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Modernisation of data architecture is key to maximising value across the business.

Dietmar Rietsch, CEO of Pimcore, identifies best practices for organisations to consider when managing modern enterprise data architecture

Time and again, data has been touted as the lifeline that businesses need to grow and, more importantly, differentiate and lead. Data powers decisions about their business operations and helps solve problems, understand customers, evaluate performance, Boost processes, measure improvement, and much more. However, having data is just a good start. Businesses need to manage this data effectively to put it into the right context and figure out the “what, when, who, where, why and how” of a given situation to achieve a specific set of goals. Evidently, a global, on-demand enterprise survives and thrives on an efficient enterprise data architecture that serves as a source of product and service information to address specific business needs.

A highly functional product and master data architecture is vital to accelerate the time-to-market, Boost customer satisfaction, reduce costs, and acquire greater market share. It goes without saying that data architecture modernisation is the true endgame to meet today’s need for speed, flexibility, and innovation. Now living in a data swamp, enterprises must determine whether their legacy data architecture can handle the vast amount of data accumulated and address the current data processing needs. Upgrading their data architecture to Boost agility, enhance customer experience, and scale fast is the best way forward. In doing so, they must follow best practices that are critical to maximising the benefits of data architecture modernisation.

Below are the seven best practices that must be followed for enterprise data architecture modernisation.

1. Build flexible, extensible data schemas

Enterprises gain a potent competitive edge by enhancing their ability to explore data and leverage advanced analytics. To achieve this, they are shifting toward denormalised, mutable data schemas with lesser physical tables for data organisation to maximise performance. Using flexible and extensible data models instead of rigid ones allows for more rapid exploration of structured and unstructured data. It also reduces complexity as data managers do not need to insert abstraction layers, such as additional joins between highly normalised tables, to query relational data.

Data models can become extensible with the help of the data vault 2.0 technique, a prescriptive, industry-standard method of transforming raw data into intelligent, actionable insights. Also, graph databases of NoSQL tap into unstructured data and enable applications requiring massive scalability, real-time capabilities, and access to data layers in AI systems. Besides, analytics can help access stored data while standard interfaces are running. Enterprises can store data using JavaScript Object Notation (JSON), permitting database structural change without affecting the business information model.

2. Focus on domain-based architecture aligned with business needs

Data architects are moving away from clusters of centralised enterprise data lakes to domain-based architectures. Herein, data virtualisation techniques are used throughout enterprises to organise and integrate distributed data assets. The domain-driven approach has been instrumental in meeting specific business requirements to speed up the time to market for new data products and services. For each domain, the product owner and product team can maintain a searchable data catalog, along with providing consumers with documentation (definition, API endpoints, schema, and more) and other metadata. As a bounded context, the domain also empowers users with a data roadmap that covers data, integration, storage, and architectural changes.

This approach significantly reduces the time spent on building new data models in the lake, usually from months to days. Instead of creating a centralised data platform, organisations can deploy logical platforms that are managed within various departments across the organisation. For domain-centric architecture, a data infrastructure as a platform approach leverages standardised tools for the maintenance of data assets to speed up implementation.

3. Eliminate data silos across the organisations

Implications of data silos for the data-driven enterprise are diverse. Due to data silos, business operations and data analytics initiatives are hindered since it is not possible to interpret unstructured, disorganised data. Organisational silos make it difficult for businesses to manage processes and make decisions with accurate information. Removing silos allows businesses to make more informed decisions and use data more effectively. Evidently, a solid enterprise architecture must eliminate silos by conducting an audit of internal systems, culture, and goals.

A crucial part of modernising data architecture involves making internal data accessible to the people who need it when they need it. When disparate repositories hold the same data, data duplicates created make it nearly impossible to determine which data is relevant. In a modern data architecture, silos are broken down, and information is cleansed and validated to ensure that it is accurate and complete. In essence, enterprises must adopt a complete and centralised MDM and PIM to automate the management of all information across diverse channels in a single place and enable the long-term dismantling of data silos.

4. Execute real-time data processing

With the advent of real-time product recommendations, personalised offers, and multiple customer communication channels, the business world is moving away from legacy systems. For real-time data processing, modernising data architecture is a necessary component of the much-needed digital transformation. With a real-time architecture, enterprises can process and analyse data with zero or near-zero latency. As such, they can perform product analytics to track behaviour in digital products and obtain insights into feature use, UX changes, usage, and abandonment.

The deployment of such an architecture starts with the shift from a traditional model to one that is data-driven. To build a resilient and nimble data architecture model that is both future-proof and agile, data architects must integrate newer and better data technologies. Besides, streaming models, or a combination of batch and stream processing, can be deployed to solve multiple business requirements and witness availability and low latency.

5. Decouple data access points

Data today is no longer limited to structured data that can be analysed with traditional tools. As a result of big data and cloud computing, the sheer amount of structured and unstructured data holding vital information for businesses is often difficult to access for various reasons. It implies that the data architecture should be able to handle data from both structured and unstructured sources, both in a structured and an unstructured format. Unless enterprises do so, they miss out on essential information needed to make informed business decisions.

Data can be exposed through APIs so that direct access to view and modify data can be limited and protected, while enabling faster and more current access to standard data sets. Data can be reused among teams easily, accelerating access to and enabling seamless collaboration among analytics teams. By doing this, AI use cases can be developed more efficiently.

6. Consider cloud-based data platforms

Cloud computing is probably the most significant driving force behind a revolutionary new data architecture approach for scaling AI capabilities and tools quickly. The declining costs of cloud computing and the rise of in-memory data tools are allowing enterprises to leverage the most sophisticated advanced analytics. Cloud providers are revolutionising how companies of all sizes source, deploy and run data infrastructure, platforms, and applications at scale. With a cloud-based PIM or MDM, enterprises can take advantage of ready-use and configured solutions, wherein they can seamlessly upload their product data, automate catalog creation, and enrich it diverse marketing campaigns.

With a cloud PIM or MDM, enterprises can eliminate the need for hardware maintenance, application hosting, version updates, and security patches. From the cost perspective, the low cost of subscription of cloud platforms is beneficial for small businesses that can scale their customer base cost-effectively. Besides, cloud-based data platforms also bring a higher level of control over product data and security.

7. Integrate modular, best-of-breed platforms

Businesses often have to move beyond legacy data ecosystems offered by prominent solution vendors to scale applications. Many organisations are moving toward modular data architectures that use the best-of-breed and, frequently, open source components that can be swapped for new technologies as needed without affecting the other parts of the architecture. An enterprise using this method can rapidly deliver new, data-heavy digital services to millions of customers and connect to cloud-based applications at scale. Organisations can also set up an independent data layer that includes commercial databases and open source components.

Data is synchronised with the back-end systems through an enterprise service bus, and business logic is handled by microservices that reside in containers. Aside from simplifying integration between disparate tools and platforms, API-based interfaces decrease the risk of introducing new problems into existing applications and speed time to market. They also make the replacement of individual components easier.

Data architecture modernisation = increased business value

Modernising data architecture allows businesses to realise the full value of their unique data assets, create insights faster through AI-based data engineering, and even unlock the value of legacy data. A modern data architecture permits an organisation’s data to become scalable, accessible, manageable, and analysable with the help of cloud-based services. Furthermore, it ensures compliance with data security and privacy guidelines while enabling data access across the enterprise. Using a modern data approach, organisations can deliver better customer experiences, drive top-line growth, reduce costs, and gain a competitive advantage.

Written by Dietmar Rietsch, CEO of Pimcore

Related:

How to get ahead of the National Data Strategy to drive business value — Toby Balfre, vice-president, field engineering EMEA at Databricks, discusses how organisations can get ahead of the National Data Strategy to drive business value.

A guide to IT governance, risk and compliance — Information Age presents your complete business guide to IT governance, risk and compliance.

Thu, 28 Jul 2022 12:00:00 -0500 Editor's Choice en text/html https://www.information-age.com/best-practices-for-modern-enterprise-data-architecture-123499796/
Killexams : Inside dark web marketplaces: Amateur cybercriminals collaborate with professional syndicates

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One listing for a remote access trojan (RAT) setup and mentoring service promised

“Make money. Fast. Simple. Easy.” 

For $449, amateur cybercriminals were provided with functionalities including a full desktop clone and control with hidden browser capability, built-in keylogger and XMR miner, and hidden file manager. 

“From cryptocurrency mining to data extraction, there’s [sic] many ways that you can earn money using my RAT setup service,” the seller promised, dubbing its listing a “NOOB [newbie] FRIENDLY MENTORING SERVICE!!” 

