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Machine Learning Software Market Increasing Demand with Leading Player, Comprehensive Analysis, Forecast to 2026 – News Times

March 9, 2020 | Author: admin

The report on the Machine Learning Software Market is a compilation of intelligent, broad research studies that will help players and stakeholders to make informed business decisions in future. It offers specific and reliable recommendations for players to better tackle challenges in the Machine Learning Software market. Furthermore, it comes out as a powerful resource providing up to date and verified information and data on various aspects of the Machine Learning Software market. Readers will be able to gain deeper understanding of the competitive landscape and its future scenarios, crucial dynamics, and leading segments of the Machine Learning Software market. Buyers of the report will have access to accurate PESTLE, SWOT, and other types of analysis on the Machine Learning Software market.

The Global Machine Learning Software Market is growing at a faster pace with substantial growth rates over the last few years and is estimated that the market will grow significantly in the forecasted period i.e. 2019 to 2026.

Machine Learning Software Market: A Competitive Perspective

Competition is a major subject in any market research analysis. With the help of the competitive analysis provided in the report, players can easily study key strategies adopted by leading players of the Machine Learning Software market. They will also be able to plan counterstrategies to gain a competitive advantage in the Machine Learning Software market. Major as well as emerging players of the Machine Learning Software market are closely studied taking into consideration their market share, production, revenue, sales growth, gross margin, product portfolio, and other significant factors. This will help players to become familiar with the moves of their toughest competitors in the Machine Learning Software market.

Machine Learning Software Market: Drivers and Limitations

The report section explains the various drivers and controls that have shaped the global market. The detailed analysis of many market drivers enables readers to get a clear overview of the market, including the market environment, government policy, product innovation, development and market risks.

The research report also identifies the creative opportunities, challenges, and challenges of the Machine Learning Software market. The framework of the information will help the reader identify and plan strategies for the potential. Our obstacles, challenges and market challenges also help readers understand how the company can prevent this.

Machine Learning Software Market: Segment Analysis

The segmental analysis section of the report includes a thorough research study on key type and application segments of the Machine Learning Software market. All of the segments considered for the study are analyzed in quite some detail on the basis of market share, growth rate, recent developments, technology, and other critical factors. The segmental analysis provided in the report will help players to identify high-growth segments of the Machine Learning Software market and clearly understand their growth journey.

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Machine Learning Software Market: Regional Analysis

This section of the report contains detailed information on the market in different regions. Each region offers a different market size because each state has different government policies and other factors. The regions included in the report are North America, Europe, Asia Pacific, the Middle East and Africa. Information about the different regions helps the reader to better understand the global market.

Table of Content

1 Introduction of Machine Learning Software Market

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

2 Executive Summary

3 Research Methodology of Market Research Intellect

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

4 Machine Learning Software 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 Machine Learning Software Market , By Deployment Model

5.1 Overview

6 Machine Learning Software Market , By Solution

6.1 Overview

7 Machine Learning Software Market , By Vertical

7.1 Overview

8 Machine Learning Software 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 Machine Learning Software 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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About Us:

Market Research Intellect provides syndicated and customized research reports to clients from various industries and organizations with the aim of delivering functional expertise. We provide reports for all industries including Energy, Technology, Manufacturing and Construction, Chemicals and Materials, Food and Beverage and more. These reports deliver an in-depth study of the market with industry analysis, market value for regions and countries and trends that are pertinent to the industry.

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Email: [emailprotected]

TAGS: Machine Learning Software Market Size, Machine Learning Software Market Growth, Machine Learning Software Market Forecast, Machine Learning Software Market Analysis, Machine Learning Software Market Trends, Machine Learning Software Market

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3 important trends in AI/ML you might be missing – VentureBeat

March 9, 2020 | Author: admin

According to a Gartner survey, 48% of global CIOs will deploy AI by the end of 2020. However, despite all the optimism around AI and ML, I continue to be a little skeptical. In the near future, I dont foresee any real inventions that will lead to seismic shifts in productivity and the standard of living. Businesses waiting for major disruption in the AI/ML landscape will miss the smaller developments.

