Research Methodology of Verified Market Research

3.1 Data Mining3.2 Validation3.3 Primary Interviews3.4 List of Data Sources

4 Cloud Computing Market Outlook

4.1 Overview4.2 Market Dynamics4.2.1 Drivers4.2.2 Restraints4.2.3 Opportunities4.3 Porters Five Force Model4.4 Value Chain Analysis

5 Cloud Computing Market, By Deployment Model

5.1 Overview

6 Cloud Computing Market, By Solution

6.1 Overview

7 Cloud Computing Market, By Vertical

7.1 Overview

8 Cloud Computing Market, By Geography

8.1 Overview8.2 North America8.2.1 U.S.8.2.2 Canada8.2.3 Mexico8.3 Europe8.3.1 Germany8.3.2 U.K.8.3.3 France8.3.4 Rest of Europe8.4 Asia Pacific8.4.1 China8.4.2 Japan8.4.3 India8.4.4 Rest of Asia Pacific8.5 Rest of the World8.5.1 Latin America8.5.2 Middle East

9 Cloud Computing Market Competitive Landscape

9.1 Overview9.2 Company Market Ranking9.3 Key Development Strategies

10 Company Profiles

10.1.1 Overview10.1.2 Financial Performance10.1.3 Product Outlook10.1.4 Key Developments

11 Appendix

11.1 Related Research

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Verified Market Research is a leading Global Research and Consulting firm servicing over 5000+ customers. Verified Market Research provides advanced analytical research solutions while offering information enriched research studies. We offer insight into strategic and growth analyses, Data necessary to achieve corporate goals and critical revenue decisions.

Our 250 Analysts and SMEs offer a high level of expertise in data collection and governance use industrial techniques to collect and analyse data on more than 15,000 high impact and niche markets. Our analysts are trained to combine modern data collection techniques, superior research methodology, expertise and years of collective experience to produce informative and accurate research.

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Cloud Computing Market Growth Trends, Key Players, Competitive Strategies and Forecasts to 2026 - Jewish Life News

2 ASX shares to buy to benefit from the cloud computing boom – Motley Fool Australia

One investment theme that I think could be well worth gaining exposure to is cloud computing.

Cloud computing is the on-demand availability of computer system resources such as data storage and computing power without direct active management by the user.

One investment theme that I think could be well worth gaining exposure to is cloud computing.

Cloud computing is the on-demand availability of computer system resources such as data storage and computing power without direct active management by the user.

It is because of the cloud that you can watch Netflix on demand wherever you are, do your accounting on the go, and have Zoom meetings with colleagues.

And as you might have noticed, particularly during the pandemic, more and more software and services are going to the cloud.

This shift to the cloud is expected to accelerate in the coming years. So much so, research by Statista shows that the size of the public cloud computing services market is expected to grow from US$227.8 billion in 2019 to US$354.6 billion by 2022. This is an increase of almost 56% in just three years and is unlikely to stop there.

The good news for Australian investors is that there are a couple of quality shares which have direct exposure to the cloud.

I believe this bodes well for their future growth and could make them great long term investments. Heres why I like them:

The first ASX share you can buy to gain exposure to the cloud computing boom is Megaport. It offers scalable bandwidth for public and private cloud connections, metro ethernet, and data centre backhaul. As of the end of March, Megaport was serving 1,777 customers out of 329 data centres globally. Both its footprint and customer numbers have been growing at a rapid rate over the last couple of years and look likely to continue thanks to the growing cloud usage.

Another way to gain exposure to cloud computing is through NEXTDC. It is one of the worlds most innovative data centre operators with a total of 9 centres across 5 capital cities. Its customers are supported by more than 550 partners that form its highly skilled and network-rich partner ecosystem. The company believes this makes it Australias only truly channel centric data centre solutions provider, offering complete service neutrality. Demand for capacity within its centres has been growing at a rapid rate over the last few years. I expect this trend to continue and drive strong earnings growth as it scales.

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James Mickleboro owns shares of NEXTDC Limited. The Motley Fool Australia's parent company Motley Fool Holdings Inc. owns shares of MEGAPORT FPO. The Motley Fool Australia has recommended MEGAPORT FPO. We Fools may not all hold the same opinions, but we all believe that considering a diverse range of insights makes us better investors. The Motley Fool has a disclosure policy. This article contains general investment advice only (under AFSL 400691). Authorised by Scott Phillips.

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2 ASX shares to buy to benefit from the cloud computing boom - Motley Fool Australia

Lockdown has brought in new ways of working. They are here to stay – Diginomica

( Chansom Pantip - shutterstock)

Although there are moments in history "where decades happen" as Lenin once wrote, most of the time change is something that creeps up on society. To paraphrase Bill Gates (and others), we're often disappointed how little seems to have changed after a year, yet underestimate how much the world will have changed after ten years. All the change that's happening now during the COVID-19 lockdown may start to feel overdone next year as everyone attempts to get back to normal. Ten years later, it will have crept back up on us and the world will feel very different.

Why does disruptive change take so long? It's because society has to adapt not just people and our habits, but also the organizations around us and the underlying infrastructure on which everything runs. I was recently reminded of this phenomenon when recalling the early years of the SaaS industry in a podcast interview. It's easy to forget how much needed to be put in place to enable everything we take for granted in cloud computing today. The early pioneers had to doggedly stick to their trajectory in the face of an incumbent tech industry that believed the cloud was just a passing fad.

Expect to hear similar in the next year or two as lockdown starts to lift and people gradually return to old, if somewhat modified, patterns of office-based work, city-center shopping and mass entertainment. Companies that in recent weeks have made a long-term commitment to remote working, such as Twitter, Facebook and Shopify, will face criticism for having acted in haste. A small minority may even abandon their plans. But that won't reverse the long-term trend towards digitally connected working and a redistribution of economic activity away from city centers.

The lessons of SaaS and cloud computing are that change on this scale requires time to evolve the technology (containers, APIs and smartphones), build out the infrastructure (broadband, networking and datacenters) and learn new ways of working (DevOps, distributed teamwork and the gig economy). It took up to twenty years to lay down all of these necessary foundations and bring cloud computing as we now know it and the digital economy that it powers to maturity.

Even now, it has taken the advent of COVID-19 to demonstrate the advantages all of this brings many businesses that had already embraced cloud computing and digital working were able to take the lockdown in their stride. Those who had not yet completed the shift away from on-premise computing were left scrambling to ramp up VPN access, source laptops, and navigate the unfamiliar etiquette of distributed teamwork. And that was just to get back in operation.

The point here is that, while cloud computing has evolved and become mainstream, business cultures, organization and working practices have barely begun to adapt to what the technology now allows. The COVID-19 lockdown has given us all a jolt in the right direction, but we are still at the very beginning of this new wave of change. Suddenly it's become clear that embracing distributed working practices founded on cloud computing makes businesses far more agile and resilient than those still stuck in the old ways. But it still feels hard to adapt to these new ways of working, because many of the necessary tools and skills are unfamiliar. It will still take time for everyone to fully grasp what's really involved.

The businesses that have already adapted are therefore like those early pioneers of SaaS twenty years ago who understood the importance of being truly cloud-native, while the majority are still imagining that the way they've always done things just needs a few small tweaks. Remember that although the first SaaS vendors got started in 1998, it was not until after the 2008 financial crisis that SaaS and cloud computing began to be accepted into the mainstream. Today's COVID-19 crisis is the beginning of a similar decade-long journey to round out the technology, infrastructure and organizational culture needed to support truly effective connected digital working.

That new world will look very different than we're used to and it's likely to keep on evolving, for decades to come. My hunch is that putting in the tools and the culture to fully support digitally connected working will in turn lead to a rethinking of how organizations recruit and marshall their workforces. That will reverse the long-term trend towards agglomeration in cities, prompting a reconfiguration of most enterprises to operate across many more distributed and far smaller locations.

This will be true even for industries such as manufacturing that for almost two centuries have sought to concentrate their operations for reasons of scale. In this new world, the cost efficiencies of scale have to be balanced against the advantages of agility and resilience. Businesses are already starting to reconfigure their supply chains to include more alternative sources, preferably onshore.

In the early stages of taking these steps, the new way of operating is more costly than the established processes. But as time goes on the processes improve and they begin to yield unexpected new advantages that had not been obvious at the beginning. In the case of SaaS, one of the most important advantages was the continuous digital connection to customers.

As digital technology proliferates, every industry is now feeling the impact of this XaaS effect, in which connected digital operations producehighly adaptive output that responds to customer needs. We are already seeing digital technology in manufacturing that allows more flexibility to customize products or to switch production faster. These trends are just getting started.

While many of these changes will become established by the end of the coming decade, some will take much longer to ripple through society. Changing bricks-and-mortar investments, such as where people live and congregate and where businesses locate their operations, is a huge shift that can't happen overnight.

For now, the pioneers will have to dig their heels in and persevere. Look back at the past decade of cloud computing to see how much can change. Just ten years ago, most people still regarded Salesforce CEO Marc Benioff as a maverick with all his talk of 'false cloud'. Workday was still struggling to persuade Fortune 500 customers to sign up. Most enterprises refused to put production workloads on AWS, saving it for dev and test. G-Suite had few enterprise customers to showcase, while Microsoft was still three years away from offering full-function Office apps in the cloud. A decade later, these companies are now mainstream providers of cloud computing to the enterprise.

Now it falls to a new generation of stubborn innovators to trust their instincts and stand their ground against a conventional wisdom that believes the rise of distributed teamwork is just a Coronavirus-induced blip. As I observed during that recent podcast about the history of SaaS:

The establishment always believes that what they're doing is the right way to do it, and are always dismissive of new things coming along. If you're doing a new thing which is actually going to end up being better then you just have to stick to it. Because it's going to be really tough for the first 10, 15, 20 years, until eventually the whole world comes around to your point of view.

I was reminded of this when reading Slack CEO Stewart Butterfield's wide-ranging interview with The Verge a few weeks ago. In the midst of a passage discussing the competition Slack is seeing from Microsoft Teams and the history of newcomers competing with established vendors, he makes this point:

The lesson of that is the small, focused startup that has real traction with customers sometimes has an advantage versus the large incumbent that has multiple lines of business.

There is a new generation of innovative entrepreneurs that recognizes how different the future of work is going to be while the incumbent giants remain wedded to the old ways of working. The history of SaaS tells us that not all of these emerging companies and their evangelist CEOs will still be in the race in ten years' time. But we must listen carefully to what they have to say, because today they are the ones that have their fingers on the pulse of how the world is changing.

Continued here:

Lockdown has brought in new ways of working. They are here to stay - Diginomica

Commerce Cloud Computing Market :Demand, Industry Size, Share, Types, Trends, Top-Manufacturers (Unilever, LOreal) Consumption, Application,…

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Based on application, the market has been segmented into:

NA

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Commerce Cloud Computing Market :Demand, Industry Size, Share, Types, Trends, Top-Manufacturers (Unilever, LOreal) Consumption, Application,...