Rise of ‘plug and play’

This is just one example of countless in the flourishing cybercrime economy, as uncovered by HP Wolf Security. The endpoint security service from HP. today released the findings of a three-month-long investigation in the report “The Evolution of Cybercrime: Why the Dark Web Is Supercharging the Threat Landscape and How to Fight Back.” 

The report’s starkest takeaway: Cybercriminals are operating on a near-professional footing with easy-to-launch, plug-and-play malware and ransomware attacks being offered on a software-as-a-service basis. This enables those with even the most rudimentary skills to launch cyberattacks. 

“Unfortunately, it’s never been easier to be a cybercriminal,” said the report’s author, Alex Holland, a senior malware analyst with HP. “Now the technology and training is available for the price of a gallon of gas.” 

Taking a walk on the dark side

The HP Wolf Security threat intelligence team led the research, in collaboration with dark web investigators Forensic Pathways and numerous experts from cybersecurity and academia. Such cybersecurity luminaries included ex-Black Hat Michael “MafiaBoy” Calce (who hacked the FBI while still in high school) and criminologist and dark web expert Mike McGuire, Ph.D., of the University of Surrey. 

The investigation involved analysis of more than 35 million cybercriminal marketplace and forum posts, including 33,000 active dark web websites, 5,502 forums and 6,529 marketplaces. It also researched leaked communications of the Conti ransomware group. 

Most notably, findings reveal an explosion in cheap and readily available “plug and play” malware kits. Vendors bundle malware with malware-as-a-service, tutorials, and mentoring services – 76% of malware and 91% of such exploits retail for less than $10. As a result, just 2 to 3% of today’s cybercriminals are high coders. 

Popular software is also providing simple entry for cybercriminals. Vulnerabilities in Windows OS, Microsoft Office, and other web content management systems were of frequent discussion. 

“It’s striking how cheap and plentiful unauthorized access is,” said Holland. “You don’t have to be a capable threat attacker, you don’t have to have many skills and resources available to you. With bundling, you can get a foot in the door of the cybercrime world.” 

The investigation also found the following: 

  • 77% of cybercriminal marketplaces require a vendor bond – or a license to sell – that can cost up to $3,000.
  • 85% of marketplaces use escrow payments, 92% have third-party dispute resolution services, and all provide some sort of review service. 

Also, because the average lifespan of a darknet Tor website is only 55 days, cybercriminals have established mechanisms to transfer reputation between sites. One such example provided a cybercriminal’s username, principle role, when they were last active, positive and negative feedback and star ratings. 

As Holland noted, this reveals an “honor among thieves” mentality, with cybercriminals looking to ensure “fair dealings” because they have no other legal recourse. Ransomware has created a “new cybercriminal ecosystem” that rewards smaller players, ultimately creating a “cybercrime factory line,” Holland said. 

Increasingly sophisticated cybercriminals

The cybercrime landscape has evolved to today’s commoditization of DIY cybercrime and malware kits since hobbyists began congregating in internet chat rooms and collaborating via internet relay chat (IRC) in the early 1990s. 

Today, cybercrime is estimated to cost the world trillions of dollars annually – and the FBI estimates that in 2021 alone, cybercrime in the U.S. ran roughly $6.9 billion. 

The future will bring more sophisticated attacks but also cybercrime that is increasingly efficient, procedural, reproducible and “more boring, more mundane,” Holland said. He anticipates more damaging destructive data-denial attacks and increased professionalization that will drive far more targeted attacks. Attackers will also focus on driving efficiencies to increase ROI, and emerging technologies such as Web3 will be “both weapon and shield.” Similarly, IoT will become a bigger target. 

“Cybercriminals have been increasingly adopting procedures of nation-state attacks,” Holland said, pointing out that many have moved away from “smash and grab” methods. Instead, they perform more reconnaissance on a target before intruding into their network – allowing for more time ultimately spent within a compromised environment. 

Mastering the basics 

There’s no doubt that cybercriminals are often outpacing organizations. Cyberattacks are increasing and tools and techniques are evolving. 

“You have to accept that with unauthorized access so cheap, you can’t have the mentality that it’s never going to happen to you,” Holland said. 

Still, there is hope – and great opportunity for organizations to prepare and defend themselves, he emphasized. Key attack vectors have remained relatively unchanged, which presents defenders with “the chance to challenge whole classes of threat and enhance resilience.” 

Businesses should prepare for destructive data-denial attacks, increasingly targeted cyber campaigns, and cybercriminals that are employing emerging technologies, including artificial intelligence, that ultimately challenge data integrity. 

This comes down to “mastering the basics,” as Holland put it: 

  • Adopt best practices such as multifactor authentication and patch management. 
  • Reduce attack surface from top attack vectors like email, web browsing and file downloads by developing response plans. 
  • Prioritize self-healing hardware to boost resilience.
  • Limit risk posed by people and partners by putting processes in place to vet supplier security and educate workforces on social engineering.
  • Plan for worst-case scenarios by rehearsing to identify problems, make improvements and be better prepared.

“Think of it as a fire drill – you have to really practice, practice, practice,” Holland said.

Cybersecurity as a team sport

Organizations should also be willing to collaborate. There is an opportunity for “more real-time threat intelligence sharing” among peers, he said. 

For instance, organizations can use threat intelligence and be proactive in horizon scanning by monitoring open discussions on underground forums. They can also work with third-party security services to uncover weak spots and critical risks that need addressing.

As most attacks start “with the click of a mouse,” it is critical that everyone become more “cyber aware” on an individual level, said Ian Pratt, Ph.D., global head of security for personal systems at HP Inc.

On the enterprise level, he emphasized the importance of building resiliency and shutting off as many common attack routes as possible. For instance, cybercriminals study patches upon release to reverse-engineer vulnerabilities and rapidly create exploits before other organizations need patching. Thus, speeding up patch management is essential, he said. 

Meanwhile, many of the most common categories of threat – such as those delivered via email and the web – can be fully neutralized through techniques such as threat containment and isolation. This can greatly reduce an organization’s attack surface regardless of whether vulnerabilities are patched.

As Pratt put it, “we all need to do more to fight the growing cybercrime machine.” 

Holland agreed, saying: “Cybercrime is a team sport. Cybersecurity must be too.”

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Thu, 21 Jul 2022 11:30:00 -0500 Taryn Plumb en-US text/html https://venturebeat.com/security/darknet-marketplaces-amateur-cybercriminals-and-professional-syndicates-collaborating/
Killexams : Buy ‘plug-n-play’ malware for the price of a pint of beer

A wide variety of malwares and vulnerability exploits can be bought with ease on underground marketplaces for about $10 (£8.40) on average, according to new statistics – only a few pennies more than the cost of London’s most expensive pint of beer.

The average price of a pint of beer has risen by 70% since the 2008 financial crisis and earlier this year, researchers at customer experience consultancy CGA found one pub in London charging £8.06. The researchers, perhaps sensibly, did not name the establishment in question.

But according to a new report, The evolution of cybercrime: why the dark web is supercharging the threat landscape and how to fight back, produced by HP’s endpoint security unit HP Wolf Security, the price of cyber criminality is tumbling, with 76% of malware advertisements, and 91% of exploits, found to retail for under $10.

Meanwhile, the average cost of an organisation’s compromised remote desktop protocol (RDP) credentials clocked in at just $5 (£4.20) – a far more appealing price for a beer as well, especially in London.

Vulnerabilities in niche systems, predictably, went for higher prices, and zero-days, vulnerabilities yet to be publicly disclosed, still fetch tens of thousands of pounds.

HP Wolf’s threat team got together with forensic specialists Forensic Pathways and spent three months scraping and analysing 35 million posts on dark web marketplaces and forums to understand how cyber criminals operate, gain each other’s trust, and build their reputations.

And unfortunately, said HP senior malware analyst and report author Alex Holland, it has never been easier or cheaper to get into cyber crime.

“Complex attacks previously required serious skills, knowledge and resource, but now the technology and training is available for the price of a gallon of gas,” said Holland. “And whether it’s having your company and customer data exposed, deliveries delayed or even a hospital appointment cancelled, the explosion in cyber crime affects us all.

“At the heart of this is ransomware, which has created a new cyber criminal ecosystem rewarding smaller players with a slice of the profits. This is creating a cyber crime factory line, churning out attacks that can be very hard to defend against and putting the businesses we all rely on in the crosshairs.”