Here are some trends that may be going unnoticed at the moment but will have big long-term impacts:

Gone are the days when on-premises versus cloud was a hot topic of debate for enterprises. Today, even conservative organizations are talking cloud and open source. No wonder cloud platforms are revamping their offerings to include AI/ML services.

With ML solutions becoming more demanding in nature, the number of CPUs and RAM are no longer the only way to speed up or scale. More algorithms are being optimized for specific hardware than ever before be it GPUs, TPUs, or Wafer Scale Engines. This shift towards more specialized hardware to solve AI/ML problems will accelerate. Organizations will limit their use of CPUs to solve only the most basic problems. The risk of being obsolete will render generic compute infrastructure for ML/AI unviable. Thats reason enough for organizations to switch to cloud platforms.

The increase in specialized chips and hardware will also lead to incremental algorithm improvements leveraging the hardware. While new hardware/chips may allow use of AI/ML solutions that were earlier considered slow/impossible, a lot of the open-source tooling that currently powers the generic hardware needs to be rewritten to benefit from the newer chips. Recent examples of algorithm improvements include Sidewaysto speed up DL training by parallelizing the training steps, andReformerto optimize the use of memory and compute power.

I also foresee a gradual shift in the focus on data privacy towards privacy implications on ML models. A lot of emphasis has been placed on how and what data we gather and how we use it. But ML models are not true black boxes. It is possible to infer the model inputs based on outputs over time. This leads to privacy leakage. Challenges in data and model privacy will force organizations to embrace federated learningsolutions. Last year, Google releasedTensorFlow Privacy, a framework that works on the principle of differential privacy and the addition of noise to obscure inputs. With federated learning, a users data never leaves their device/machine. These machine learning models are smart enough and have a small enough memory footprint to run on smartphones and learn from the data locally.

Usually, the basis for asking for a users data was to personalize their individual experience. For example, Google Mail uses the individual users typing behavior to provide autosuggest. What about data/models that will help improve the experience not just for that individual but for a wider group of people? Would people be willing to share their trained model (not data) to benefit others? There is an interesting business opportunity here: paying users for model parameters that come from training on the data on their local device and using their local computing power to train models (for example, on their phone when it is relatively idle).

Currently, organizations are struggling to productionize models for scalability and reliability. The people who are writing the models are not necessarily experts on how to deploy them with model safety, security, and performance in mind. Once machine learning models become an integral part of mainstream and critical applications, this will inevitably lead to attacks on models similar to the denial-of-service attacks mainstream apps currently face. Weve already seen some low-tech examples of what this could look like: making a Tesla speed up instead of slow down, switch lanes, abruptly stop, or turning on wipers without proper triggers. Imagine the impacts such attacks could have on financial systems, healthcare equipment, etc. that rely heavily on AI/ML?

Currently, adversarial attacks are limited to academia to understand the implications of models better. But in the not too distant future, attacks on models will be for profit driven by your competitors who want to show they are somehow better, or by malicious hackers who may hold you to ransom. For example, new cybersecurity tools today rely on AI/ML to identify threats like network intrusions and viruses. What if I am able to trigger fake threats? What would be the costs associated with identifying real-vs-fake alerts?

To counter such threats, organizations need to put more emphasis on model verification to ensure robustness. Some organizations are already using adversarial networks to test deep neural networks. Today, we hire external experts to audit network security, physical security, etc. Similarly, we will see the emergence of a new market for model testing and model security experts, who will test, certify, and maybe take on some liability of model failure.

Organizations aspiring to drive value through their AI investments need to revisit the implications on their data pipelines. The trends Ive outlined above underscore the need for organizations to implement strong governance around their AI/ML solutions in production. Its too risky to assume your AI/ML models are robust, especially when theyre left to the mercy of platform providers. Therefore, the need of the hour is to have in-house experts who understand why models work or dont work. And thats one trend thats here to stay.

Sudharsan Rangarajan is Vice President of Engineering at Publicis Sapient.