Global Cloud Computing Services Market Expected to reach highest CAGR by 2025: Amazon Web Services (AWS), Microsoft, IBM, Aliyun, Google Cloud…

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This study covers following key players:Amazon Web Services (AWS)MicrosoftIBMAliyunGoogle Cloud PlatformSalesforceRackspaceSAPOracleVmwareDELLEMC

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Market segment by Type, the product can be split into Software as a Service (SaaS)Platform as a Service (PaaS)Infrastructure as a Service (IaaS)Everything as a Service (XaaS)

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Some Major TOC Points:1 Report Overview2 Global Growth Trends3 Market Share by Key Players4 Breakdown Data by Type and ApplicationContinued

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Global Cloud Computing Services Market Expected to reach highest CAGR by 2025: Amazon Web Services (AWS), Microsoft, IBM, Aliyun, Google Cloud...

Get your head in the clouds: The key benefits of cloud services to your small business – Stuff.co.nz

OPINION: Cloud computing is not just the future it has already well and truly become the business standard. And those who have yet to adopt the technology are facing the consequences now more than ever.

Organisations that have taken advantage of the technology are seeing an incredible payoff during the Covid-19 pandemic crisis, maintaining business continuity and resilience while their entire workforce seamlessly works from home. For the less fortunate, theyve been caught off guard as they lack the infrastructure and capabilities to keep their business running effectively.

Cloud computing enables on-demand delivery of computer services over the internet, typically managed by a third-party provider. This could be services from basic storage, networking, processing power or office applications. This is a shift from having onsite infrastructure which is managed and maintained by the business itself.

POOL VISION

Prime Minister Jacinda Ardern has made a habit of praising Kiwi ingenuity in her press conferences.

Businesses yet to make the jump likely have understandable worries. How much will it cost? Will my data be safe? Why change if my current system is working fine? Cloud services have come a long way, and with the right approach, secure and cost effective.

READ MORE:* Could a JobStart scheme for small businesses help tackle unemployment?* Why it might be time to upgrade that temporary home office setup * Answers to common questions about the Small Business Cashflow Loan Scheme* Amazon needs to take on Xbox and PlayStation gaming console dominance

The pandemic has proven the risk of being complacent with your technology. So, what are the benefits of making your business cloud-based?

SECURE AND SAFE DATA

From Amazon to Google to Microsoft, these providers have invested considerably into the security and reliability of their systems. Many cloud providers offer advanced security features such as multi-factor authentication, encryption, and access control. A security flaw or hack on their system would be a devastating to these brands, meaning that you can rely on their constant vigilance.

If youre not comfortable with, or legally cannot store your data offshore, there are providers are offering cloud storage hosted locally. Microsoft is already underway developing their own New Zealand data centres to satisfy this requirement. Cloud storage also provides the ability to access your business data anywhere. If your on-premise local storage becomes inaccessible, then so does your data. And it doesnt matter how secure your data is if youre unable to use it.

WORK ANYWHERE

It couldnt be more obvious than now, but there is a strong business case for giving your workforce the capability to work from anywhere. And it goes beyond weathering the pandemic crisis. Global trends have been moving towards organisations offering more flexible working arrangements. For business wishing to attract the very best talent, providing a working from home option can be a strong selling point. Flexible working has also shown that it can increase job satisfaction and improve productivity. Additionally, having a cloud-based system can enable you to seamlessly bring external contributors into your work environment regardless of whether they are in New Zealand or overseas.

SCALABILITY

Using cloud services gives your business the full capability to scale your infrastructure to the needs of the moment. This solution is quicker and normally more cost effective than the upfront purchasing of onsite technology that needs to be maintained, managed, and upgraded by your business. Cloud providers have the benefit of economies of scale and can offer a range of services catered to your own business' requirements. The result enables rapid deployment and gains more cost efficiency for your organisation. Additionally, your business can seize opportunities quickly knowing full well they upscale of their technology capabilities almost instantly. Alternatively, you can save costs by decreasing capabilities if you no longer require them.

One report Ive read suggests that 94 per cent of enterprises are taking advantage of the cloud already, so if you havent, its time to get join. As Covid-19 has shown, it is critical for maintaining business continuity.

When approaching implementing cloud services in your business, I recommend researching what type of service is the best fit for your business.

This article has mostly discussed the public cloud services and infrastructure shared by all of a providers customers. But there are also private cloud services, which is essentially infrastructure dedicated to your organisation, and are useful when you have bespoke workloads, or special security requirements. Some businesses incorporate a mix of public and private called hybrid cloud, which if designed correctly, can give you benefits from each infrastructure class.

Once youve understood what cloud models to adopt, your next step is to select which services you want to migrate to the cloud next. What we typically see prioritised is the following: Email, file storage, office applications, business collaboration, accounting, and CRM/ERP. What is most often missed is the most important identity management and security.

As for specific applications to that can best take advantage of cloud services, I would recommend:

Office 365: This contains the top three items on the list above, and with the proper expertise is also identity management and security

Microsoft Teams: Part of the Office 365 suite this service offers a flexible and intuitive collaboration tools that can boost your teams communication and productivity. Teams can also be extended to become your business telephone system.

LastPass: Security is paramount, and a rigorous security policy must password conventions. All passwords need to be random and unique, and LastPass will keep a vault of these.

Geof Robinson is the chief technology officer at Telesmart

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Get your head in the clouds: The key benefits of cloud services to your small business - Stuff.co.nz

An FAQ on cloud APIs and application development – TechTarget

APIs are a common way for software developers to interface with services, without worrying about the inner workings of that service or the service provider.

While cloud users can employ consoles and portals to provision and control cloud resources, the public cloud is also a natural fit for APIs. Application developers use APIs to access cloud services through web-based communication. A developer writes code that makes a call to the cloud provider's API, passes the requisite parameters and arguments in the context of the call, and then examines the response to confirm the operation. Let's take a closer look at the purpose and use of APIs in cloud computing.

A cloud API enables end users to access a cloud provider's application or service, such as compute infrastructure, storage resources or monitoring tools. APIs define the possible features and functions of that app or service, along with the details needed to execute them. APIs are typically based on REST or Simple Object Access Protocol communication schemes and rely on authorization schemes such as OAuth 2.0 to ensure user authentication and security.

Think of an API as a menu for a restaurant. A menu, or an API, is an interface you use to decide what to order. To order, you don't need extensive insight into how the restaurant, or service provider, operates behind the scenes.

Public clouds are founded on the notion of self-service and automation, so APIs are critical to how they operate. In fact, AWS, Microsoft Azure, Google Cloud Platform and other cloud platforms use APIs to drive all of their user-facing operations, such as when developers create new software or when they use the console. Let's consider how this works with AWS as an example.

AWS provides a broad range of APIs that can drive any provisioning or operation. For example, the Amazon EC2 API supports services that include Amazon EC2 instances, Amazon Elastic Block Store, Amazon Virtual Private Cloud and AWS VPN. The Amazon S3 REST API supports Amazon S3.

Suppose a software developer wants to use AWS to create up to three EC2 instances using an Amazon machine image called ami-60a54010. The developer also wants to locate those instances in an Availability Zone in the US East-1 Region, and enable monitoring of those provisioned compute instances. The EC2 API command might appear as:

https://ec2.amazonaws.com/?Action=RunInstances&ImageId=ami-60a54010&MaxCount=3&MinCount=1&Placement.AvailabilityZone=us-east-1b&Monitoring.Enabled=true&AUTHPARAMS

As shown above, the fundamental API command is RunInstances, while parameters include ImageId, MaxCount, MinCount, Placement.AvailabilityZone and Monitoring.Enabled. The details for each parameter are the arguments of the parameters. There can be hundreds of API commands. The Amazon EC2 API reference manual alone consists of hundreds of pages of documentation.

Developers can build powerful applications faster than ever with APIs. For service providers, the API maintains their control and security of the data. Providers can also track API usage, which makes it a valuable and growing source of revenue. Every time a developer uses a provider's API, chances are they're paying something for that call -- or per-thousand calls or whatever the case may be.

For example, software designed to process and render geographical data might employ a cloud service such as Google Maps to provide visual mapping and location capabilities. This alleviates the need for a business to create its own maps and mapping algorithms, but it isn't necessarily free either. Other major platforms such as Facebook, Twitter, Netflix and countless other providers have APIs that allow outside developers to access services and data.

The single, overarching issue APIs address is connection. APIs connect software across a network. When a business creates an application or a service, an API can be created and deployed to allow other software to interface with that software or service.

APIs are typically designed and implemented when a service is used by multiple applications and many users want to access the same service. This is ideal for the public cloud, where countless users might access a service such as AWS Lambda or transfer data to a storage service.

APIs are also well-suited for applications that are implemented as multiple distributed components. The application components call upon each other's API(s). In this way, the components can be updated and scaled independently and located in distributed locations for greater performance and availability. One example of this is container-based microservices applications that rely on APIs for container-to-container communication.

Different applications within a business can share the same API. For example, several database deployments may use the same API for database access. However, APIs are typically unique and purpose-built software that is rarely standardized between businesses and developers. The API developed by one business to support one application will almost certainly not work for another application developed by another business. This approach underlies many of the issues around cloud provider APIs, vendor lock-in and cloud API standardization.

There are several ways to categorize APIs. One popular way is to distinguish between vendor-specific APIs and cross-platform APIs. A vendor-specific cloud API is intended to support the services of a particular cloud provider. For example, the Microsoft Azure REST API is dedicated to the many services offered by the Azure public cloud, such as Azure DevOps, Cosmos DB and Visual Studio. A vendor-specific cloud API can be developed to address every nuance and feature of that platform. However, it will only work with that provider, and you'll need a different API to work with other providers.

By comparison, a cross-platform API is intended to provide identical functionality between two or more cloud providers. Examples of cross-platform APIs include Simple Cloud, part of the Zend Technologies, Apache's jclouds, and Apache's Libcloud. Developers can employ the same commands and parameters to perform the same tasks regardless of the actual cloud provider. However, this often leads to limited functionality and control, which is why vendor-specific APIs remain the most popular type of API for developers.

Cloud APIs can also be categorized by type, such as infrastructure, platform and software. IaaS APIs are typically focused on provisioning compute and storage resources. PaaS APIs are generally dedicated to providing back-end services or architectures such as databases. And SaaS, or application, APIs are intended to provide connectivity or interoperability with a software product or suite, such as Microsoft Office 365.

Application portability is a central concept of modern cloud computing and a solution to vendor lock-in. Cloud users may want to relocate data to another provider's services if they have better capabilities or lower prices. For example, a business may opt to move a data set to another cloud if it offers better machine learning and AI services.

APIs handle the actual dynamics of executing the migration. APIs create and secure a target storage resource in a desired cloud region and then implement the copy process. Such processes can typically be performed programmatically through a script. The actions executed by such a program would invariably interface with the source and destination cloud providers through their respective APIs, because everything in the public cloud happens through APIs anyway.