The exercise also found many cyber criminal vendors bundling their wares for sale. In what might reasonably be termed the cyber criminal equivalent of a supermarket meal deal, the buyers receive plug-and-play malware kits, malware- or ransomware-as-a-service (MaaS/RaaS), tutorials, and even mentoring, as opposed to sandwiches, crisps and a soft drink.

In fact, the skills barrier to cyber criminality has never been lower, the researchers said, with only 2-3% of threat actors now considered “advanced coders”.

And like people who use legitimate marketplaces such as Ebay or Etsy, cyber criminals value trust and reputation, with over three-quarters of the marketplaces of forums requiring a vendor bond of up to $3,000 to become a licensed seller. An even bigger majority – over 80% – used escrow systems to protect “good faith” deposits made by buyers, and 92% had some kind of third-party dispute resolution service.

Every marketplace studied also provides vendor feedback scores. In many cases, these hard-won reputations are transferrable between sites, the average lifespan of a dark web marketplace clocking in at less than three months.

Fortunately, protecting against such increasingly professional operations is, as ever, largely a case of paying attention to mastering the basics of cyber security, adding multi-factor authentication (MFA), better patch management, limiting risks posed by employees and suppliers, and being proactive in terms of gleaning threat intelligence.

Ian Pratt, HP Inc’s global head of security for personal systems, said: “We all need to do more to fight the growing cyber crime machine. For individuals, this means becoming cyber aware. Most attacks start with a click of a mouse, so thinking before you click is always important. But giving yourself a safety net by buying technology that can mitigate and recover from the impact of bad clicks is even better.

“For businesses, it’s important to build resiliency and shut off as many common attack routes as possible. For example, cyber criminals study patches on release to reverse-engineer the vulnerability being patched and can rapidly create exploits to use before organisations have patched. So, speeding up patch management is important.

“Many of the most common categories of threat, such as those delivered via email and the web, can be fully neutralised through techniques such as threat containment and isolation, greatly reducing an organisation’s attack surface, regardless of whether the vulnerabilities are patched or not.”

Thu, 21 Jul 2022 07:12:00 -0500 en text/html https://www.computerweekly.com/news/252523004/Buy-plug-n-play-malware-for-the-price-of-a-pint-of-beer
Killexams : How DevOps works in the enterprise How DevOps works in the enterprise — it's all about rapidity of release, but without sacrificing and compromising on quality in the digital world How DevOps works in the enterprise image

DevOps is an enabler of digital transformation.

How DevOps works in the enterprise is one of key questions business leaders have been asking.

This relatively new discipline, which Atlassian describes as agile applied beyond the software team, is helping businesses release products fast, but without cutting corners — which is “the name of the game at the moment in the digital world”, according to Gordon Cullum, speaking as CTO at Mastek — now technology director at Axiologik.

Increasingly, DevOps is the style in which businesses want to interact with each other in the digital age; it’s about rapidity of release without sacrificing and compromising on quality.

Patrick Callaghan, vice-president, partner CTO at DataStax, goes one step further.

He suggests that businesses “can’t truly function as an enterprise without applying DevOps software development principles…. DevOps in practice is ideal for organisations looking to streamline production, automate processes and build a culture of collaboration within their software teams. DevOps innovators are confident in their code because they both test it and make it fail in order to produce reliable apps.”

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What is DevOps?

How DevOps works? Before getting into this, it’s important to understand what is DevOps.

Quoting AWS, ‘DevOps is the combination of cultural philosophies, practices, and tools that increases an organisation’s ability to deliver applications and services at high velocity: evolving and improving products at a faster pace than organisations using traditional software development and infrastructure management processes. This speed enables organisations to better serve their customers and compete more effectively in the market.’

This is a very practical explanation, but there are multiple definitions of the term.

It’s often described as a set of evolutionary practices inherited from the ways of agile working, which are more tuned to bringing the delivery and operational support communities closer together. This surrounds using processes and tooling that has been developed over the years for things like test automation, continuous integration, continuous deployment, to enable the faster flow of code. These new releases of code could be new functionality, architectural change or bug fixes.

“It’s a combination of keeping the lights on and changing delivery,” says Cullum.


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The future of DevOps


Reinvigorating an old way of working

Bringing delivery and support together is a throwback to the 1980s and 1990s, “where IT just did IT and you didn’t care whether you asked them to fix a bug or deliver functionality,” continues Cullum.

This ethos is being reinvigorated in DevOps. But the reason it works and is more powerful today is because of the emergence of enabling technologies and new ways of working.

“While, 20 to 30 years ago we may have had JFDI approaches for getting stuff into live environments, what we now have are very controlled, measured processes, brought around by tools such as Puppet and Jenkins — these all create the robust, quality, managed pipeline that allows fast delivery,” explains Cullum.

Culturally, the discipline brings lots of old and new ideas together

Why DevOps now?

The reason DevOps has emerged now is because companies are involved in a highly competitive arms race.

Everything is accelerating so fast from a delivery point of view; if businesses can’t release code quickly, then they are probably already being disrupted. This brings challenges, but also provides advantages if you are already on that curve. Agile work patterns, for example, only really work if the organisation already has a relatively modern architecture.

The other area in the acceleration of DevOps is the emergence of cloud services. Over the last five to 10 years, the cloud has enabled very quick, easy and at times cost effective processes and techniques. These can be spun out in environments, infrastructures, platforms or whole services, and can be wired together very easily.

What this means is that architects are more able to build componentised architectures that are independently able to be released, modified and scaled from each other.

“So modern techniques, such as microservices and even serverless architectures, really accelerate the uptake of DevOps capabilities from a delivery and support point of view within an organisation,” says Cullum.

Bringing all these things together; the rise of cloud, the need to get things out faster but at a high quality, the rise of all the tooling that enables fast pipeline deliveries, changing culture and IT, what you’ve got is DevOps.

According to Statista, 21 per cent of DevOps engineers have added source code management to their DevOps practices, in the aim to accelerate the release of code.

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How DevOps works in the enterprise

What is the best approach organisations can take to DevOps? “It’s horses for courses-type conversation,” answers Cullum. By this, he means there are a lot of “complications under the hood”.

The first thing for organisations would be to identify why they want to adopt DevOps, so “they can keep their eyes on the prize”.

“It’s not about a marketing term, it’s not about somebody at c-level saying we want to implement DevOps, go away and do it,” suggests Cullum. “You have to know why you’re trying to do it. What is it you want? Do you want repeatable quality? Do you want cheaper or faster deliveries? Do you recognise a need to modify the architecture,” he asks?

Gordon Cullum looks after Mastek's technology strategy.

Gordon Cullum oversaw digital transformation company Mastek’s technology strategy as its CTO.

The leaders at legacy organisations, such as an older bank with monolithic environments, can’t just send their IT department on a DevOps training programme and expect them to be able to change the way they release software on mainframes. “It isn’t going to work like that,” suggests Cullum. In this scenario, there needs to be an architecture enablement programme that takes place, “which is how these legacy organisations can make sure that the services they deliver through the IT estate can be componentised in a way that delivery teams can run at their own pace.”

So, how DevOps works depends on the journey. There is no simple answer. But, the key takeaways for business leaders would be; don’t underestimate the cultural change required (people have to buy into the idea, similar to digital transformation), don’t rely too much on heavy documentation (you’re not going to know everything up front) and approach risk proactively (don’t be afraid of change).

If business then decide to implement DevOps within teams, from a process and method point of view, then these questions must be addressed; is your architecture able to support it? Is a leadership roadmap in place that creates the environment necessary to start delivering fast, high quality, automated deliveries?

“It’s a good question and requires a very consultative answer,” says Cullum.

Addressing these six steps in the DevOps cycle will lead to organisation success in this discipline. Image source: 6 C’s of DevOps Life Cycle

Addressing these six steps in the DevOps cycle will lead to organisation success in this discipline. Image source: 6 C’s of DevOps Life Cycle.

The DevOps workforce

As with any new disciple, even traditional ones in technology, the skills gap proves irksome. So, when implementing DevOps, should organisations retrain or bring in new talent?

It’s probably a bit of both, but the biggest thing people need is the right attitude. Mastek soon found this, according to Cullum. The programmers, designers and product managers who have been in the industry for 15 to 20 years are sometimes resistant to the change DevOps brings. They need to embrace a rapid change mindset, and accept that delivery and operations need to get closer together.

Generally, however, if “you aren’t already stuck in the mud at a senior level”, individuals in the industry are already well versed in the pace of change and in learning new techniques — they have to be “cross-skilled,” as Cullum describes.

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Justifying this, he explains that what Mastek is finding is that it’s easier to train trainee engineers in new techniques, because they haven’t yet been conditioned to think in the older, waterfall-style ways of thinking.