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Supermicro’s data centre on a pole sends IoT processing to the Edge – Data Economy

March 9, 2020 | Author: admin

Here are the five things you need to know this morning, March 05, 2020, from around the world directly to you.

Domo announcesCanadian data centre

Domo (Nasdaq: DOMO) has announced that it has expanded itsinfrastructure in North America and is now live with a new data centre runningon Amazon Web Services (AWS) in Canada.

This expansion will provide regional support and datagovernance for customers in that region as well as global customers withworldwide operations, according to the company.

The data centre is the companys latest move establishingits commitment to serving Canadian customers from coast to coast and inproviding localized support to its growing base of more than 1,900 worldwidecustomers.

Our customers trust us with one of their most valuableassets in the cloud era: their data, said Daren Thayne, chief technologyofficer at Domo.

Our latest data centre expansion ensures customers doingbusiness from Canada can continue to move at record speed, knowing their datais being managed with the unique security, privacy and compliance requirementsof that region.

Keysource appointedto NEUPC Framework

Data centre firm Keysource has been appointed to the NorthEastern Universities Purchasing Consortium (NEUPC) Framework for the provisionof Data Centre Management equipment and Infrastructure for a further fouryears.

NEUPC is one of six UK Higher Education purchasing consortiaestablished to deliver and manage a range of collaborative framework agreementswithin the higher education sector.

NEUPCs new Data Centre Management Framework offers a broadscope of equipment, infrastructure and consultancy.

We have a long pedigree of providing high-performance data centre facilities to the education sector and our clients include University of Leicester, University of Exeter and Bristol University, said Richard Clifford, Senior Consultant and Head of Innovation at Keysource.

This is our tenth year of working with NEUPC as one of their trusted data centre companies that will support the Education sector in the UK.

CloudFest 2020 cancelleddue to Coronavirus

As the Covid-19 story develops, it is not only threateningglobal health, but seriously disrupting everyday operations.

Due to public health concerns related to the coronavirusoutbreak, the organisers of CloudFest announced it has cancelled CloudFest2020.

The annual cloud, hosting and data centre industry event wasscheduled for March 14 19 in Europa Park in Rust, Germany.

The health and safety of our attendees, partners,presenters, and colleagues is of the utmost importance to us, stated theCloudFest Team.

We were forced to consider the growing risk of exposure,especially in the German state of Baden-Wrttemberg, where our event islocated.

The unclear infection path, as well as the risk ofquarantine orders lasting several weeks on short notice, could not be ignored.

With over 7,000 people from the cloud community expected togather from almost every continent, the risk of inadvertently spreading thevirus was just too high.

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Healthcare Industryplans to ramp up Hybrid cloud adoption

Healthcare organisations around the globe are under pressureto drive digital transformation to meet increasing patient care demands.

Nutanix (NASDAQ: NTNX) has announced the healthcare industryfindings of its second annual Enterprise Cloud Index Report, measuringhealthcare organisations plans for adopting private, hybrid and public clouds.

Overall 2019 ECI data found digital transformationsignificantly impacted cloud implementation across various industry verticals,and healthcare organisations were no different with 68% citing this trend.

In line with top healthcare IT trends, healthcare companiesranked personalised healthcare (52%) and AI assistants (44%) as positivelyimpacting their cloud adoption.

Lume raises $4.3 millionto expand cloud and edge data centre offerings

Lume has announced that it has secured a $4.3 millioninvestment to support its innovative cloud offerings and bring the companysCloud Anyware and edge data centre solutions to new markets and customers.

The funding round was led by BaseCamp Capital LLC, aColorado-based private equity group.

Lume also announced that Octavio Morales has joined the companysBoard of Directors. Morales was one of the original co-founders of TierPointand served as the companys CEO until its acquisition in 2012.

He has over 30 years of experience and expertise within the industry that will help guide the companys growth strategy.