But there are cloud services intended to accelerate cloud data migration, such as the AWS Transfer Family or Google's Transfer Service for cloud data. Such services can simplify the migration process, though the services will still employ cloud provider APIs.

Ultimately, data migrations require the use of APIs and involve a clear business strategy and significant planning to understand the business tradeoffs, performance impacts, and cloud data movement and storage costs involved with any cloud data migration.

Standards are attractive because any product or service that adheres to them will behave in a known, well-understood manner. Cloud standards are central to the ideas of cloud interoperability and portability. Thus, cloud API standards make it easier for organizations to use multiple clouds.

However, standards are often more of a negotiation than a technical hurtle. As with any service, it's the differentiators -- the features and capabilities only available with a certain provider -- that make a public cloud service stand out. If every provider offered the same set of services in the same way, competitive differentiators would be lost. Similarly, standardization demands some sharing of intellectual property, which would be a bitter pill for providers to swallow, given the investments they've made in their platforms.

Progress toward any common cloud APIs has been incredibly slow because the public cloud market is owned by three principal providers -- AWS, Microsoft and Google. Standardization is only economically attractive when there are many competing providers and the industry would suffer or adoption would falter without it. This isn't really the case in today's public cloud market.

There are some standards initiatives evolving quietly, such as the cross-platform cloud APIs noted earlier. However, cloud providers are more likely to adopt industry standards that drive greater usage or make it easier to deploy applications on their platforms. For example, adopting a prevalent technology standard such as Open Virtualization Format (OVF) makes it easier for cloud users to create machine images that are suitable for rapid, scalable cloud deployment. For example, the machine image file name used as the argument to an API parameter would usually be an .ovf file, though other common formats can also be supported.

In other cases, cloud APIs will seek to support critical behaviors such as security and authentication standards, including HIPAA, Payment Card Industry Data Security Standard, Federal Risk and Authorization Management Program and many others. Organizations that operate in those industries will be better able to adopt a public cloud infrastructure if those platforms adhere to regulatory standards.

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An FAQ on cloud APIs and application development - TechTarget

The cost of training machines is becoming a problem – The Economist

Jun 11th 2020

THE FUNDAMENTAL assumption of the computing industry is that number-crunching gets cheaper all the time. Moores law, the industrys master metronome, predicts that the number of components that can be squeezed onto a microchip of a given sizeand thus, loosely, the amount of computational power available at a given costdoubles every two years.

For many comparatively simple AI applications, that means that the cost of training a computer is falling, says Christopher Manning, the director of Stanford Universitys AI Lab. But that is not true everywhere. A combination of ballooning complexity and competition means costs at the cutting edge are rising sharply.

Dr Manning gives the example of BERT, an AI language model built by Google in 2018 and used in the firms search engine. It had more than 350m internal parameters and a prodigious appetite for data. It was trained using 3.3bn words of text culled mostly from Wikipedia, an online encyclopedia. These days, says Dr Manning, Wikipedia is not such a large data-set. If you can train a system on 30bn words its going to perform better than one trained on 3bn. And more data means more computing power to crunch it all.

OpenAI, a research firm based in California, says demand for processing power took off in 2012, as excitement around machine learning was starting to build. It has accelerated sharply. By 2018, the computer power used to train big models had risen 300,000-fold, and was doubling every three and a half months (see chart). It should knowto train its own OpenAI Five system, designed to beat humans at Defense of the Ancients 2, a popular video game, it scaled machine learning to unprecedented levels, running thousands of chips non-stop for more than ten months.

Exact figures on how much this all costs are scarce. But a paper published in 2019 by researchers at the University of Massachusetts Amherst estimated that training one version of Transformer, another big language model, could cost as much as $3m. Jerome Pesenti, Facebooks head of AI, says that one round of training for the biggest models can cost millions of dollars in electricity consumption.

Facebook, which turned a profit of $18.5bn in 2019, can afford those bills. Those less flush with cash are feeling the pinch. Andreessen Horowitz, an influential American venture-capital firm, has pointed out that many AI startups rent their processing power from cloud-computing firms like Amazon and Microsoft. The resulting billssometimes 25% of revenue or moreare one reason, it says, that AI startups may make for less attractive investments than old-style software companies. In March Dr Mannings colleagues at Stanford, including Fei-Fei Li, an AI luminary, launched the National Research Cloud, a cloud-computing initiative to help American AI researchers keep up with spiralling bills.

The growing demand for computing power has fuelled a boom in chip design and specialised devices that can perform the calculations used in AI efficiently. The first wave of specialist chips were graphics processing units (GPUs), designed in the 1990s to boost video-game graphics. As luck would have it, GPUs are also fairly well-suited to the sort of mathematics found in AI.

Further specialisation is possible, and companies are piling in to provide it. In December, Intel, a giant chipmaker, bought Habana Labs, an Israeli firm, for $2bn. Graphcore, a British firm founded in 2016, was valued at $2bn in 2019. Incumbents such as Nvidia, the biggest GPU-maker, have reworked their designs to accommodate AI. Google has designed its own tensor-processing unit (TPU) chips in-house. Baidu, a Chinese tech giant, has done the same with its own Kunlun chips. Alfonso Marone at KPMG reckons the market for specialised AI chips is already worth around $10bn, and could reach $80bn by 2025.

Computer architectures need to follow the structure of the data theyre processing, says Nigel Toon, one of Graphcores co-founders. The most basic feature of AI workloads is that they are embarrassingly parallel, which means they can be cut into thousands of chunks which can all be worked on at the same time. Graphcores chips, for instance, have more than 1,200 individual number-crunching cores, and can be linked together to provide still more power. Cerebras, a Californian startup, has taken an extreme approach. Chips are usually made in batches, with dozens or hundreds etched onto standard silicon wafers 300mm in diameter. Each of Cerebrass chips takes up an entire wafer by itself. That lets the firm cram 400,000 cores onto each.

Other optimisations are important, too. Andrew Feldman, one of Cerebrass founders, points out that AI models spend a lot of their time multiplying numbers by zero. Since those calculations always yield zero, each one is unnecessary, and Cerebrass chips are designed to avoid performing them. Unlike many tasks, says Mr Toon at Graphcore, ultra-precise calculations are not needed in AI. That means chip designers can save energy by reducing the fidelity of the numbers their creations are juggling. (Exactly how fuzzy the calculations can get remains an open question.)

All that can add up to big gains. Mr Toon reckons that Graphcores current chips are anywhere between ten and 50 times more efficient than GPUs. They have already found their way into specialised computers sold by Dell, as well as into Azure, Microsofts cloud-computing service. Cerebras has delivered equipment to two big American government laboratories.

Moores law isnt possible any more

Such innovations will be increasingly important, for the AIfuelled explosion in demand for computer power comes just as Moores law is running out of steam. Shrinking chips is getting harder, and the benefits of doing so are not what they were. Last year Jensen Huang, Nvidias founder, opined bluntly that Moores law isnt possible any more.

Other researchers are therefore looking at more exotic ideas. One is quantum computing, which uses the counter-intuitive properties of quantum mechanics to provide big speed-ups for some sorts of computation. One way to think about machine learning is as an optimisation problem, in which a computer is trying to make trade-offs between millions of variables to arrive at a solution that minimises as many as possible. A quantum-computing technique called Grovers algorithm offers big potential speed-ups, says Krysta Svore, who leads the Quantum Architectures and Computation Group at Microsoft Research.

Another idea is to take inspiration from biology, which proves that current brute-force approaches are not the only way. Cerebrass chips consume around 15kW when running flat-out, enough to power dozens of houses (an equivalent number of GPUs consumes many times more). A human brain, by contrast, uses about 20W of energyabout a thousandth as muchand is in many ways cleverer than its silicon counterpart. Firms such as Intel and IBM are therefore investigating neuromorphic chips, which contain components designed to mimic more closely the electrical behaviour of the neurons that make up biological brains.

For now, though, all that is far off. Quantum computers are relatively well-understood in theory, but despite billions of dollars in funding from tech giants such as Google, Microsoft and IBM, actually building them remains an engineering challenge. Neuromorphic chips have been built with existing technologies, but their designers are hamstrung by the fact that neuroscientists still do not understand what exactly brains do, or how they do it.

That means that, for the foreseeable future, AI researchers will have to squeeze every drop of performance from existing computing technologies. Mr Toon is bullish, arguing that there are plenty of gains to be had from more specialised hardware and from tweaking existing software to run faster. To quantify the nascent fields progress, he offers an analogy with video games: Were past Pong, he says. Were maybe at Pac-Man by now. All those without millions to spend will be hoping he is right.

This article appeared in the Technology Quarterly section of the print edition under the headline "Machine, learning"

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The cost of training machines is becoming a problem - The Economist

Cloud Computing in Automotive Market 2020 Trends, Growth, Scope, Size, Overall Analysis and Forecast by 2025 – Personal Injury Bureau UK

Global Cloud Computing in Automotive market report presents an overview of the market on the basis of key parameters such as market size, revenue, sales analysis and key drivers. The market size of global Cloud Computing in Automotive market is anticipated to grow at large scale over the forecast period (2020-2025). The main purpose of the study report is to give users an extensive viewpoint of the market. So that users can apply strategic processes to benchmark themselves against rest of the world. Key drivers as well as challenges of the market are discussed in the report. Also reports provides an in depth analysis of the Cloud Computing in Automotive market with current and future trends.

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In addition, the market research industry delivers the detailed analysis of the global Cloud Computing in Automotive market for the estimated forecast period. The market research study delivers deep insights about the different market segments based on the end-use, types and geography. One of the most crucial feature of any report is its geographical segmentation of the market that consists of all the key regions. This section majorly focuses over several developments taking place in the region including substantial development and how are these developments affecting the market. Regional analysis provides a thorough knowledge about the opportunities in business, market status& forecast, possibility of generating revenue, regional market by different end users as well as types and future forecast of upcoming years.

Top Leading Key Players are:Amazon Web Services, Microsoft Azure, and Google Cloud Platform

Browse the complete report @https://www.adroitmarketresearch.com/industry-reports/cloud-computing-in-automotive-market

The company profile section also focusses on companies planning expansions along with mergers & acquisitions, new initiatives, R&D updates and financial updates. But, one of the most important aspects focused in this study is the regional analysis. In addition, several aspects such as the perspective of the end users are also being covered for the growth of the Cloud Computing in Automotive market. The market research also covers and conducts the interviews and analyses the growth of the market for the estimated growth of the market.

The study analyses numerous factors that are influencing the Cloud Computing in Automotive market from supply and demand side and further evaluates market dynamics that are impelling the market growth over the prediction period. In addition to this, the Cloud Computing in Automotive market report provides inclusive analysis of the SWOT and PEST tools for all the major regions such as North America, Europe, Asia Pacific, and the Middle East and Africa. The report offers regional expansion of the industry with their product analysis, market share, and brand specifications. Furthermore, the Cloud Computing in Automotive market study offers an extensive analysis of the political, economic, and technological factors impelling the growth of the market across these economies.