“It’s harder to change attitude than it is to change a technology skill set,” he says. “So, we are cross-training and it’s working quite successfully, but we are seeing an accelerating effect by focusing on DevOps and agile techniques for our trainees.”

To satisfy this, there are seven key skills for businesses to consider:

1. Flexibility
2. Security skills
3. Collaboration
4. Scripting skills
5. Decision-making
6. Infrastructure knowledge
7. Soft skills

DevOps: an essential part of digital transformation?

Digital transformation is a wholesale reinvention of business — embracing digital, culturally and technologically.

“If you’re not reinventing your business processes, then you are not doing a transformation,” points out Cullum.

But, if businesses are reinventing business processes, then by definition they’re probably going to be overhauling large chunks of their IT estate, including the aforementioned legacy.

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By embarking on this journey, sooner or later, these transformative businesses will be moving into a modern-style architecture with different components and different paces of different deliveries.

“In our case, we often talk about pace-layered deliveries,” says Cullum. “You’re going to put a lot more focus in your systems of differentiation and innovation, and they have to have rapid relatively robust change going in,” he says.

DevOps is the enabler of that.

If businesses aren’t doing DevOps — they might call it something else — or repeatable, automated deployment testing processes then they are not embracing change and able to make releases at the speed of change.

Why DevOps is important

DevOps, like digital, is an assumed norm now. It’s probably a little late to start thinking about it.

“If you aren’t already thinking about it or aren’t already doing it, you’re probably way behind the curve,” warns Cullum.

In digitally-resistant organisations it is likely that there are “guerrilla factions” that are trying DevOps. “In this case, you should probably go and look at what’s going on there and work out how you can industrialise that and scale it out,” he advises. “If you aren’t doing any of that, then you’re probably holding yourself back as a business.”

Some argue, however, it’s never too late to join the DevOps integration race.

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Business case study

Callaghan suggests that Netflix is a great example of making DevOps work for the business.

He says: “Netflix has used Apache Cassandra™ for its high availability, and to test for this they wrote a series of testing libraries called “Chaos Monkey.” For example, both “Chaos Kong” and “Chaos Gorilla” tests are used to decimate Netflix infrastructure to evaluate the impact on availability and function. As a result of the practice, Netflix is confident in their system and its reliability. DevOps software development practice enables Netflix to effectively speed up development and produce an always-on experience for their users.”

The DevOps engineer: fulfilling the software development life cycle

The DevOps engineer is becoming a more common presence in the enterprise. But, what exactly does the role entail and how can you become one? Read here

Related:

How to drive impact and change via DevOps — Stephen Magennis, managing director for Expleo Technology (UK technology), discusses how impact and change can be driven via DevOps.

How intelligent software delivery can accelerate digital experience success — Greg Adams, regional vice-president UK&I at Dynatrace, discusses how intelligent software delivery can accelerate digital experience success.

Mon, 01 Aug 2022 12:00:00 -0500 Nick Ismail en text/html https://www.information-age.com/how-devops-works-in-the-enterprise-123481877/
Killexams : IBM Research Rolls Out A Comprehensive AI And Platform-Based Edge Research Strategy Anchored By Enterprise Use Cases And Partnerships

I recently met with Dr. Nick Fuller, Vice President, Distributed Cloud, at IBM Research for a discussion about IBM’s long-range plans and strategy for artificial intelligence and machine learning at the edge.

Dr. Fuller is responsible for providing AI and platform–based innovation for enterprise digital transformation spanning edge computing and distributed cloud management. He is an IBM Master Inventor with over 75 patents and co-author of 75 technical publications. Dr. Fuller obtained his Bachelor of Science in Physics and Math from Morehouse College and his PhD in Applied Physics from Columbia University.

Edge In, not Cloud Out

In general, Dr. Fuller told me that IBM is focused on developing an "edge in" position versus a "cloud out" position with data, AI, and Kubernetes-based platform technologies to scale hub and spoke deployments of edge applications.

A hub plays the role of a central control plane used for orchestrating the deployment and management of edge applications in a number of connected spoke locations such as a factory floor or a retail branch, where data is generated or locally aggregated for processing.

“Cloud out” refers to the paradigm where cloud service providers are extending their cloud architecture out to edge locations. In contrast, “edge in” refers to a provider-agnostic architecture that is cloud-independent and treats the data-plane as a first-class citizen.

IBM's overall architectural principle is scalability, repeatability, and full stack solution management that allows everything to be managed using a single unified control plane.

IBM’s Red Hat platform and infrastructure strategy anchors the application stack with a unified, scalable, and managed OpenShift-based control plane equipped with a high-performance storage appliance and self-healing system capabilities (inclusive of semi-autonomous operations).

IBM’s strategy also includes several in-progress platform-level technologies for scalable data, AI/ML runtimes, accelerator libraries for Day-2 AI operations, and scalability for the enterprise.

It is an important to mention that IBM is designing its edge platforms with labor cost and technical workforce in mind. Data scientists with PhDs are in high demand, making them difficult to find and expensive to hire once you find them. IBM is designing its edge system capabilities and processes so that domain experts rather than PhDs can deploy new AI models and manage Day-2 operations.

Why edge is important

Advances in computing and storage have made it possible for AI to process mountains of accumulated data to provide solutions. By bringing AI closer to the source of data, edge computing is faster and more efficient than cloud. While Cloud data accounts for 60% of the world’s data today, vast amounts of new data is being created at the edge, including industrial applications, traffic cameras, and order management systems, all of which can be processed at the edge in a fast and timely manner.

Public cloud and edge computing differ in capacity, technology, and management. An advantage of edge is that data is processed and analyzed at / near its collection point at the edge. In the case of cloud, data must be transferred from a local device and into the cloud for analytics and then transferred back to the edge again. Moving data through the network consumes capacity and adds latency to the process. It’s easy to see why executing a transaction at the edge reduces latency and eliminates unnecessary load on the network.

Increased privacy is another benefit of processing data at the edge. Analyzing data where it originates limits the risk of a security breach. Most of the communications between the edge and the cloud is then confined to such things as reporting, data summaries, and AI models, without ever exposing the raw data.

IBM at the Edge

In our discussion, Dr. Fuller provided a few examples to illustrate how IBM plans to provide new and seamless edge solutions for existing enterprise problems.

Example #1 – McDonald’s drive-thru

Dr. Fuller’s first example centered around Quick Service Restaurant’s (QSR) problem of drive-thru order taking. Last year, IBM acquired an automated order-taking system from McDonald's. As part of the acquisition, IBM and McDonald's established a partnership to perfect voice ordering methods using AI. Drive-thru orders are a significant percentage of total QSR orders for McDonald's and other QSR chains.

McDonald's and other QSR restaurants would like every order to be processed as quickly and accurately as possible. For that reason, McDonald's conducted trials at ten Chicago restaurants using an edge-based AI ordering system with NLP (Natural Language Processing) to convert spoken orders into a digital format. It was found that AI had the potential to reduce ordering errors and processing time significantly. Since McDonald's sells almost 7 million hamburgers daily, shaving a minute or two off each order represents a significant opportunity to address labor shortages and increase customer satisfaction.

Example #2 – Boston Dynamics and Spot the agile mobile robot

According to an earlier IBM survey, many manufacturers have already implemented AI-driven robotics with autonomous decision-making capability. The study also indicated that over 80 percent of companies believe AI can help Boost future business operations. However, some companies expressed concern about the limited mobility of edge devices and sensors.

To develop a mobile edge solution, IBM teamed up with Boston Dynamics. The partnership created an agile mobile robot using IBM Research and IBM Sustainability Software AI technology. The device can analyze visual sensor readings in hazardous and challenging industrial environments such as manufacturing plants, warehouses, electrical grids, waste treatment plants and other hazardous environments. The value proposition that Boston Dynamics brought to the partnership was Spot the agile mobile robot, a walking, sensing, and actuation platform. Like all edge applications, the robot’s wireless mobility uses self-contained AI/ML that doesn’t require access to cloud data. It uses cameras to read analog devices, visually monitor fire extinguishers, and conduct a visual inspection of human workers to determine if required safety equipment is being worn.

IBM was able to show up to a 10X speedup by automating some manual tasks, such as converting the detection of a problem into an immediate work order in IBM Maximo to correct it. A fast automated response was not only more efficient, but it also improved the safety posture and risk management for these facilities. Similarly, some factories need to thermally monitor equipment to identify any unexpected hot spots that may show up over time, indicative of a potential failure.