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Amazon, Microsoft cloud-computing can weather a recession and coronavirus, analysts say – The Columbian

March 9, 2020 | Author: admin

Cloud computing is a fast-growing business at both Redmond-based Microsoft and Seattle-based Amazon, where it balances the thinner profit margins of the retail side of the company. Cloud competitors including Google and IBM also have major engineering offices in the region.

In the quarter ended Dec. 31, Microsoft reported sales of $11.9 billion in the business segment that includes its Azure cloud computing business, lumped in with its traditional server software and business consulting services. The company said Azure sales increased 62% from a year earlier, though it doesnt disclose the revenue figure. Amazon Web Services (AWS) reported revenue of nearly $10 billion in the same period, up 34%.

Cloud services companies allow customers to rent remote computing power, scaling up and down usage, and associated costs, as needed. The cloud has steadily replaced the old model of organizations building and owning their own servers and data centers, which takes time, requires large up-front capital outlays as well as ongoing maintenance costs, and leaves them with excess computing capacity that goes unused except during brief periods of peak demand.

A business running on the cloud that experiences a spike in customer traffic to its website can immediately call on servers in a global network of Amazon or Microsoft data centers to handle the load. When the traffic subsides, they can turn off those services. Likewise, if a company needs to perform a complex analysis or test a machine learning algorithm, it can rent nearly limitless computing power from a cloud provider for a few hours, rather than incurring the cost of owning it.

In practice, businesses tend to scale up their cloud usage but dont often scale it back down, said Quinn, whose firm helps companies manage their AWS bills and has customers that spend in aggregate about $1 billion a year on Amazons cloud.

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Is Cloud Hosting The Best Hosting Option For Your Website? – Analytics Insight

March 9, 2020 | Author: admin

Every website needs a web hosting service. There simply isnt any way that a website can exist without the server that hosts it. However, as is the nature of technology, there will always be attempts to create better, more efficient ways of doing things. Remember when virtual machines were created in order for computer hardware to be used more efficiently? That kind of change is constantly happening, and while not every attempt becomes disruptive enough to replace its predecessor, each attempt is a step in the right direction. Cloud hosting is a good example of such an attempt. It can pave the way for a more efficient use of physical servers, after all.

But before adopting a particular method, technology, or trend, you first need to determine if its going to be beneficial to your objectives and goals. And when theres a significant amount of money involved, you wouldnt want to spend it just on a trial-and-error session.

So, you resort to the next best thing gather information from other people whove had experience with cloud hosting. So, what makes cloud hosting so special? In order to thoroughly understand this new technology, we first have to look at how traditional web hosting functions.

Web hosting is a service that allows persons and companies to publish websites on the internet. A web hosting service provider provides the resources necessary for a website to function. These websites are saved on physical servers, which are what contain the resources necessary for a website to function. When users visit your website, they first type your web address on their browser, which will prompt their computer to connect to the server where your website is stored. This is when your website becomes viewable by the user.

There are three types of web hosting: Shared multiple websites depend on a single server. As you might imagine, this limits website performance and the failure of a single server could mean downtime for all the websites stored on that server. This, however, is still a valid option for websites that do not require a lot of resources to handle traffic because they arent as costly as other types of web hosting. There is also an innate security risk in a shared web hosting.

Dedicated dedicated servers provide the best performance and the highest degree of customizability among all types of web hosting. This is where a single server is dedicated to a single website. This also means that the very best of support would be made available to the website. This is an ideal option for websites that require a lot of performance to handle massive amounts of web traffic.

VPS a virtual private server is a virtual machine that caters to the individual needs of a user just as a separate physical computer that is dedicated to a particular user. This means that resources are pre-allocated to each website that is connected to the server to prevent websites from pulling resources from one another. Several virtual private servers can be maintained on a single physical server, which means that if that single physical server fails, all the websites that rely on that server experience downtime.

Cloud hosting, much like many other cloud-based services, is a type of hosting service that makes use of parts of several servers to support a single websites resource requirements and to ensure maximum website uptime. Because a website is supported by multiple servers in a server cluster, it will have the necessary resources needed for it to remain functional even when a single server in that cluster fails. So, in essence, the resources needed can simply be drawn from a different server in the event that one of the multiple servers fails.