In the final section of the report on Cloud Computing in Automotive Market, the dashboard view of the companies is provided, to compare the current industrial scenario and their contribution in total Cloud Computing in Automotive Market. Moreover, it is primarily designed to provide clients with an objective and detailed comparative assessment of key providers specific to a market segment. Report audiences can gain segment-specific manufacturer insights to identify and evaluate key competitors based on the in-depth assessment of their capabilities and success in the Cloud Computing in Automotive Marketplace.

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Adroit Market Research is an India-based business analytics and consulting company incorporated in 2018. Our target audience is a wide range of corporations, manufacturing companies, product/technology development institutions and industry associations that require understanding of a markets size, key trends, participants and future outlook of an industry. We intend to become our clients knowledge partner and provide them with valuable market insights to help create opportunities that increase their revenues. We follow a code- Explore, Learn and Transform. At our core, we are curious people who love to identify and understand industry patterns, create an insightful study around our findings and churn out money-making roadmaps.

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Cloud Computing in Automotive Market 2020 Trends, Growth, Scope, Size, Overall Analysis and Forecast by 2025 - Personal Injury Bureau UK

Where are all the robots? – TechCrunch

Rajat BhageriaContributor

We were promised robots everywhere fully autonomous robots that will drive our cars end-to-end, clean our dishes, drive our freight, make our food, pipette and do our lab work, write our legal documents, mow the lawn, balance our books and even clean our houses.

And yet instead of Terminator or WALL-E or HAL 9000 or R2-D2, all we got is Facebook serving us ads we dont want to click on, Netflix recommending us another movie that we probably shouldnt stay up to watch, and iRobots Roomba.

So what went wrong? Where are all the robots?

This is the question Ive been trying to investigate while building my own robotics company (a currently stealth company named Chef Robotics in the food robotics space) as well as investing in many robotics/AI companies through my venture capital fund Prototype Capital. Heres what Ive learned.

First and foremost, robots arent anything new. Industrial six degrees of freedom (read as six motors serially attached to each other) robot arms were actually developed around 1973 and there are hundreds of thousands of them out there its just that up to this point, almost all of these robots have been in the extremely controlled environment of factory automation doing the same thing over and over again millions of times. And weve formed many multibillion dollar companies through these factory automation robots including FANUC, KUKA, ABB and Foxconn (yes they make their own robots). Go to any automotive manufacturing plant and youll see hundreds (or in Teslas case, thousands). They work insanely well and can pick up massive payloads a full car and have precision sometimes up to a millimeter.

More generally, the world of industrial automation is extremely mature and there are hundreds of systems integrators who you can go to and say, I want an automation machine that does this one extremely narrow use case millions of times. Build me a system to do it. This is how Coca-Cola gets their bottle fillers, Black & Decker makes their drills, Proctor & Gamble makes your shampoo, and more generally how we manufacture most products today. These systems integrators may charge you $1M and make you wait a year to make the machine, but almost any kind of system is possible in this world. The problem with these systems is that they mostly are whats known as hard automation in that theyre mainly mechatronic systems and will work inordinately well if the inputs into the system are exactly what theyre designed and programmed to do; but as soon as you put a two-liter Coca-Cola bottle into a bottling machine designed for half-a-liter bottles, the system doesnt know what to do and will fail.

The other major world we see lots of production robots (excluding purely software AI agents like recommender systems, spam finders for email, object recognition systems for your photos app, chat bots and voice assistants) is surgical robots. One of the major players in this space is a company called Intuitive Surgical ($66B market cap) who has built and already deployed around 5,000 teleoperated robots. Note that these robots are indeed remotely controlled by a physician and arent mostly autonomous. But considering that upwards of 40% of deaths in a hospital are correlated with a mistake that a physician makes, patients are paying extra for these robotic surgeries and hospitals are buying them in droves; major players like Verb Surgical, Johnson & Johnson, Auris Health, and Mako Robotics are following this trend.

What youll notice about both factory automation and surgical robots is that theyre in extremely controlled environments. In the case of factory robots, the robots arent really thinking but rather doing the same thing over and over again. And in the case of surgical robots, almost all the perception, thinking and control is being done by a human operator. But as soon as you make the factory automation robots think for themselves or have the surgical robot make decisions without human supervision, the systems break down.

The distinction to be made is that we dont see robots today in the day-to-day world we live in in noncontrolled environments. Why dont we see robots in the day-to-day world? Whats the one major thing that is preventing us from reaching our dystopian world robotic future? Is it a hardware issue? A software issue? An intelligence issue? An economics issue? A human interaction issue?

In order to answer that question, its important to understand what a robot actually means. In the literature, a robot is an agent that does four things:

In the last 50 years, weve made exponential advances in each of these realms:

In other words, purely from a technical perspective (well come to economics and human interaction later), it doesnt seem like sensing and acting are the major bottlenecks. We have really great and cheap sensors and we have great actuation technology (thanks mainly to industrial automation).

So the problem is mainly in think. Specifically, according to University of Pennsylvania Engineering Dean Vijay Kumar and Founder of the Robotics GRASP Lab, the reason we dont see robots in our day-to-day world is that the physical world is continuous while computation, and therefore sensing and control, are discrete, and the world is extremely highly dimensional and stochastic. In other words, just because a manipulator can pick up a tea cup does not mean it can pick a wine glass. Currently the paradigm for think that most companies have adopted is based on the idea of machine learning and more specifically deep learning where the basic premise is that instead of writing a program as in classical computing that takes in some input and spits out an output based on it, why dont we give an agent a bunch of inputs and outputs in the form of training data and have it come up with the program? Just as we learned in algebra that the equation for a line is y = mx + b, the basic idea is that if we give the machine learning algorithm y and x, it can find m and b (except on much more complex equations). This approach works well enough to get you most of the way there.

But in the insanely unpredictable world we live in, the idea of providing training data in the hordes with the idea of if you see this, do this doesnt work; simply said, there will never be enough training data to predict every single case out there. We dont know what we dont know and unless we have training data for every single instance that has ever happened to an agent in the past and that will ever happen to an agent in the future, this deep learning-based model can not bring us to full autonomy (How can you predict something that you dont even know is possible?). Humans as intelligent beings can actually think; deep learning-based agents arent thinking theyre pattern matching and if the current state the agent is in doesnt match one of the patterns thats already been given to it, the robot fails (or in the case of autonomous vehicles, crashes).

So perhaps deep neural nets are not the way we get to 100% autonomous systems (which is why companies like OpenAI are investing into reinforcement learning algorithms that mimic a Pavlovian reward/pain-based approach to learning). But in the meantime for startups, what if the question of how to build a fully autonomous agent is the wrong question to ask?

A company that exemplifies this idea of not pursuing 100% autonomy is Ripcord, a Hayward, California-based startup that does autonomous digitization of paper. Today corporations have thousands of reams of paper that theyd love to digitize no human went to college to become a staple remover, says CEO Alex Fielding and so they send them to Ripcord where the reams are fed into robot cells that pick and place each sheet, scan them and then restack them. Chatting with Alex in the factory, one of the things that struck me was that he never mentioned the idea of automating humans. Rather his pitch was that Ripcord makes a human 40x more efficient. I saw this first hand one human oversees four robotic work cells at Alexs facility. In one example, the robot was working extremely fast through sheets of paper when it perceived a sheet that confused it. Just then, the human overseeing the system received a clear notification on a screen with the problem. The human quickly fixed the problem within 10 seconds, and the robot spurred back into life for the next sheets.

So what if the question for how to build a successful robotics company is not How do we build agents to automate humans? but rather How do we build agents to make humans 40x more efficient while also using their intelligence to handle all the edge cases? While artificial intelligence develops, this seems to be the formula for building successful companies in the meantime.

Another company that exemplifies this is Kiwi Robotics. Based in Berkeley, California, Kiwi makes food delivery mobile robots. But chatting with CEO Felipe Chvez, We are not an AI company; we are a delivery company. When Felipe founded Kiwi, he didnt invest into a ton of expensive machine learning engineers; rather after building the hardware prototype, he built low-latency software to be able to teleoperate Kiwi. The idea was initially humans doing 100% of decision-making for Kiwi and slowly theyd build algorithms to decrease that from 100% to full autonomy. Today Kiwi has a team of dozens of teleoperators in Colombia (where Felipe was born) and has made over 100,000 deliveries. A single human can oversee multiple robots and the robot is making almost all the decisions and the humans are just course-correcting. On the other hand, many competitors who are investing in full autonomy are struggling to make even 1,000 deliveries. [Full disclosure I am an investor in Kiwi Robotics though my fund Prototype Capital.]

In both of these cases, one of most important factors is not the machine learning algorithms but rather the human machine interface. Is that what contemporary robotics companies are missing? According to Keenan Wyrobek, the Founder of blood drone delivery company Zipline and an early robotics pioneer, while I get the cut labor pitch works well to business owners in the US market, I have seen countless robotics startups fail with this mindset. Make sure your design and eng[ineering] team focus on making all the users of your system more productive I dont care how good your robot is, it still has users (people who set up, reconfigure, troubleshoot, maintain, etc). And if those users are not at the center of your design process your robots will not work well enough to ever see a[n] ROI.

Further, according to Amar Hanspal, CEO of Bright Machines and former Co-CEO of Autodesk, The common factor between both is that robotic companies start with the technology first (it is too hard and somewhat exciting, so it becomes an end goal in itself) rather than the problem they are trying to solve. The key is to define a problem youre trying to solve and then build a great UX around it. Robotics is a means to an end, not the end itself.

So far weve seen that one of the major reasons robotics for the everyday world havent lived up to their promise is that the world is extremely stochastic and artificial intelligence-based on deep learning-based models simply isnt good enough to deal with every corner case. So perhaps instead of a labor savings model, robotics companies should adopt the human augmentation model. Take Apple and Airbnbs playbook of a human centered design-first mentality not engineering and invest into amazing user experience.

Here are a few other things we can do to bring robots to the forefront:

The first is to sell the product before building it. In the software world of Silicon Valley, The Lean Startup by Eric Ries has popularized the idea of launch fast and iterate fast till you get to product market fit. For software startups, this works insanely well. But with hardware and robotics, what ends up happening is that engineering talent-heavy startups focus initially not on sales but rather on engineering and they build, build, build. Then they go to customers to sell, customers say, This doesnt exactly meet our goals, the companies dont have enough runway to iterate and then they die. This has happened over and over. It seems like for software startups, the lean startup approach works since you can launch most of the time for free (thanks to the cloud), iterate once in the field, deployments are fast and you have five or six shots on goal before you run out of money in your seed round. But in the world of hardware, you have upfront hardware costs, deployments are slow, iteration cycles are slow and you only have one or two shots on goal.