IBM is working with National Grid, an energy company, to develop a mobile solution using Spot, the agile mobile robot, for image analysis of transformers and thermal connectors. As shown in the above graphic, Spot also monitored connectors on both flat surfaces and 3D surfaces. IBM was able to show that Spot could detect excessive heat build-up in small connectors, potentially avoiding unsafe conditions or costly outages. This AI/ML edge application can produce faster response times when an issue is detected, which is why IBM believes significant gains are possible by automating the entire process.

IBM market opportunities

Drive-thru orders and mobile robots are just a few examples of the millions of potential AI applications that exist at the edge and are driven by several billion connected devices.

Edge computing is an essential part of enterprise digital transformation. Enterprises seek ways to demonstrate the feasibility of solving business problems using AI/ML and analytics at the edge. However, once a proof of concept has been successfully demonstrated, it is a common problem for a company to struggle with scalability, data governance, and full-stack solution management.

Challenges with scaling

“Determining entry points for AI at the edge is not the difficult part,” Dr. Fuller said. “Scale is the real issue.”

Scaling edge models is complicated because there are so many edge locations with large amounts of diverse content and a high device density. Because large amounts of data are required for training, data gravity is a potential problem. Further, in many scenarios, vast amounts of data are generated quickly, leading to potential data storage and orchestration challenges. AI Models are also rarely "finished." Monitoring and retraining of models are necessary to keep up with changes the environment.

Through IBM Research, IBM is addressing the many challenges of building an all-encompassing edge architecture and horizontally scalable data and AI technologies. IBM has a wealth of edge capabilities and an architecture to create the appropriate platform for each application.

IBM AI entry points at the edge

IBM sees Edge Computing as a $200 billion market by 2025. Dr. Fuller and his organization have identified four key market entry points for developing and expanding IBM’s edge compute strategy. In order of size, IBM believes its priority edge markets to be intelligent factories (Industry 4.0), telcos, retail automation, and connected vehicles.

IBM and its Red Hat portfolio already have an established presence in each market segment, particularly in intelligent operations and telco. Red Hat is also active in the connected vehicles space.

Industry 4.0

There have been three prior industrial revolutions, beginning in the 1700s up to our current in-progress fourth revolution, Industry 4.0, that promotes a digital transformation.

Manufacturing is the fastest growing and the largest of IBM’s four entry markets. In this segment, AI at the edge can Boost quality control, production optimization, asset management, and supply chain logistics. IBM believes there are opportunities to achieve a 4x speed up in implementing edge-based AI solutions for manufacturing operations.

For its Industry 4.0 use case development, IBM, through product, development, research and consulting teams, is working with a major automotive OEM. The partnership has established the following joint objectives:

  • Increase automation and scalability across dozens of plants using 100s of AI / ML models. This client has already seen value in applying AI/ML models for manufacturing applications. IBM Research is helping with re-training models and implementing new ones in an edge environment to help scale even more efficiently. Edge offers faster inference and low latency, allowing AI to be deployed in a wider variety of manufacturing operations requiring instant solutions.
  • Dramatically reduce the time required to onboard new models. This will allow training and inference to be done faster and allow large models to be deployed much more quickly. The quicker an AI model can be deployed in production; the quicker the time-to-value and the return-on-investment (ROI).
  • Accelerate deployment of new inspections by reducing the labeling effort and iterations needed to produce a production-ready model via data summarization. Selecting small data sets for annotation means manually examining thousands of images, this is a time-consuming process that will result in - labeling of redundant data. Using ML-based automation for data summarization will accelerate the process and produce better model performance.
  • Enable Day-2 AI operations to help with data lifecycle automation and governance, model creation, reduce production errors, and provide detection of out-of-distribution data to help determine if a model’s inference is accurate. IBM believes this will allow models to be created faster without data scientists.

Maximo Application Suite

IBM’s Maximo Application Suite plays an important part in implementing large manufacturers' current and future IBM edge solutions. Maximo is an integrated public or private cloud platform that uses AI, IoT, and analytics to optimize performance, extend asset lifecycles and reduce operational downtime and costs. IBM is working with several large manufacturing clients currently using Maximo to develop edge use cases, and even uses it within its own Manufacturing.

IBM has research underway to develop a more efficient method of handling life cycle management of large models that require immense amounts of data. Day 2 AI operations tasks can sometimes be more complex than initial model training, deployment, and scaling. Retraining at the edge is difficult because resources are typically limited.

Once a model is trained and deployed, it is important to monitor it for drift caused by changes in data distributions or anything that might cause a model to deviate from original requirements. Inaccuracies can adversely affect model ROI.

Day-2 AI Operations (retraining and scaling)

Day-2 AI operations consist of continual updates to AI models and applications to keep up with changes in data distributions, changes in the environment, a drop in model performance, availability of new data, and/or new regulations.

IBM recognizes the advantages of performing Day-2 AI Operations, which includes scaling and retraining at the edge. It appears that IBM is the only company with an architecture equipped to effectively handle Day-2 AI operations. That is a significant competitive advantage for IBM.

A company using an architecture that requires data to be moved from the edge back into the cloud for Day-2 related work will be unable to support many factory AI/ML applications because of the sheer number of AI/ML models to support (100s to 1000s).

“There is a huge proliferation of data at the edge that exists in multiple spokes,” Dr. Fuller said. "However, all that data isn’t needed to retrain a model. It is possible to cluster data into groups and then use sampling techniques to retrain the model. There is much value in federated learning from our point of view.”

Federated learning is a promising training solution being researched by IBM and others. It preserves privacy by using a collaboration of edge devices to train models without sharing the data with other entities. It is a good framework to use when resources are limited.

Dealing with limited resources at the edge is a challenge. IBM’s edge architecture accommodates the need to ensure resource budgets for AI applications are met, especially when deploying multiple applications and multiple models across edge locations. For that reason, IBM developed a method to deploy data and AI applications to scale Day-2 AI operations utilizing hub and spokes.

The graphic above shows the current status quo methods of performing Day-2 operations using centralized applications and a centralized data plane compared to the more efficient managed hub and spoke method with distributed applications and a distributed data plane. The hub allows it all to be managed from a single pane of glass.

Data Fabric Extensions to Hub and Spokes

IBM uses hub and spoke as a model to extend its data fabric. The model should not be thought of in the context of a traditional hub and spoke. IBM’s hub provides centralized capabilities to manage clusters and create multiples hubs that can be aggregated to a higher level. This architecture has four important data management capabilities.

  1. First, models running in unattended environments must be monitored. From an operational standpoint, detecting when a model’s effectiveness has significantly degraded and if corrective action is needed is critical.
  2. Secondly, in a hub and spoke model, data is being generated and collected in many locations creating a need for data life cycle management. Working with large enterprise clients, IBM is building unique capabilities to manage the data plane across the hub and spoke estate - optimized to meet data lifecycle, regulatory & compliance as well as local resource requirements. Automation determines which input data should be selected and labeled for retraining purposes and used to further Boost the model. Identification is also made for atypical data that is judged worthy of human attention.
  3. The third issue relates to AI pipeline compression and adaptation. As mentioned earlier, edge resources are limited and highly heterogeneous. While a cloud-based model might have a few hundred million parameters or more, edge models can’t afford such resource extravagance because of resource limitations. To reduce the edge compute footprint, model compression can reduce the number of parameters. As an example, it could be reduced from several hundred million to a few million.
  4. Lastly, suppose a scenario exists where data is produced at multiple spokes but cannot leave those spokes for compliance reasons. In that case, IBM Federated Learning allows learning across heterogeneous data in multiple spokes. Users can discover, curate, categorize and share data assets, data sets, analytical models, and their relationships with other organization members.

In addition to AI deployments, the hub and spoke architecture and the previously mentioned capabilities can be employed more generally to tackle challenges faced by many enterprises in consistently managing an abundance of devices within and across their enterprise locations. Management of the software delivery lifecycle or addressing security vulnerabilities across a vast estate are a case in point.

Multicloud and Edge platform

In the context of its strategy, IBM sees edge and distributed cloud as an extension of its hybrid cloud platform built around Red Hat OpenShift. One of the newer and more useful options created by the Red Hat development team is the Single Node OpenShift (SNO), a compact version of OpenShift that fits on a single server. It is suitable for addressing locations that are still servers but come in a single node, not clustered, deployment type.

For smaller footprints such as industrial PCs or computer vision boards (for example NVidia Jetson Xavier), Red Hat is working on a project which builds an even smaller version of OpenShift, called MicroShift, that provides full application deployment and Kubernetes management capabilities. It is packaged so that it can be used for edge device type deployments.