So, yes. Cloud hosting does sound similar to a virtual private server, but there are a few differences that set them apart from each other.

The primary difference between cloud hosting and VPS is their approach and scalability. Remember that cloud hosting servers make use of server clusters, where parts of multiple servers support a single website. This means that users have access to near-unlimited resources needed to run their website and that these resources can easily be adjusted to the needs of the website. This is especially valuable for websites that experience spikes in traffic on a regular basis.

On the other hand, VPS runs multiple instances of servers on a single physical server. This means that while the websites hosted by the physical do not battle over resources, if that single physical server fails, all the websites that are linked to that server would experience downtime.

Its also significantly more difficult to scale with a VPS server because the resources allocated to each website are predetermined, which means that while these servers are going to be able to perform much better than shared servers, there is still a chance that your websites load could exceed the amount of resources allocated for your website. Despite this, VPS hosting tends to cost less than cloud hosting.

While hosting your website on the cloud does sound like the future, it isnt as tried and tested as traditional web hosting options. Whether youre willing to take a risk or not depends on what you use your website for. If you use your website as a means of earning money, then betting on something that isnt tried and tested could prove to be catastrophic if it fails.

Otherwise, by all means, opt for a cloud hosting service.

What truly minimizes the risk here is the fact that traditional web hosting methods have been around for as long as anyone can remember. This means that there is a wealth of information that can help guide users toward good service providers. A good source of this information can be found in web hosting review sites. For example, MangoMatter has some great hosting comparisons that provide readers with an in-depth comparison between the web hosting options that are available on the market.

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Customers are now more discerning about moving to the public cloud, says Pulsants Rob Coupland – NS Tech

March 9, 2020 | Author: admin

Pulsant is a data centre and cloud infrastructure business, that focuses on the UK mid-market it aims to help organisations that are going through a transformation, particularly from an on-premises environment to a cloud environment. The company operates 10 data centres that cover the UK stretching from London in the south to Edinburgh in the North, and it counts the likes of the NHS, Newcastle FC and Kwik Fit as its customers.

A huge part of the companys business is in managed services. According to CEO Rob Coupland, 85 per cent of the companys revenue comes from co-location services, managed network services and private cloud. The latter two make up nearly two-thirds of the turnover for the business.

We provide IT infrastructure services, so thats things like private cloud, network infrastructure, or just the data centre but what we wrap around that is other services like security for data centre, networks and cloud platforms, storage, back-up, disaster recovery and other services, he says.

The company offers managed services for cloud platforms including Microsoft Azure, Amazon Web Services and Google Cloud Platform. But unlike other IT infrastructure companies, managed services is not something new for the company.

What makes us different to other data centre companies is that when we started we offered managed services weve always been a managed services provider, starting with managed hosting about a decade ago, he says.

According to Coupland, demand has switched from the managed hosting offering to the multi-tenant private cloud offering, but he says that more surprisingly, a big part of the business is still in co-location services.

Were still seeing a strong demand for co-location and perhaps even more so than previous years because businesses 18 months to two years ago were all thinking of moving to the public cloud, but now theyre more selective about where they put their workloads, he says.

The companys customer base mainly consists of UK regional businesses, for whom many still deliver their IT services in a traditional way. But as digital transformation has quickly caught their attention, these businesses are looking for some support particularly as they dont have the same resources as big businesses in their IT teams.

This is where they look for providers like us to help with their journey and their aspiration is often expressed as moving everything to the cloud. When you dig deeper, theyre looking for flexibility and the ability to access apps and systems from different locations, says Coupland.

In addition, these mid-market enterprises are particularly concerned about cost management, especially as they still use many traditional IT systems and services, and this is what attracts them to the idea of the private cloud as they see it as a way to not have to maintain their own infrastructure, and give them the flexibility of cloud computing, while managing costs.

So even though you have these big cloud companies attracting the headlines, regional businesses are looking for regional partners to help them through this journey, he says.