To be clear, we are extremely adept at hardware; its just that software-centric Silicon Valley isnt (with notable exceptions being Apple and Tesla). Perhaps one of the reasons is a lack of selling before building. Case in point: Boeing didnt approach Juan Trippe, the legendary founder of Pan Am Airlines and say, Heres a Boeing 747 do you like it? No. Let me go back and build a new version Do you like it now? (i.e., iteration a la The Lean Startup). Instead, Boeing asked Pan Am to give them an upfront order for dozens of units with all the features upfront so that Boeing could build it right the first time. In other words, Boeing sells their product before building it. Systems Integrators ask for orders and cash before building anything. So do most hardware companies and military branches. Maybe robotics companies can take a page from Bill Gates playbook and sell MS-DOS to IBM before writing MS-DOS.

One of the benefits of selling before building is that you can do a sanity check on unit economics. Robotics is one of those fields where not only is there technical risk but also unit economics risk. Many companies have historically found that even if they can find a great idea in a constrained environment, build the tech, raise venture capital and build great human machine collaboration, their economics dont make sense and once again they fail. By selling before building, you have to analyze your customers economics as well as your own and make sure it makes sense. If you try to sell your product before building and nobody wants it, its an extremely low-risk way of figuring out that your customers probably wont buy it and that you may want to move onto the next idea.

More generally on economics, we need to shift from upfront cash models to robotics as a service models. A lot of the customers who will be buying robotic applications have extremely low margins and cannot afford to pay $100,000+ upfront for a system (even if the payback period is a year or two). Adding fuel to the fire is that the activation energy ends up being too much to change something when they already have something that works. Thus they reject the product (and then the startup dies). We can take a page from the solar cell/photovoltaic cell industry here; solar cell economics make a ton of sense for a lot of homeowners and yet for a very long time in the 2000s, we saw very few solar cells. Why? The upfront was too much for most Americans even though the economics make sense in a few years. The tipping point was not technical but rather financial with companies like Solar City, Sunrun, Sun Power and others innovating on a model where the customer pays almost $0 upfront but then has monthly PPA loans where they pay per kilowatt-hour that the cells generate. The same was the innovation of cloud computing rather than buying a bunch of servers locally to run Oracle and SAP, companies like Salesforce came up with a pay for what you use model. To be successful, robotics companies need to do financial engineering so that customers have to pay very little upfront and only pay for what they use (each hour worked, each sheet of paper scanned, each dish cleaned, each mile driven, each kilo of freight shipped).

Another one of the benefits of selling before building is that you can consistently test in the field even though youre building hardware too. Traditionally this iteration after deployment is the benefit of software (compared to Apple who often starts hardware development for some of their Macs five to seven years ahead of launch). Since you already have a customer, they have a vested interest in making the product work. One strategy weve seen be extremely successful is providing some advisor equity to your early customers so that theyre further incentivized to work with you to make the product economically and technically work for them.

But not everything has to be software either. These days, most Silicon Valley VCs cringe when they see robotics companies that are hardware heavy. Well invest if you take a more software approach they say, and so today we see robotics companies trying to use almost 100% off-the-shelf hardware and focus almost all their efforts on software. That makes sense in certain applications but the fact of the matter is that hardware fails a lot less than software and hardware has been around for millennia and were really good at it compared to the relatively nascent computing era. In a lot of cases, hardware can solve the problem a lot better than software. Take for example bin picking; today there are dozens of startups who have raised hundreds of millions of dollars from major VCs building generic deep learning-based and reinforcement learning-based systems to be able to pick and place generic objects out of a bin. On the other hand, at PACK Expo in Las Vegas, I was able to see a company called Soft Robotics. They have taken a mostly hardware-based approach to bin picking with a novel gripper that, without any computer vision, can pick up and place objects using great control (much more consistently than almost all computer vision-based startups). Sure, building a software and training data moat matters, but why solve the problem in a more complex way when theres a simpler and robust solution? We shouldnt run from hardware we just need to rethink how to do hardware.

More generally, Silicon Valley VCs have created a mentality that if a company cannot be worth a billion dollars, its not worth doing or investing in. So robotics founders try to build technology that can serve every possible customer in the hopes of raising venture capital; and although they alleviate VCs, they end up building a product that doesnt make any one customer extremely happy. The best companies at the beginning had extremely small markets. In our highly dimensional world, trying to build an insanely generic robotics company day one is a mistake. Rather, at the beginning its important to focus on one (or maybe two) customer(s) maniacally. Once you solve that customers problem, youll find that other customers probably want something similar. Robotics will probably not scale as fast as consumer or even enterprise software companies at the beginning. But this is not unheard of. Before Intel and the personal computer era, computing worked very similar to how automation systems integrators work today: you went to an engineering firm for a specific computer that could do one thing say calculate the trajectory of your missiles you pay them $1M, you wait six months and you get your computer the size of a room. Just as computing was slow and nonscalable at the beginning so too will be robotics. Thats okay and there are still billions of dollars in returns to reap.

Finally, perhaps the way to go to build a successful robotics company is indeed to sell vertical B2B solutions (i.e., the hole in the wall not a drill) instead of making consumer-facing B2C companies. The promise of the latter was simple: If existing customers dont see the technology working for them or the economics making sense, why dont we both develop the technology and be our own customer? After all, our tech is better so we can make our own profit and plus we can control the environment and so it should be technically easier too. It was the same pitch as innovative high frequency trading firms who decided to build their own hedge funds instead of selling their technology to other hedge funds. So we saw B2C robotic restaurants, end-to-end legal firms that were building AI to automate itself and consumer-facing coffee shops. The problem was two-fold: One, most B2C businesses like restaurants fail and most startups fail, but trying to do both is just too much, especially for a startup with limited runway; and two, a lot of these brands didnt work out not because the tech didnt work but rather because the consumer brand wasnt strong enough. The kind of team it takes to build a hard technical product is very different than the kind of team it takes to build a consumer brand and, oftentimes, even if their tech works, the brand wasnt strong enough and so customers came once to take a picture but retention wasnt good enough to make the economics work. The same is true for education-based and toy robotics while these are cool, we have yet to see an example of a company who used this model to build a lasting company since it seems like theyre more nice to have than need to have. (So when an economic downturn like the one were in happens, nobody wants the product anymore.)

There also has recently been a trend toward platforms to empower robotics companies to make it easier for them to succeed just like AWS made it easier for modern internet companies to succeed. Again this sounds great on the surface but the difference is that before AWS, there was a flourishing set of software companies who were building great businesses and who had cash to pay AWS for a better product. But today, there simply arent enough robotics companies who have enough revenue to make these B2B companies make sense. It still seems we need the killer application of the iPhone before the platform of the App Store makes sense.

In other words, we have a long way to go in terms of seeing robots in our day-to-day world since there are so many places robotics companies can go wrong. Here are the kinds of robots that I think well see more of in the day-to-day world in the short term (next two to four years):

More autonomous factory automation. For factory automation, the customers already exist. If we can build better technology that makes these systems more autonomous, well see a lot more customers who want this.

Semi-autonomous and teleoperated companies. Similar to the surgical robots, Tesla autopilot and Kiwi, well see a lot more companies whose goal is partial autonomy and of augmenting humans not replacing them.

Manipulation based robots in factory-like settings. In 2015 mainly because of Googles investment into self-driving cars, VCs invested hundreds of millions into autonomous vehicles with the premise that driving is driving is driving. If we can solve driving for one car and in one city, it can probably scale pretty well. Today, were in a bit of a winter in autonomous vehicles and very few companies seem to have an idea of what to do next (mainly because the world is so random and deep learning may not be enough). On the other hand, manipulation was left behind and today seems to be making a comeback as were seeing engineers leaving autonomous vehicle companies and seeking something new that could actually be in production sooner. Manipulation applications tend to be in extremely controlled environments and well probably see more of these (such as Bright Machines microfactories and AMP Robotics recycling sorting robots)

In the same vein, today theres a trend of moving toward the cloud. Imagine that before the first Industrial Revolution, we used to make textiles in our homes. But then we realized that we can centralize production of textiles at factories and take advantage of economies of scale. As a result, today we see very few people making textiles at our homes. Applying this to today, if you imagine a world in which almost everything moves to the cloud and you send your household chores to someone else to do them using a central robotic facility (cooking, dishwashing, cloth washing, cloth folding, etc.), theres a massive opportunity to apply robots that affect the everyday person but are in a setting where robots work best (factories).

Perhaps the only thing well do in our homes then is cleaning, and thus there is and always will be a massive opportunity for cleaning robots from systems to clean indoor homes, mow outdoor laws, clean indoor malls and other B2B applications, and plow outdoor snow.

Robotics still holds immense promise and its certainly doable. Selling before building, ensuring the unit economics work early with low-risk bets, testing the system often in the field, providing early customers advisor equity to align incentives, building a product to solve a problem for a particular customer well rather than building something generic, thinking about robots as a combination of great hardware and great software rather than software alone and pursuing vertical B2B applications can help. But in a broader sense, rather than hitting every nail with the same software mentality hammer, it may be time to think from scratch.

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Where are all the robots? - TechCrunch

Cloud Computing: Concepts, Technology & Architecture (The …

Cloud computing, more than most disciplines in IT, suffers from too much talk and not enough practice. Thomas Erl has written a timely book that condenses the theory and buttresses it with real-world examples that demystify this important technology. An important guidebook for your journey into the cloud.--Scott Morrison, Chief Technology Officer, Layer 7 Technologies

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Thomas, in his own distinct and erudite style, provides a comprehensive and a definitive book on cloud computing. Just like his previous masterpiece, Service-Oriented Architecture: Concepts, Technology, and Design, this book is sure to engage CxOs, cloud architects, and the developer community involved in delivering software assets on the cloud. Thomas and his authoring team have taken great pains in providing great clarity and detail in documenting cloud architectures, cloud delivery models, cloud governance, and economics of cloud, without forgetting to explain the core of cloud computing that revolves around Internet architecture and virtualization. As a reviewer for this outstanding book, I must admit I have learned quite a lot while reviewing the material. A must have book that should adorn everybodys desk!--Vijay Srinivasan, Chief Architect - Technology, Cognizant Technology Solutions

This book provides comprehensive and descriptive vendor-neutral coverage of cloud computing technology, from both technical and business aspects. It provides a deep-down analysis of cloud architectures and mechanisms that capture the real-world moving parts of cloud platforms. Business aspects are elaborated on to give readers a broader perspective on choosing and defining basic cloud computing business models. Thomas Erls Cloud Computing: Concepts, Technology & Architecture is an excellent source of knowledge of fundamental and in-depth coverage of cloud computing.--Masykur Marhendra Sukmanegara, Communication Media & Technology, Consulting Workforce Accenture

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A must-read for anyone involved in cloud design and decision making! This insightful book provides in-depth, objective, vendor-neutral coverage of cloud computing concepts, architecture models, and technologies. It will prove very valuable to anyone who needs to gain a solid understanding of how cloud environments work and how to design and migrate solutions to clouds.--Gijs in t Veld, Chief Architect, Motion10

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One of the best books on cloud computing I have ever read. It is complete yet vendor technology neutral and successfully explains the major concepts in a well-structured and disciplined way. It goes through all the definitions and provides many hints for organizations or professionals who are approaching and/or assessing cloud solutions. This book gives a complete list of topics playing fundamental roles in the cloud computing discipline. It goes through a full list of definitions very clearly stated. Diagrams are simple to understand and self-contained. Readers with different skill sets, expertise, and backgrounds will be able to understand the concepts seamlessly.--Antonio Bruno, Infrastructure and Estate Manager, UBS AG

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Cloud Computing: Concepts, Technology & Architecture is a comprehensive compendium of all the relevant information about the transformative cloud technology. Erls latest title concisely and clearly illustrates the origins and positioning of the cloud paradigm as the next-generation computing model. All the chapters are carefully written and arranged in an easy-to-understand manner. This book will be immeasurably beneficial for business and IT professionals. It is set to shake up and help organize the world of cloud computing.--Pethuru Raj, Ph.D., Enterprise Architecture Consultant, Wipro

A cloud computing book that will stand out and survive the test of time, even in one of the fastest evolving areas of technology. This book does a great job breaking down the high level of complexity of cloud computing into easy-to-understand pieces. It goes beyond the basic, often repeated, explanations. It examines the fundamental concepts and the components, as well as the mechanisms and architectures that make up cloud computing environments. The approach gradually builds the readers understanding from the ground up.