Overall, IBM and Red Hat have developed a full complement of options to address a large spectrum of deployments across different edge locations and footprints, ranging from containers to management of full-blown Kubernetes applications from MicroShift to OpenShift and IBM Edge Application Manager.

Much is still in the research stage. IBM's objective is to achieve greater consistency in terms of how locations and application lifecycle is managed.

First, Red Hat plans to introduce hierarchical layers of management with Red Hat Advanced Cluster Management (RHACM), to scale by two to three orders of magnitude the number of edge locations managed by this product. Additionally, securing edge locations is a major focus. Red Hat is continuously expanding platform security features, for example by recently including Integrity Measurement Architecture in Red Hat Enterprise Linux, or by adding Integrity Shield to protect policies in Red Hat Advanced Cluster Management (RHACM).

Red Hat is partnering with IBM Research to advance technologies that will permit it to protect platform integrity and the integrity of client workloads through the entire software supply chains. In addition, IBM Research is working with Red Hat on analytic capabilities to identify and remediate vulnerabilities and other security risks in code and configurations.

Telco network intelligence and slice management with AL/ML

Communication service providers (CSPs) such as telcos are key enablers of 5G at the edge. 5G benefits for these providers include:

  • Reduced operating costs
  • Improved efficiency
  • Increased distribution and density
  • Lower latency

The end-to-end 5G network comprises the Radio Access Network (RAN), transport, and core domains. Network slicing in 5G is an architecture that enables multiple virtual and independent end-to-end logical networks with different characteristics such as low latency or high bandwidth, to be supported on the same physical network. This is implemented using cloud-native technology enablers such as software defined networking (SDN), virtualization, and multi-access edge computing. Slicing offers necessary flexibility by allowing the creation of specific applications, unique services, and defined user groups or networks.

An important aspect of enabling AI at the edge requires IBM to provide CSPs with the capability to deploy and manage applications across various enterprise locations, possibly spanning multiple end-to-end network slices, using a single pane of glass.

5G network slicing and slice management

Network slices are an essential part of IBM's edge infrastructure that must be automated, orchestrated and optimized according to 5G standards. IBM’s strategy is to leverage AI/ML to efficiently manage, scale, and optimize the slice quality of service, measured in terms of bandwidth, latency, or other metrics.

5G and AI/ML at the edge also represent a significant opportunity for CSPs to move beyond traditional cellular services and capture new sources of revenue with new services.

Communications service providers need management and control of 5G network slicing enabled with AI-powered automation.

Dr. Fuller sees a variety of opportunities in this area. "When it comes to applying AI and ML on the network, you can detect things like intrusion detection and malicious actors," he said. "You can also determine the best way to route traffic to an end user. Automating 5G functions that run on the network using IBM network automation software also serves as an entry point.”

In IBM’s current telecom trial, IBM Research is spearheading the development of a range of capabilities targeted for the IBM Cloud Pak for Network Automation product using AI and automation to orchestrate, operate and optimize multivendor network functions and services that include:

  • End-to-end 5G network slice management with planning & design, automation & orchestration, and operations & assurance
  • Network Data and AI Function (NWDAF) that collects data for slice monitoring from 5G Core network functions, performs network analytics, and provides insights to authorized data consumers.
  • Improved operational efficiency and reduced cost

Future leverage of these capabilities by existing IBM Clients that use the Cloud Pak for Network Automation (e.g., DISH) can offer further differentiation for CSPs.

5G radio access

Open radio access networks (O-RANs) are expected to significantly impact telco 5G wireless edge applications by allowing a greater variety of units to access the system. The O-RAN concept separates the DU (Distributed Units) and CU (Centralized Unit) from a Baseband Unit in 4G and connects them with open interfaces.

O-RAN system is more flexible. It uses AI to establish connections made via open interfaces that optimize the category of a device by analyzing information about its prior use. Like other edge models, the O-RAN architecture provides an opportunity for continuous monitoring, verification, analysis, and optimization of AI models.

The IBM-telco collaboration is expected to advance O-RAN interfaces and workflows. Areas currently under development are:

  • Multi-modal (RF level + network-level) analytics (AI/ML) for wireless communication with high-speed ingest of 5G data
  • Capability to learn patterns of metric and log data across CUs and DUs in RF analytics
  • Utilization of the antenna control plane to optimize throughput
  • Primitives for forecasting, anomaly detection and root cause analysis using ML
  • Opportunity of value-added functions for O-RAN

IBM Cloud and Infrastructure

The cornerstone for the delivery of IBM's edge solutions as a service is IBM Cloud Satellite. It presents a consistent cloud-ready, cloud-native operational view with OpenShift and IBM Cloud PaaS services at the edge. In addition, IBM integrated hardware and software Edge systems will provide RHACM - based management of the platform when clients or third parties have existing managed as a service models. It is essential to note that in either case this is done within a single control plane for hubs and spokes that helps optimize execution and management from any cloud to the edge in the hub and spoke model.

IBM's focus on “edge in” means it can provide the infrastructure through things like the example shown above for software defined storage for federated namespace data lake that surrounds other hyperscaler clouds. Additionally, IBM is exploring integrated full stack edge storage appliances based on hyperconverged infrastructure (HCI), such as the Spectrum Fusion HCI, for enterprise edge deployments.

As mentioned earlier, data gravity is one of the main driving factors of edge deployments. IBM has designed its infrastructure to meet those data gravity requirements, not just for the existing hub and spoke topology but also for a future spoke-to-spoke topology where peer-to-peer data sharing becomes imperative (as illustrated with the wealth of examples provided in this article).

Wrap up

Edge is a distributed computing model. One of its main advantages is that computing, and data storage and processing is close to where data is created. Without the need to move data to the cloud for processing, real-time application of analytics and AI capabilities provides immediate solutions and drives business value.

IBM’s goal is not to move the entirety of its cloud infrastructure to the edge. That has little value and would simply function as a hub to spoke model operating on actions and configurations dictated by the hub.

IBM’s architecture will provide the edge with autonomy to determine where data should reside and from where the control plane should be exercised.

Equally important, IBM foresees this architecture evolving into a decentralized model capable of edge-to-edge interactions. IBM has no firm designs for this as yet. However, the plan is to make the edge infrastructure and platform a first-class citizen instead of relying on the cloud to drive what happens at the edge.

Developing a complete and comprehensive AI/ML edge architecture - and in fact, an entire ecosystem - is a massive undertaking. IBM faces many known and unknown challenges that must be solved before it can achieve success.

However, IBM is one of the few companies with the necessary partners and the technical and financial resources to undertake and successfully implement a project of this magnitude and complexity.

It is reassuring that IBM has a plan and that its plan is sound.

Paul Smith-Goodson is Vice President and Principal Analyst for quantum computing, artificial intelligence and space at Moor Insights and Strategy. You can follow him on Twitter for more current information on quantum, AI, and space.

Note: Moor Insights & Strategy writers and editors may have contributed to this article.

Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movandi.

Mon, 08 Aug 2022 03:51:00 -0500 Paul Smith-Goodson en text/html https://www.forbes.com/sites/moorinsights/2022/08/08/ibm-research-rolls-out-a-comprehensive-ai-and-ml-edge-research-strategy-anchored-by-enterprise-partnerships-and-use-cases/
Killexams : QinetiQ expands U.S. footprint with Avantus Federal deal

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Fri, 05 Aug 2022 16:37:00 -0500 en text/html https://washingtontechnology.com/companies/2022/08/qinetiq-expands-us-footprint-avantus-federal-deal/375494/?oref=wt-skybox-hp
Killexams : Big Data Services Market to Witness Massive Growth by 2029 | Accenture, Deloitte, Hewlett-Packard (HP)

New Jersey, N.J., July 18, 2022 The Big Data Services Market research report provides all the information related to the industry. It gives the outlook of the market by giving authentic data to its client which helps to make essential decisions. It gives an overview of the market which includes its definition, applications and developments, and manufacturing technology. This Big Data Services market research report tracks all the latest developments and innovations in the market. It gives the data regarding the obstacles while establishing the business and guides to overcome the upcoming challenges and obstacles.

The latest trend gaining momentum in the market is increasing market consolidation. Consolidation in the global big data services market is intensifying as many large enterprise IT vendors are acquiring companies to provide new big data technologies. Large vendors are targeting smaller companies to expand their business portfolios and are acquiring major pure-play Big Data vendors. One of the main drivers of this market is the growing amount of data. Data volumes are exploding and more data has been created since 2014 than in all of previous history. Enterprise applications generate large volumes of data and will continue throughout the forecast period and beyond.