Amazon Web Services CEO Andy Jassy told delegates at AWS:reInvent last year that only 3 per cent of all IT workloads were in the cloud and Coupland believes that this illustrates how much attention big business transformations are getting as smaller enterprises are not necessarily shifting all of their workloads into the cloud just yet.

There are a lot of workloads that are on servers in data rooms inside office buildings, and so often people talk about public clouds future, but actually a lot of this is going to be about getting those servers and platforms into properly managed databases so they can secure a service level around them, and then theres an awful lot which will kind of be more of a gradual migration to a combination of public and private cloud, he states.

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Former Mac head Jean-Louis Gasse says all Macs could today be ARM powered – 9to5Mac

March 9, 2020 | Author: admin

Former senior Apple exec Jean-Louis Gasse, who once held the role of head of Macintosh development, says that it would be perfectly viable for the entire Mac range to be powered by ARM chips even the Mac Pro. This reverses a view he held last year when he called the idea a fantasy.

He said that while one of the two problems he discussed last year remains a huge challenge for Apple, power is no longer an issue

Jean-Louis Gasse last year said that having considered both sides of the argument, hed concluded that the switch from Intel to ARM-based chips simply wasnt practical.

After last weeks thought experiment on the Macs future, I realized that leaving the x86 processor family made little practical sense. A pleasing fantasy, perhaps, but too complicated in practice.

One of the reasons for that is he didnt believe an ARM-based CPU could ever be powerful enough for the Mac Pro.

The Pro is a monstrously powered machine that costs tens of thousands of dollars and is designed for a (relatively) small audience of content creator professionals and other high-end technical users running fluidics dilutions and the demanding calculations involved in machine-learning applications. Will these users be satisfied with a lesser CPU in the name of Mac line cohesion?

In a blog post yesterday, however, he said he was wrong.

Ampere designs and sells high-powered ARM chips that compete with the Xeon processors used in cloud servers [] Ampere shows us that the ARM architecture can yield the class of chips a Mac Pro would need. And, as it happens, the chips are manufactured by TSMC, the same company that makes Apples Axx processors.

There does, however, remain one further problem: what he describes as the Mac fork: until the transition was complete, youd have one set of Macs running on Intel chips, and another running on ARM-based chips, requiring two different versions of macOS.

If (or, more likely, when) the Mac switches to Axx chips, the change wont be instantaneous. Some Macs will become powered by Apples home-grown CPU chips, others, like the Mac Pro, will remain on x86 processors. And thus well have a fork of macOS.

And as soon as the first ARM-powered Macs are announced, anyone considering an Intel-powered one would know that they were essentially buying tech which wont run the latest version of macOS because the most modern version would be the one running on ARM chips. Is that upheaval worthwhile, he asks, at a time when the Mac line only accounts for 8% of Apples revenue?

Jean-Louis Gasse says he has no idea what Apples decision will be.

My personal view is that hes of course right about the Mac fork problem, but as Ive argued previously, history proves that Apple is willing to bite the bullet here.

Apple has done this not just once, but twice. First in the 1994 switch from theMotorola 68000 architecture of the original Macintosh range to PowerPC, and again in the 2006 move from PPC to Intel. It eased the transitions witha68000 emulatorandRosetta.

Thats not to say that such transitions arent painful; they are. Horribly so for a while. Those of us whove lived through both moves can still recall some of the frustrations to this day.

But in both cases, we got over it, and the end result was worth it. The same will be true again.

Ming-Chi Kuo has suggested that Apple will release its first ARM-powered Mac at some point next year.

Photo: Alison van Diggelen/Fresh Dialogues

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AWS to double sales droids as Google, Microsoft’s growing clouds threaten to gobble larger slices of Bezos’ pie – The Register

March 9, 2020 | Author: admin

Amazon Web Services plans to double its sales staffing numbers this year in the face of mounting competition and slowing growth.

The hiring spree, reportedly announced in a sales meeting in Chicago in January, will bring in security, AI, and data analytics specialists to help AWS's sales staff answer technical questions from customers and sell more services.