In a rapidly evolving area like cloud computing, its easy to focus on details and miss the big picture. The focus on concepts and architectural models instead of vendor-specific details allows readers to quickly gain essential knowledge of complex topics. The concepts come together in the last part of the book, which should be required reading for any decision maker evaluating when and how to start a transition to cloud computing. Its thorough, comprehensive coverage of fundamentals and advanced topics makes the book a valuable resource to keep on your desk or your eBook reader, regardless if youre new to the topic or you already have cloud experience.

I highly recommend the book to those looking to implement or evaluate cloud environments, or simply looking to educate themselves in a field that will shape IT over the next decade.--Christoph Schittko, Principal Technology Strategist & Cloud Solution Director, Microsoft

Cloud Computing: Concepts, Technology & Architecture is an excellent resource for IT professionals and managers who want to learn and understand cloud computing, and who need to select or build cloud systems and solutions. It lays the foundation for cloud concepts, models, technologies, and mechanisms. As the book is vendor-neutral, it will remain valid for many years. We will recommend this book to Oracle customers, partners, and users for their journey toward cloud computing. This book has the potential to become the basis for a cloud computing manifesto, comparable to what was accomplished with the SOA manifesto.--Jurgen Kress, Fusion Middleware Partner Adoption, Oracle EMEA

Thomas Erl is a top-selling IT author, founder of Arcitura Education, editor of the Service Technology Magazine and series editor of the Prentice Hall Service Technology Series from Thomas Erl. With more than 175,000 copies in print world-wide, his books have become international bestsellers and have been formally endorsed by senior members of major IT organizations, such as IBM, Microsoft, Oracle, Intel, Accenture, IEEE, HL7, MITRE, SAP, CISCO, HP, and many others. As CEO of Arcitura Education Inc. and in cooperation with CloudSchool.com and SOASchool.com, Thomas has led the development of curricula for the internationally recognized Cloud Certified Professional (CCP) and SOA Certified Professional (SOACP) accreditation programs, which have established a series of formal, vendor-neutral industry certifications obtained by thousands of IT professionals around the world. Thomas has toured over 20 countries as a speaker and instructor and regularly participates in international conferences, including Service Technology Symposium and Gartner events. More than 100 articles and interviews by Thomas have been published in numerous publications, including The Wall Street Journal and CIO Magazine.

Dr. Zaigham Mahmood is a published author of six books, four of which are dedicated to cloud computing. He acts as a technology consultant at Debesis Education UK and a Researcher at the University of Derby, UK. He further holds positions as a foreign professor and professor extraordinaire with international educational institutions. Professor Mahmood is a certified cloud trainer and a regular speaker at the International SOA, Cloud + Service Technology Symposium, and he has published more than 100 articles. His specialized areas of research include distributed computing, project management, and e-government.

Professor Ricardo Puttini has 15 years of field experience as a senior IT consultant at major government organizations in Brazil. He has taught several undergraduate and graduate-level courses in service orientation, service-oriented architecture, and cloud computing. Ricardo was the general chair of the 4th International SOA Symposium and 3rd International Cloud Symposium that was held in the spring of 2011. He holds a Ph.D. in Communication Networks (2004) from the University of Brasilia, where he has taught in the Electrical Engineering department since 1998. Ricardo spent 18 months at the LEcole Superieure dElectricite (Supelec) in Rennes, France, during his Ph.D., where he started researching distributed system architecture and security.

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Cloud Computing Overview – Tutorialspoint

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Cloud Computing provides us means of accessing the applications as utilities over the Internet. It allows us to create, configure, and customize the applications online.

The termCloudrefers to aNetworkorInternet. In other words, we can say that Cloud is something, which is present at remote location. Cloud can provide services over public and private networks, i.e., WAN, LAN or VPN.

Applications such ase-mail, web conferencing, customer relationship management (CRM) execute on cloud.

Cloud Computingrefers tomanipulating, configuring,andaccessingthe hardware and software resources remotely. It offers online data storage, infrastructure, and application.

Cloud computing offers platform independency, as the software is not required to be installed locally on the PC. Hence, the Cloud Computing is making our business applicationsmobileandcollaborative.

There are certain services and models working behind the scene making the cloud computing feasible and accessible to end users. Following are the working models for cloud computing:

Deployment models define the type of access to the cloud, i.e., how the cloud is located? Cloud can have any of the four types of access: Public, Private, Hybrid, and Community.

Thepublic cloudallows systems and services to be easily accessible to the general public. Public cloud may be less secure because of its openness.

Theprivate cloudallows systems and services to be accessible within an organization. It is more secured because of its private nature.

Thecommunity cloudallows systems and services to be accessible by a group of organizations.

Thehybrid cloudis a mixture of public and private cloud, in which the critical activities are performed using private cloud while the non-critical activities are performed using public cloud.

Cloud computing is based on service models. These are categorized into three basic service models which are -

Anything-as-a-Service (XaaS) is yet another service model, which includes Network-as-a-Service, Business-as-a-Service, Identity-as-a-Service, Database-as-a-ServiceorStrategy-as-a-Service.

TheInfrastructure-as-a-Service (IaaS)is the most basic level of service. Each of the service models inherit the security and management mechanism from the underlying model, as shown in the following diagram:

IaaSprovides access to fundamental resources such as physical machines, virtual machines, virtual storage, etc.

PaaS provides the runtime environment for applications, development and deployment tools, etc.

SaaSmodel allows to use software applications as a service to end-users.

The concept ofCloud Computingcame into existence in the year 1950 with implementation of mainframe computers, accessible viathin/static clients. Since then, cloud computing has been evolved from static clients to dynamic ones and from software to services. The following diagram explains the evolution of cloud computing:

Cloud Computing has numerous advantages. Some of them are listed below -

One can access applications as utilities, over the Internet.

One can manipulate and configure the applications online at any time.

It does not require to install a software to access or manipulate cloud application.

Cloud Computing offers online development and deployment tools, programming runtime environment throughPaaS model.

Cloud resources are available over the network in a manner that provide platform independent access to any type of clients.

Cloud Computing offerson-demand self-service. The resources can be used without interaction with cloud service provider.

Cloud Computing is highly cost effective because it operates at high efficiency with optimum utilization. It just requires an Internet connection

Cloud Computing offers load balancing that makes it more reliable.

Although cloud Computing is a promising innovation with various benefits in the world of computing, it comes with risks. Some of them are discussed below:

It is the biggest concern about cloud computing. Since data management and infrastructure management in cloud is provided by third-party, it is always a risk to handover the sensitive information to cloud service providers.

Although the cloud computing vendors ensure highly secured password protected accounts, any sign of security breach may result in loss of customers and businesses.

It is very difficult for the customers to switch from oneCloud Service Provider (CSP)to another. It results in dependency on a particular CSP for service.

This risk involves the failure of isolation mechanism that separates storage, memory, and routing between the different tenants.

In case of public cloud provider, the customer management interfaces are accessible through the Internet.

It is possible that the data requested for deletion may not get deleted. It happens because either of the following reasons

There are four key characteristics of cloud computing. They are shown in the following diagram:

Cloud Computing allows the users to use web services and resources on demand. One can logon to a website at any time and use them.

Since cloud computing is completely web based, it can be accessed from anywhere and at any time.

Cloud computing allows multiple tenants to share a pool of resources. One can share single physical instance of hardware, database and basic infrastructure.

It is very easy to scale the resources vertically or horizontally at any time. Scaling of resources means the ability of resources to deal with increasing or decreasing demand.

The resources being used by customers at any given point of time are automatically monitored.

In this service cloud provider controls and monitors all the aspects of cloud service. Resource optimization, billing, and capacity planning etc. depend on it.

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Cloud Computing Overview - Tutorialspoint

The Basics of Cloud Computing | Lucidchart

Cloud computing is taking the world by storm. In fact, 94% of workloads and compute instances will be processed through cloud data centers by 2021, compared to only 6% by traditional data centers, according to research by Cisco.

The principle of the cloud isnt new, but as more and more companies and businesses switch to cloud-based services, its important to understand the nuances of cloud computing terminology and concepts.

For non-techies out there, the cloud might be an intimidating and nebulous concept. We hear about cloud computing all the time, but what exactly does it mean?

The National Institute of Standards and Technology (NIST) describes the basics of cloud computing this way:

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.

Still confused?

In short, the cloud is the Internet, and cloud computing is techspeak that describes software and services that run through the Internet (or an intranet) rather than on private servers and hard drives.

Cloud computing differs from traditional IT hosting services in that the consumer (whether thats a business, organization, or individual user) generally doesnt own the infrastructure needed to support the programs or applications they use.

Instead, those elements are owned and operated by a third party, and the end-user pays only for the services they use. In other words, cloud computing is an on-demand, utility-based model of computing.

On-demand self-service

Users can access computing services via the cloud when they need to without interaction from the service provider. The computing services should be fully on-demand so that users have control and agility to meet their evolving needs.

Broad network access

Cloud computing services are widely available via the network through users preferred tools (e.g., laptops, desktops, smartphones, etc.).

Resource pooling

One of the most attractive elements of cloud computing is the pooling of resources to deliver computing services at scale. Resources, such as storage, memory, processing, and network bandwidth, are pooled and assigned to multiple consumers based on demand.

Rapid elasticity

Successful resource allocation requires elasticity. Resources must be assigned accurately and quickly with the ability to absorb significant increases and decreases in demand without service interruption or quality degradation.