Get the PDF sample Copy (Including FULL TOC, Graphs, and Tables) of this report @:

https://www.a2zmarketresearch.com/sample-request/658016

Competitive landscape:

This Big Data Services research report throws light on the major market players thriving in the market; it tracks their business strategies, financial status, and upcoming products.

Some of the Top companies Influencing this Market include:Accenture, Deloitte, Hewlett-Packard (HP), IBM, PricewaterhouseCoopers (PwC), SAP, Teradata

Market Scenario:

Firstly, this Big Data Services research report introduces the market by providing an overview which includes definition, applications, product launches, developments, challenges, and regions. The market is forecasted to reveal strong development by driven consumption in various markets. An analysis of the current market designs and other basic characteristics is provided in the Big Data Services report.

Regional Coverage:

The region-wise coverage of the market is mentioned in the report, mainly focusing on the regions:

  • North America
  • South America
  • Asia and Pacific region
  • Middle East and Africa
  • Europe

Segmentation Analysis of the market

The market is segmented on the basis of the type, product, end users, raw materials, etc. the segmentation helps to deliver a precise explanation of the market

Market Segmentation: By Type

Public Cloud

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An assessment of the market attractiveness with regard to the competition that new players and products are likely to present to older ones has been provided in the publication. The research report also mentions the innovations, new developments, marketing strategies, branding techniques, and products of the key participants present in the global Big Data Services market. To present a clear vision of the market the competitive landscape has been thoroughly analyzed utilizing the value chain analysis. The opportunities and threats present in the future for the key market players have also been emphasized in the publication.

This report aims to provide:

  • A qualitative and quantitative analysis of the current trends, dynamics, and estimations from 2022 to 2029.
  • The analysis tools such as SWOT analysis, and Porter’s five force analysis are utilized which explain the potency of the buyers and suppliers to make profit-oriented decisions and strengthen their business.
  • The in-depth analysis of the market segmentation helps to identify the prevailing market opportunities.
  • In the end, this Big Data Services report helps to save you time and money by delivering unbiased information under one roof.

Table of Contents

Global Big Data Services Market Research Report 2022 – 2029

Chapter 1 Big Data Services Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Big Data Services Market Forecast

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Mon, 18 Jul 2022 00:58:00 -0500 A2Z Market Research en-US text/html https://www.digitaljournal.com/pr/big-data-services-market-to-witness-massive-growth-by-2029-accenture-deloitte-hewlett-packard-hp
Killexams : Stolen Credentials Selling on the Dark Web for Price of a Gallon of Gas

PALO ALTO, Calif. , July 21, 2022 (GLOBE NEWSWIRE) -- HP Inc. HPQ today released The Evolution of Cybercrime: Why the Dark Web is Supercharging the Threat Landscape and How to Fight Back – an HP Wolf Security Report. The findings show cybercrime is being supercharged through "plug and play" malware kits that make it easier than ever to launch attacks. Cyber syndicates are collaborating with amateur attackers to target businesses, putting our online world at risk.

The HP Wolf Security threat team worked with Forensic Pathways, a leading group of global forensic professionals, on a three-month dark web investigation, scraping and analyzing over 35 million cybercriminal marketplaces and forum posts to understand how cybercriminals operate, gain trust, and build reputation.

Key findings include:

  • Malware is cheap and readily available – Over three quarters (76%) of malware advertisements listed, and 91% of exploits (i.e. code that gives attackers control over systems by taking advantage of software bugs), retail for under $10 USD. The average cost of compromised Remote Desktop Protocol credentials is just $5 USD. Vendors are selling products in bundles, with plug-and-play malware kits, malware-as-a-service, tutorials, and mentoring services reducing the need for technical skills and experience to conduct complex, targeted attacks – in fact, just 2-3% of threat actors today are advanced coders1.
  • The irony of ‘honor amongst cyber-thieves' – Much like the legitimate online retail world, trust and reputation are ironically essential parts of cybercriminal commerce: 77% of cybercriminal marketplaces analyzed require a vendor bond – a license to sell – which can cost up to $3,000. 85% of these use escrow payments, and 92% have a third-party dispute resolution service. Every marketplace provides vendor feedback scores. Cybercriminals also try to stay a step ahead of law enforcement by transferring reputation between websites – as the average lifespan of a dark net Tor website is only 55 days.
  • Popular software is giving cybercriminals a foot in the door – Cybercriminals are focusing on finding gaps in software that will allow them to get a foothold and take control of systems by targeting known bugs and vulnerabilities in popular software. Examples include the Windows operating system, Microsoft Office, web content management systems, and web and mail servers. Kits that exploit vulnerabilities in niche systems command the highest prices (typically ranging from $1,000-$4,000 USD). Zero Days (vulnerabilities that are not yet publicly known) are retailing at 10s of thousands of dollars on dark web markets.

"Unfortunately, it's never been easier to be a cybercriminal. Complex attacks previously required serious skills, knowledge and resource. Now the technology and training is available for the price of a gallons of gas. And whether it's having your company ad customer data exposed, deliveries delayed or even a hospital appointment cancelled, the explosion in cybercrime affects us all," comments report author Alex Holland, Senior Malware Analyst at HP Inc.

"At the heart of this is ransomware, which has created a new cybercriminal ecosystem rewarding smaller players with a slice of the profits. This is creating a cybercrime factory line, churning out attacks that can be very hard to defend against and putting the businesses we all rely on in the crosshairs," Holland adds.

HP consulted with a panel of experts from cybersecurity and academia – including ex-black hat hacker Michael ‘Mafia Boy' Calce and authored criminologist, Dr. Mike McGuire – to understand how cybercrime has evolved and what businesses can do to better protect themselves against the threats of today and tomorrow. They warned that businesses should prepare for destructive data denial attacks, increasingly targeted cyber campaigns, and cybercriminals using emerging technologies like artificial intelligence to challenge organizations' data integrity.

To protect against current and future threats, the report offers up the following advice for businesses:

Master the basics to reduce cybercriminals' chances: Follow best practices, such as multi-factor authentication and patch management; reduce your attack surface from top attack vectors like email, web browsing and file downloads; and prioritize self-healing hardware to boost resilience.

Focus on winning the game: plan for the worst; limit risk posed by your people and partners by putting processes in place to vet supplier security and educate workforces on social engineering; and be process-oriented and rehearse responses to attacks so you can identify problems, make improvements and be better prepared.

Cybercrime is a team sport. Cybersecurity must be too: talk to your peers to share threat information and intelligence in real-time; use threat intelligence and be proactive in horizon scanning by monitoring open discussions on underground forums; and work with third-party security services to uncover weak spots and critical risks that need addressing.

"We all need to do more to fight the growing cybercrime machine," says Dr. Ian Pratt, Global Head of Security for Personal Systems at HP Inc. "For individuals, this means becoming cyber aware. Most attacks start with a click of a mouse, so thinking before you click is always important. But giving yourself a safety net by buying technology that can mitigate and recover from the impact of bad clicks is even better."

"For businesses, it's important to build resiliency and shut off as many common attack routes as possible," Pratt continues. "For example, cybercriminals study patches on release to reverse engineer the vulnerability being patched and can rapidly create exploits to use before organizations have patched. So, speeding up patch management is important. Many of the most common categories of threat such as those delivered via email and the web can be fully neutralized through techniques such as threat containment and isolation, greatly reducing an organization's attack surface regardless of whether the vulnerabilities are patched or not."

You can read the full report here https://threatresearch.ext.hp.com/evolution-of-cybercrime-report/

Media contacts:
Vanessa Godsal / vgodsal@hp.com

About the research

The Evolution of Cybercrime – The Evolution of Cybercrime: Why the Dark Web is Supercharging the Threat Landscape and How to Fight Back – an HP Wolf Security Report is based on findings from:

  1. An independent study carried out by dark web investigation firm Forensic Pathways and commissioned by HP Wolf Security. The firm collected dark web marketplace listings using their automated crawlers that monitor content on the Tor network. Their Dark Search Engine tool has an index consisting of >35 million URLs of scraped data. The collected data was examined and validated by Forensic Pathway's analysts. This report analyzed approximately 33,000 active websites across the dark web, including 5,502 forums and 6,529 marketplaces. Between February and April 2022, Forensic Pathways identified 17 recently active cybercrime marketplaces across the Tor network and 16 hacking forums across the Tor network and the web containing relevant listings that comprise the data set.
  2. The report also includes threat telemetry from HP Wolf Security and research into the leaked communications of the Conti ransomware group.
  3. Interviews with and contributions from a panel of cybersecurity experts including:
    • Alex Holland, report author, Senior Malware Analyst at HP Inc.
    • Joanna Burkey, Chief Information Security Officer at HP Inc.
    • Dr. Ian Pratt, Global Head of Security for Personal Systems at HP Inc.
    • Boris Balacheff, Chief Technologist for Security Research and Innovation at HP Labs, HP Inc.
    • Patrick Schlapfer, Malware Analyst at HP Inc.
    • Michael Calce, former black hat "MafiaBoy", HP Security Advisory Board Chairman, CEO of decentraweb, and President of Optimal Secure.
    • Dr. Mike McGuire, senior lecturer of criminology at the University of Surrey, UK and authored expert on cybersecurity.
    • Robert Masse, HP Security Advisory Board member and Partner at Deloitte.
    • Justine Bone, HP Security Advisory Board member and CEO at Medsec.