The exact size of AWS's sales team is a closely guarded secret, even to its own staff. The cloud biz's chief suit, Andy Jassy, has said the number was in the "thousands" in a 2016 interview, and it has likely grown considerably since then.

AWS dominates cloud computing, munching 32.3 per cent of the market, according to Canalys. That's well ahead of Microsoft's 16.9 per cent and Google's 5.8 per cent.

But the Jeff-Bezos-run titan's enormous growth has begun to slow recently as other providers catch up. Of the big four cloud providers, Google grew the most last year, swelling 87.8 per cent, Microsoft came in second, with 64 per cent growth. Alibaba was close behind with 63.8 per cent. But AWS's growth, at 36 per cent, was half that of its nearest rival.

AWS still posted the biggest revenue increase in absolute terms with $9.2bn compared with Microsoft's $7.1bn but many saw the pair's recent financial results as an early sign that rival services were beginning to catch up with Bezos' behemoth.

Google Cloud's chief exec, Thomas Kurian, recently committed to tripling the size of his sales team as part of a wider restructure. The former Oracle exec has pushed for more services to woo enterprise customers, and is looking to expand Google's reseller network.

Last week, the company inked a deal with LA-based service provider SADA to resell $500m in Google Cloud services over the next three years. Google plans to invest $10bn into data centres and offices across the US this year.

Arch-rival Microsoft has shifted its focus to aggressively target Amazon's cloud clients. The strategy is working, according to some analysts. Last year, Redmond surprised everyone by beating AWS to win the US Department of Defense's $10bn decade-long JEDI IT supply deal, which seeks to switch the the US's military data over to the cloud. AWS appealed the decision and was granted a pause on the contract until the courts came to a decision on whether or not it was awarded fairly.

The new hires make up the first sales shakeup at AWS in several years. Up to now, the cloud giant has focused on selling basic building block services, such as its cloud servers and storage. But the company is now shifting focus to finished products, like Pinpoint, which helps manage marketing campaigns, and Fraud Detector, a service the company is currently testing that detects online fraud. Other AWS services include Outposts and Local Zones.

Amazon recently reported revenues of $280.5bn up 20 per cent on the previous year. About a tenth of this came from AWS, which generated $35.03bn.

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What are the Benefits of Cloud-Based Security Systems for Indian Businesses? – India West

March 9, 2020 | Author: admin

India is quickly becoming a global powerhouse in terms of small- to medium-sized businesses. Not only has this trend opened up a plethora of possibilities for individuals from all walks of life, but the presence of the Internet signifies that even startup operations have the ability to reach what can only be called a truly international audience. Still, cyber security is a very real issue in this day and age. One of the latest advancements involves what is known as cloud-based security. How do these systems function and what benefits can they offer your budding enterprise?

All About Redundancy

One of the main principles behind any cloud-based system is that it is located within the "ether" of the digital domain. In other words, there are no physical servers to break down nor hard drives which can become corrupted. This is a massive benefit, as your information will not suddenly be lost in the event of a physical system failure.

This also enables cloud networks to be highly redundant. As information tends to be stored across multiple "hubs", an issue with one will not impact the functionality of another. Businesses no longer need to keep vital information (such as the personal details of a customer or credit card data) within in-house servers. Not only will clients remain safer than in the past, but such an approach can actually be much cheaper when compared to traditional security systems.

Flexible and Adaptable when the Need Arises

Another reason why cloud-based security systems are some of the fastest growing technology trends in 2020 and beyond involves the fact that they are scalable. In other words, they can be upgraded or downgraded as may be needed. Why is this important?

We need to remember that hackers and similar entities are always trying to keep one step ahead of the authorities. This can be extremely dangerous for businesses which store their information with the use of outdated methods. Perhaps the most well-known example can be seen in the 2016 data breach associated with Indian banks. It is estimated that more than 3.2 million debit cards were hacked as a result. This is one of the reasons why many organisations are now migrating into the cloud community.