Measured service

Following the utility model, cloud computing services are measured and metered. This measurement allows the service provider (and consumer) to track usage and gauge costs according to their demand on resources.

Compare cloud vs on-premises server solutions to find the right solution for your organization.

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Cloud solutions come in three primary service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

IaaS gives users access to storage, networking, servers, and other computing resources via the cloud. While the user is still responsible for managing their applications, data, middleware, etc., IaaS provides automated and scalable environments that provide a high degree of control and flexibility for the user.

For example, many businesses use IaaS to support workload spikes during busy seasons (like holidays).

Popular IaaS providers include:

Find the best cloud platform for you and your business when you compare AWS, Azure, and GCP.

Learn more

This service layer is primarily geared towards developers and operations professionals. Service providers rent out cloud-based platforms for users to develop and deliver applications. In other words, PaaS provides a framework that makes it easier and more efficient to build, customize, and deploy applications.

Cloud application services are the most well-known of the cloud service models. The software is hosted, packaged, and delivered by a third party through the Internet (typically on a browser-based interface). By delivering the software application over the Internet, enterprises can offload the costs of management and maintenance to the vendor(s).

Popular SaaS options include email and customer relationship management software.

There are three main cloud service options: private, public, and hybrid clouds. Each has its own advantages and disadvantages and which one you (or your business) choose will depend on your data as well as the level of security and management you need.

A public cloud is probably the most commonly understood cloud computing option. This is where all the services and supporting infrastructure are managed off-site over the Internet and shared across multiple users (or tenants).

A good example of a public cloud at the individual consumer level is a streaming service like Netflix or Hulu. Users subscribe to the service through an individual account but access the same services across the platform through the Internet.

The advantage of using a public cloud is the increased efficiency and subsequent cost-effectiveness from shared resources. Public clouds are typically cheaper than private and hybrid cloud solutions (as well as traditional on-premise computing) because they rely on economies of scale. Users dont have to pay for services they arent using and dont have to worry about managing and maintaining the physical infrastructure.

A private cloud provides IT services through the Internet or a private network to select users, rather than to the general public. Instead of having multiple tenants, like a public cloud does, a private cloud typically has only one tenant. All the data is protected behind a firewall. This is a popular choice for many businesses who want the agility of the cloud with greater customization and security.

Private clouds can reside on-site or off-site. The distinguishing feature is the single, private tenant who maintains greater control over the IT services. Private clouds are popular choices for organizations who have high priorities on security and compliance.

A hybrid cloud environmentcombines both private and public cloud elements to varying degrees. Despite operating independently, the clouds in a hybrid environment communicate over an encrypted connection and allow for the portability of data and applications.

This is an increasingly popular cloud solution because it allows organizations greater flexibility to meet their IT needs.

There are many potential advantages to adopting cloud-based solutions for your business. Depending on your business and data needs, migrating to a cloud environment can result in the following benefits:

Although the initial price tag for migrating to the cloud can give some businesses sticker shock, there are attractive opportunities for ROI and cost savings. Operating on the cloud typically means adopting a pay-as-you-go model, which means you no longer have to pay for IT youre not using (whether thats storage, bandwidth, etc.).

Plus, cloud solutions are particularly affordable for smaller businesses who dont have the capital to build out and manage their own IT infrastructures. Greater efficiencies and economies of scale mean more money in your pocket in the long run.

A managed cloud platform is generally much more reliable than an in-house IT infrastructure, with fewer instances of downtime or service interruptions. Most providers offer 24/7 support and over 99.9% availability.

With backups for their backups, you can rest assured your data and applications will be available whenever you need them.

The cloud brings a level of portability unheard of with traditional IT delivery. By managing your data and software on the cloud, employees can access necessary information and communicate with each other whenever and wherever they want from their laptop, smartphone, or other Internet-connected devices.

Cloud-based solutions open up opportunities for more remote work and higher productivity and efficiency as everyone is assured access to the same updated information at the touch of a button.

Is your business preparing to move to the cloud? Use our checklist to keep your cloud migration strategy on track.

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The Basics of Cloud Computing | Lucidchart

Forget Amazon, Microsoft Is a Better Cloud Computing Stock …

Editor's note: Inaccurate information about use of Azure has been removed from this article. In an SEC filing on March 31, Microsoft noted that a March 28 blog post it made "contained, among other information, a statement that 'We have seen a 775percent increase of our cloud services in regions that have enforced social distancing or shelter in place orders.' The metric in this statement was intended to refer only to a specific cloud-based service, Teams calling and meeting monthly users, in a specific country, Italy. The statement was not intended to provide information about the performance of Azure and cloud services generally, Microsofts Intelligent Cloud segment, or Microsoft as a whole. We corrected the blog entry to clarify the nature of this information on March30, 2020."

With millions of people sheltering in place amid the COVID-19 pandemic, the cloud computing market is getting a serious usage boost.

Schools, corporations, and individuals are using cloud-based software to learn, collaborate, and stay connected. That's driving increased demand for cloud services, boding well for the likes of Amazon (NASDAQ:AMZN), through its Amazon Web Services, and Microsoft (NASDAQ:MSFT), through its Azure services.

Amazon is the overall leader in this sector, but Microsoft is a scrappy second-place player. It's been chipping away at AWS' lead, and with demand surging amid the pandemic, it's emerging as the better cloud computing stock to own.

Image source: Getty Images.

The COVID-19 pandemic is changing the way the world operates, including how we work. A significant number of companies deemed non-essential have transitioned to remote work environments to remain in operation, using cloud-based software to collaborate and work. At the same time, a large segment of the population is practicing social distancing and turning to virtual tools to stay connected.

That plays into Microsoft's strengths thanks to many of its software tools that reside on the cloud. Take Skype, its cloud-based video conferencing tool. Since the pandemic hit, Skype has seen a 70% surge in daily users. Skype calling minutes are up 220%.

Microsoft's Teams collaboration tool is also enjoying red-hot demand, with daily active users jumping by 12 million in one week alone in early March. Since then, demand continues to surge as more workers get used to the new work-at-home norm.

That demand for cloud-based services isn't going to go away anytime soon, even if cities begin easing social distancing rules in the coming weeks or months.

Take the tech giant's newly signed deal with the National Basketball Association as one example of what the future may look like. The NBA is adopting Microsoft's Azure cloud to offer fans an enhanced experience. The NBA suspended its basketball season in March. To get the season going again, there is a real chance that games could be played in empty arenas and broadcast to fans. If that's the case, the NBA is hoping its cloud deal with Microsoft will help keep fans engaged remotely. The NBA isn't the only sports league that has to figure out how to keep fans coming back for more while stay-at-home orders are in place. The deal with the NBA may be the first of more to come for Microsoft.

Then there's Office 365, Microsoft's cloud-based productivity software offering that has more than 38 million subscribers. In an effort to get more consumers to pay monthly instead of upgrading their OS every few years, Microsoft is rebranding Office 365 into Microsoft 365, and is adding more AI-driven features. It's also launching a subscription plan that costs $9.99 a month for families and $6.99 a month for individuals.

That's not to say AWS isn't winning cloud contracts, but Microsoft's moves are more high profile and, given the pandemic, could be winning bets over the long run.

An important growth area for both AWS and Microsoft are federal, state, and local governments. With many government systems outdated and in need of an upgrade, Microsoft and AWS have been jockeying for contracts. The biggest of all, the Joint Enterprise Defense Infrastructure project or JEDI, a 10-year $10 billion move to the cloud for the Pentagon, was awarded to Microsoft last year, driving the stock higher. But it was quickly contested by AWS, which said it was the shoe-in to win the contract until President Donald Trump got involved. That's prompted AWS to file a lawsuit seeking to get the contract halted, claiming political bias.

Both companies have much to lose by not landing the contract, but Microsoft is in a more precarious position. In order to win more government contracts it needs to get in the door, something AWS has already achieved.

The case is still being worked out in the courts, but Microsoft did get a partial win this month, when the Defense Department's inspector general found that awarding the full contract to Microsoft (instead of breaking it up among its rivals) was "consistent with applicable acquisition standards," and not driven by political bias on the part of the Trump administration.

That was welcome news to Microsoft, which said the inspector general's report shows the DoD properly awarded the contract to the software giant.In a blog titled "It bid high and lost. Should Amazon be allowed to do-over on JEDI?," Microsoft's deputy general counsel Jon Palmer argued Amazon lost the contract because it priced its offering too high, not because Trump hates AWS owner Jeff Bezos.

"There is a simple explanation for Microsoft's victory -- the strength of our technology, and our willingness to listen to and respond to our potential customers," wrote Palmer. "Even if you believe that Amazon may have started as the front runner, it's clear our team worked hard to catch up and surpass them by investing in our technology and listening to the DoD."

It's not clear what the courts will decide, but with cloud momentum growing at Microsoft and more opportunities to grow because of the COVID-19 pandemic, Microsoft is the better cloud computing stock.

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Forget Amazon, Microsoft Is a Better Cloud Computing Stock ...

Cloud Computing Risks, Challenges & Problems Businesses …

Everywhere you turn these days the cloud is being talked about. This ambiguous term seems to encompass almost everything about us. While the cloud is just a metaphor for the internet,cloud computingis what people are really talking about these days. It provides better data storage, data security, flexibility, increased collaboration between employees, and changes the workflow of small businesses and large enterprises to help them make better decisions while decreasing costs.

It is clear that utilizing the cloud is a trend that continues to grow. We have already predicted in our business intelligence trends article the importance and implementation of the cloud in companies like Alibaba, Amazon, Google and Microsoft.

The significance of the cloud is increasing exponentially. Gartner forecasts that the cloud services market will grow 17.3% in 2019 ($206.2 billion) and by 2022, 90% of organizations will be using cloud services.

Considering all the potential and development cloud computing has undergone in recent years, there are also many challenges businesses are facing. In this article, we have gathered 10 most prominent challenges of cloud computing that will deliver new insights and aspects in the cloud market. But first, lets start with a simple explanation of the general characteristics and basic definitions.

Cloud computing is the delivery of various hardware and software services over the internet, through a network of remote servers. These remote servers are busy storing, managing, and processing data that enables users to expand or upgrade their existing infrastructure.

The capabilities and breadth of the cloud are enormous. The IT industry broke it into three categories to help better define use cases.

All of this is a deviation from traditional on-premise computing which is done via a local server or personal computer. These traditional methods are increasingly being left behind. In fact, the IDGs recentlypublishedEnterprise Cloud Computing Survey (2018) found that 73% of organizations have at least one application, or a portion of their computing infrastructure already in the cloud 17% plan to do so within the next 12 months.

It is evident that the cloud is expanding. Since we live in a digital age, where data discovery and big data simply surpass the traditional storage and manual implementation and manipulation of business information, companies are searching for the best possible solution of handling data. Traditional spreadsheets no longer serve their purpose, there is just too much data to store, manage and analyze. Be it in the form of online BI tools, or an online data visualization system, a company must address where and how to store its data. Even the most traditional sectors have to adjust:

In an effort to do everything from offer better in-store customer service to fully leverage advances in manufacturing, companies from even most traditional and change-resistant sectors are seeing the writing on the wall: Cloud technology strategies cut cost and risk. Lalit Bhatt, Project Leader at Maruti Techlabs.

Though the opportunities are great, this explosion hasnt come without issues in cloud computing. We discussed already some of these cloud computing challenges when comparing cloud vs on premise BI strategies. Now lets go over more of those challenges organizations are facing, and how they are being addressed.

In January 2018, RightScale conducted its annualState of the Cloud Surveyon the latest cloud trends. They questioned 997 technical professionals across a broad cross-section of organizations about their adoption of cloud infrastructure. Their findings were insightful, especially in regards to current cloud computing challenges. To answer the main question of what are the challenges for cloud computing, below we have expanded upon some of their findings and provided additional cloud computing problemsthat businesses may need to address.

Security risks of cloud computing have become the top concern in 2018 as 77% of respondents stated in the referred survey. For the longest time, the lack of resources/expertise was the number one voiced cloud challenge. In 2018 however, security inched ahead.

We already mentioned the hot debate around data security in our business intelligence trends 2019 article, andsecurity has indeed been a primary, and valid, concern from the start of cloud computing technology: you are unable to see the exact location where your data is stored or being processed. This increases the cloud computing risks that can arise during the implementation or management of the cloud. Headlines highlighting data breaches, compromised credentials, and broken authentication, hacked interfaces and APIs, account hijacking havent helped alleviate concerns. All of this makes trusting sensitive and proprietary data to a third party hard to stomach for some and, indeed, highlighting the challenges of cloud computing. Luckily as cloud providers and users, mature security capabilities are constantly improving. To ensure your organizations privacy and security is intact, verify the SaaS provider has secure user identity management, authentication, and access control mechanisms in place. Also, check which database privacy and security laws they are subject to.

While you are auditing a providers security and privacy laws, make sure to also confirm the third biggest issue is taken care of: compliance. Your organization needs to be able to comply with regulations and standards, no matter where your data is stored. Speaking of storage, also ensure the provider has strict data recovery policies in place.

The security risks of cloud computing have become a reality for every organization, be it small or large. Thats why it is important to implement a secure BI cloud tool that can leverage proper security measures.

The next part of our cloud computing risks list involves costs. For the most part cloud computing can save businesses money. In the cloud, an organization can easily ramp up its processing capabilities without making large investments in new hardware. Businesses can instead access extra processing through pay-as-you-go models from public cloud providers. However, the on-demand and scalable nature of cloud computing services make it sometimes difficult to define and predict quantities and costs.

Luckily there are several ways tokeep cloud costs in check, for example, optimizing costs by conducting better financial analytics and reporting, automating policies for governance, or keeping the management reporting practice on course, so that these issues in cloud computing could be decreased.

One of the cloud challenges companies and enterprises are facing today is lack of resources and/or expertise. Organizations are increasingly placing more workloads in the cloud while cloud technologies continue to rapidly advance. Due to these factors, organizations are having a tough time keeping up with the tools. Also, the need for expertise continues to grow. These challenges can be minimized through additional training of IT and development staff. A strong CIO championing cloud adoption also helps. As Cloud EngineerDrew Firmentputs it:

The success of cloud adoption and migrations comes down to your peopleand the investments you make in a talent transformation program. Until you focus on the #1 bottleneck to the flow of cloud adoption, improvements made anywhere else are an illusion.

SME (small and medium-sized) organizations may find adding cloud specialists to their IT teams to be prohibitively costly. Luckily, many common tasks performed by these specialists can be automated. To this end companies are turning to DevOps tools, like Chef and Puppet, to perform tasks like monitoring usage patterns of resources and automated backups at predefined time periods. These tools also help optimize the cloud for cost, governance, and security.

There are many challenges facing cloud computing and governance/control is in place number 4. Proper IT governance should ensure IT assets are implemented and used according to agreed-upon policies and procedures; ensure that these assets are properly controlled and maintained, and ensure that these assets are supporting your organizations strategy and business goals.

In todays cloud-based world, IT does not always have full control over the provisioning, de-provisioning, and operations of infrastructure. This has increased the difficulty for IT to provide the governance, compliance, risks and data quality management required. To mitigate the various risks and uncertainties in transitioning to the cloud, IT must adapt its traditional IT governance and control processes to include the cloud. To this effect, the role of central IT teams in the cloud has been evolving over the last few years. Along with business units, central IT is increasingly playing a role in selecting, brokering, and governing cloud services. On top of this third-party cloud computing/management providers are progressively providing governance support and best practices.

One of the risks of cloud computing is facing today is compliance. That is an issue for anyone using backup services or cloud storage. Every time a company moves data from the internal storage to a cloud, it is faced with being compliant with industry regulations and laws. For example, healthcare organizations in the USA have to comply with HIPAA (Health Insurance Portability and AccountabilityActof 1996), public retail companies have to comply with SOX (Sarbanes-Oxley Act of 2002) and PCI DSS (Payment Card Industry Data Security Standard).

Depending on the industry and requirements, every organization must ensure these standards are respected and carried out.

This is one of the many challenges facing cloud computing, and although the procedure can take a certain amount of time, the data must be properly stored.

Cloud customers need to look for vendors that can provide compliance and check if they are regulated by the standards they need. Some vendors offer certified compliance, but in some cases, additional input is needed on both sides to ensure proper compliance regulations.

Challenges facing cloud computing havent just been concentrated in one, single cloud.

The state of multi-cloud has grown exponentially in recent years. Companies are shifting or combining public and private clouds and, as mentioned earlier, tech giants like Alibaba and Amazon are leading the way.

In the referred survey, 81 percent of enterprises have a multi-cloud strategy. Enterprises with a hybrid strategy (combining public and private clouds) fell from 58 percent in 2017 to 51 percent in 2018, while organizations with a strategy of multiple public clouds or multiple private clouds grew slightly.

While organizations leverage an average of almost 5 clouds, it is evident that the use of the cloud will continue to grow. Thats why it is important to answer the main questions organizations are facing today: what are the challenges for cloud computing and how to overcome them?

When a business moves to the cloud it becomes dependent on the service providers. The next prominent challenges of moving to cloud computing expand on this partnership. Nevertheless, this partnership often provides businesses with innovative technologies they wouldnt otherwise be able to access. On the other hand, the performance of the organizations BI and other cloud-based systems is also tied to the performance of the cloud provider when it falters. When your provider is down, you are also down.

This isnt uncommon, over the past couple of years all the big cloud players have experienced outages. Make sure your provider has the right processes in place and that they will alert you if there is ever an issue.

For the data-driven decision making process, real-time data for organizations is imperative. Being able to access data that is stored on the cloud in real-time is one of the imperative solutions an organization has to consider while selecting the right partner.

With an inherent lack of control that comes with cloud computing, companies may run into real-time monitoring issues. Make sure your SaaS provider has real-time monitoring policies in place to help mitigate these issues.

Although building a private cloud isnt a top priority for many organizations, for those who are likely to implement such a solution, it quickly becomes one of the main challenges facing cloud computing private solutions should be carefully addressed.

Creating an internal or private cloud will cause a significant benefit: having all the data in-house. But IT managers and departments will need to face building and gluing it all together by themselves, which can cause one of the challenges of moving to cloud computing extremely difficult.

It is important to keep in mind also the steps that are needed to ensure the smooth operation of the cloud:

As this article stated: the cloud software layer has to grab an IP address, set up a virtual local area network (VLAN), put the server in the load balancing queue, put the server in the firewall rule set for the IP address, load the correct version of RHEL, patch the server software when needed and place the server into the nightly backup queue.

That being said, it is obvious that developing a private cloud is no easy task, but nevertheless, some organizations still manage and plan to do so in the next years.

Most organizations did not have a robust cloud adoption strategy in place when they started to move to the cloud. Instead, ad-hoc strategies sprouted, fueled by several components. One of them was the speed of cloud adoption. Another one was the staggered expiration of data center contracts/equipment, which led to intermittent cloud migration. Finally, there also were individual development teams using the public cloud for specific applications or projects. These bootstrap environments have fostered full integration and maturation issues including:

In fact, a recentsurveyby IDC of 6,159 executives found that just3% of respondents define their cloud strategies as optimized. Luckily, centralized IT, strong governance and control policies, and some heavy lifting can get usage, adoption, and cloud computing strategies inline.

Nearly half of the decision makers believe that their IT workforce is not completely prepared to address the cloud computing industry challenges and managing their cloud resources over the next 5 years. Since businesses are adopting the cloud strategy more often than ever, it is eminent that the workforce should keep up and carefully address the potential issues.

One of the main cloud computing industry challenges in recent years concentrates on migration. This is a process of moving an application to a cloud. An although moving a new application is a straightforward process, when it comes to moving an existing application to a cloud environment, many cloud challenges arise.

A recent survey conducted by Velostrata showed that over 95% of companies are currently migrating their applications to the cloud, and over half of them find it more difficult than expected projects are over budget and deadline.

What are the challenges faced during storing data in the cloud? Most commonly cited were:

In another survey, although not that recent, but a picturesque perception of the migration to the cloud; IT professionals stated they would rather get a root canal, dig a ditch, or do their own taxes than address challenges in cloud computing regarding the deployment process.

It is no secret; cloud computing is revolutionizing the IT industry. It is also shaking up the business intelligence (BI) landscape, and well, pretty everything else it touches. As thecloud adoption exponentially grows, businesses of all sizes are realizing the benefits. For startups and small to medium-sized businesses (SMEs), that cant afford costly server maintenance, but also may have to scale overnight, the benefits of utilizing the cloud are especially great.

While cloud computing challenges do exist, if properly addressed, these 10 issues dont mean your IT roadmap has to remain anchored on-premise. Business intelligence (BI) and the cloud are an ideal match, as the first oneprovides the right information to the right people while the latteris an agile way to access BI applications.

So, what are the challenges faced during storing data in the cloud and how to overcome them?

To make the best out ofit and overcome issues, you should takea strategic iterative approach to implementation, explore hybrid cloud solutions, involve business and IT teams, invest in a CIO, and choosethe right BISaaS partner. All this will ensure that the benefits ofcloud business intelligence will far outweigh thechallenges.

Clearly, organizations have some demanding work ahead of them, especially since the adoption of the cloud is becoming a business standard that will grow exponentially. Cloud is not just an idea to implement overnight, but a strategic approach, management details, and professionals involvement can help reduce potential risks, costs, and flaws in the implementation process. The future of cloud lies upon introducing industry standards, that will help in addressing regulatory, management and technological matters.

To summarize, here are the top challenges in cloud computing:

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Cloud Computing Risks, Challenges & Problems Businesses ...