Let's assume for a moment that a virus is detected within a cloud-based system. As opposed to being forced to update the entire software package, a simple patch can be put in place; helping to secure any sensitive information. In the same respect, the security protocols themselves can be changed in accordance with emerging threats.

You will also be pleased to learn that small businesses throughout India can leverage these very same advantages. Cloud-based security systems are cost-effective solutions which will provide you with a much-needed technological edge. We should still stress that not all providers have been created equally. This is why it is always important to perform a fair amount of research. You will then be able to make an informed choice based around the needs of your organisation.

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What are the Benefits of Cloud-Based Security Systems for Indian Businesses? - India West

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How thousands of servers leverage hybrid IT at Times Internet – ETCIO.com

March 9, 2020 | Author: admin

With more than 550 million monthly active users, 38 brands (TOI, ET, CricBuzz, Gaana, MX Player, Magicbricks, Dineout, and others) under its name, and 5,500 employees, Times Internet Limited (TIL) is Indias largest digital products company.

Spread across multiple geographies, the Times Internet datacentre and infrastructure stack is one of the most complex ones in the market and Sumit Malhotra, CIO of Times Internet is taking a hybrid approach to effectively manage and improve the companys infrastructure.

To manage workloads, self-healing hybrid cloud servers have been deployed, powered by 80,000 CPU cores, running over 12,000 instances that allow any of the groups businesses to scale up and down as needed. The company also works with other cloud partners such as AWS, Google Cloud and Azure for different services.

Using ML for managing workloads For the data centres, a machine learning-backed monitoring system has been developed, which is capable of monitoring 10 lakh metrics per second.

Given the companys wide range of offerings and diverse set of customers, consistency and reliability is expected from the networking infrastructure. For effective performance, a solution for identifying outages in real-time has also been deployed.

Malhotra explained that performing a simple check on a particular website itself is a long process given the complexities involved.

A website sitting on CDN (Content Delivery Network) is mapped to a load balancer and then to the application server. Each application server is itself connected to the different database and cache servers--its a big mesh. Considering we have a lot of interdependencies across, we wanted to make sure that we wanted to identify the problem area very quickly, he said.

After pooling data from different sources (from monitoring system, CDN and logging engine), predictive analysis is done to find out the probable cause of outage.

It helps us cut down and identify the reason for the outage from 2 minutes to 60 minutes to 10 seconds, added Malhotra.

The company also has a centralised system which sends bills to each business heads related to IT infrastructure consumption and requirements. Through this, the various departments within the firm can take an analytical look at utilization of the different IT resources and how much they are spending on what resources, helping them optimize their costs.

Going forward, Malhotra wants to take this system to another level where the respective business heads will also get insights saying that Youll save X amount of money if you follow this recommendation.

There are many and security is on top of the list. This year a lot more of our investment will go into our SoC. Most of our data centres are scalable and we are moving away from transit links to peering links which will help us in reducing cost.

"We are also focusing on optimisation which would enable us to get more of our existing hardware", he added.

Chatbot for IT supportTIL started using chatbot called Toby two years ago and it has been extensively integrated with various systems. It began with a small function where the bot would notify the user (a TIL employee) if a visitor comes and it will ask for his/her approval.

Then the chatbot extended it to various other things like requesting an IT asset, cabs or other services.

The idea is to give people a window where they can get a lot more done in a lesser amount of time so that the manual requests get really low. More than 80% of the workflow today is done through the chatbot.

Malhotras team created bots and integrated with different systems such as ticketing, a CMDB (Configuration Management Database) for all our assets, transport booking, digital management asset. We created APIs which integrated with all these systems and integrated with G-Suite (used by all TIL employees).

Malhotra also plans to integrate Toby with the HR tool; an employee would be able to ask things such as leaves left and much more through chatbot.

We are also going to integrate the chatbot with our SOC operations. For example, we get an antivirus alarm and we are finding an anomaly. So, the user will be notified in real-time, that a problem has been going on and the request has been attended. The idea is to take the feedback from different systems and reach out to people through a single window, says Malhotra.

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How thousands of servers leverage hybrid IT at Times Internet - ETCIO.com

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