About HP

HP Inc. is a technology company that believes one thoughtful idea has the power to change the world. Its product and service portfolio of personal systems, printers, and 3D printing solutions helps bring these ideas to life. Visit http://www.hp.com.

About HP Wolf Security

From the maker of the world's most secure PCs2 and Printers3, HP Wolf Security is a new breed of endpoint security. HP's portfolio of hardware-enforced security and endpoint-focused security services are designed to help organizations safeguard PCs, printers, and people from circling cyber predators. HP Wolf Security provides comprehensive endpoint protection and resiliency that starts at the hardware level and extends across software and services.

©Copyright 2022 HP Development Company, L.P. The information contained herein is subject to change without notice. The only warranties for HP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HP shall not be liable for technical or editorial errors or omissions contained herein.


1 According to Michael Calce, former black hat "MafiaBoy", HP Security Advisory Board Member, CEO of decentraweb, and President of Optimal Secure
2 Based on HP's unique and comprehensive security capabilities at no additional cost among vendors on HP Elite PCs with Windows and 8th Gen and higher Intel® processors or AMD Ryzen™ 4000 processors and higher; HP ProDesk 600 G6 with Intel® 10th Gen and higher processors; and HP ProBook 600 with AMD Ryzen™ 4000 or Intel® 11th Gen processors and higher.
3 HP's most advanced embedded security features are available on HP Enterprise and HP Managed devices with HP FutureSmart firmware 4.5 or above. Claim based on HP review of 2021 published features of competitive in-class printers. Only HP offers a combination of security features to automatically detect, stop, and recover from attacks with a self-healing reboot, in alignment with NIST SP 800-193 guidelines for device cyber resiliency. For a list of compatible products, visit: hp.com/go/PrintersThatProtect. For more information, visit: hp.com/go/PrinterSecurityClaims.


© 2022 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.

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Thu, 21 Jul 2022 04:40:00 -0500 text/html https://www.benzinga.com/pressreleases/22/07/g28155967/stolen-credentials-selling-on-the-dark-web-for-price-of-a-gallon-of-gas
Killexams : The Market Is Teeming: Bargains on Dark Web provide Novice Cybercriminals a Quick Start

Would-be cybercriminals can easily buy advanced tools, common exploits, and stolen credentials on underground markets for a few dollars — a low barrier to entry for novices, according to a study of 33,000 Dark Web marketplaces.

According to new analysis from HP Wolf Security and researchers at Forensic Pathways, there are plenty of bargains to be had. Out of the 174 exploits found advertised on the Dark Web, 91% cost less than $10, while 76% of the more than 1,650 advertisements for malware have a similar price.

Other common attacker assets also have similarly low prices: The average cost, for example, for stolen credentials for accessing a Remote Desktop Protocol (RDP) instance is just $5.

While more advanced malware groups use private forums to trade zero-day exploits, the available credentials, exploits, and tools on offer in the wider underground economy allow novices to quickly create a credible toolset, says Alex Holland, senior malware analyst at HP and primary author of the report.

Novice cybercriminals "can use a freely available open source tool, and — as long as you are skilled enough to encrypt, use a packer, use techniques to evade defenses — then that tool will do a perfectly good job," he says.

Dark Web pricing from HP report.
The vast majority of exploits and malware are sold on the Dark Web for less than $10. Source: HP's The Evolution of Cybercrime report.

The study of Dark Web marketplaces analyzed approximately 33,000 active sites, forums, and marketplaces over a two-month period, finding that the market for basic tools and knowledge is well entrenched, and attracting new customers all the time.

The increase in the number of threat actors could mean businesses will find their operations targeted even more than they are today, according to Michael Calce, HP Security Advisory Board member and former hacker (aka MafiaBoy). HP brought in criminologists and former hackers to help put the study in context.

"Today, only a small minority of cybercriminals really code, most are just in it for the money — and the barrier to entry is so low that almost anyone can be a threat actor," Calce says in the report. "That's bad news for businesses."

To protect themselves from the swelling ranks of cyberattackers, HP recommends that companies do the basics, using automation and best practices to reduce their attack surface area. In addition, businesses need to regularly conduct exercises to help plan for and respond to the worst-case attacks, as attackers will increasingly attempt to limit executives choices following an attack to make ransom payments the best worst option.

"If the worst happens and a threat actor breaches your defenses, then you don't want this to be the first time you have initiated an incident response plan," Joanna Burkey, chief information security officer at HP, says in the report. "Ensuring that everyone knows their roles, and that people are familiar with the processes they need to follow, will go a long way to containing the worst of the impact."

Cybercrime Convergence: Nation-State Tactics Blend With Financial Campaigns

The report also found that advanced actors are becoming more professional, using increasingly destructive attacks to scale up the pressure on victims to pay. At the same time, financially motivated cybercriminals groups continue to adopt many of the tactics used by high-end nation-state threat actors.

These especially focus on living-off-the-land attacks where the attacker uses system administration tools to avoid endpoint-detection systems that would otherwise flag malware, according to HP.

While the shift likely comes from the transfer of knowledge as cybercriminals become more skillful and learn the latest tactics used by advanced persistent threats, a number of groups are also blending nation-state activities—such as cyberespionage — and cybercriminal activities aimed at turning a profit. The leak of text messages from the Conti group highlighted that the members occasionally conducted operations at the request of at least two Russian government agencies.

Ransomware Is Here to Stay

Elsewhere in the report, researchers note that ransomware gangs will focus on timing their attacks to put the most pressure on organizations, such as attacking retailers during the holiday seasons, the agriculture sector during harvest seasons, or universities as students return to school. 

Ransomware has declined in the first half of the year for various reasons, but HP sees the trend as temporary.

"We don't see ransomware going away, but we do see it evolving over time," Holland says. "Ransomware attacks will actually become more creative."

Enforcing Ethics on the Dark Web

The study also found that trust continues to be a major problem for Dark Web markets in the same way that online businesses have had to deal with fraud and bad actors. The Dark Web, of course, has facets that make trust even harder to come by: A website on the anonymous Tor network, for example, has an average lifespan of 55 days, according to the researchers.

To ensure that vendors and customers play fair, the marketplaces have adopted many of the same strategies as legitimate businesses. Vendors are usually required to offer a bond of thousands of dollars to ensure trust. Customers can leave ratings on every marketplace. And escrow payments have become commonplace, with 85% of transactions using escrow payment systems.

Thu, 21 Jul 2022 04:51:00 -0500 en text/html https://www.darkreading.com/threat-intelligence/market-bargains-dark-web-novice-cybercriminals-quick-start
Killexams : Agricultural Tractor Market Size to Reach USD 90.11 Billion by 2030, Says The Brainy Insights

Brainy Insights Pvt. Ltd.

The increasing adoption of advanced & new technology in the agriculture sector to increase productivity worldwide is one of the driving factors of the market growth.

Newark, Aug. 03, 2022 (GLOBE NEWSWIRE) -- As per the report published by The Brainy Insights, the global agricultural tractor market is expected to grow from USD 63.25 billion in 2021 to USD 90.11 billion by 2030, at a CAGR of 4.01% during the forecast period 2022-2030.

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The rise in farm mechanizations and raised inclination for the more miniature power output tractors are anticipated to expand demand for the agricultural tractor market during the projection period. Further, the increase in demand for high efficient tractors for different applications like planting, sowing, and others are the driving factors of the market growth. Moreover, the high operational price, massive cost of agriculture tractors, and regular service needs are the restraining factors of the market growth. Furthermore, a government enterprise for helping and delivering subsidies to farmers with low-interest rates is an opportunity for market growth.
Competitive Strategy

To enhance their market position in the global agricultural tractor market, the key players are now focusing on adopting the strategies such as product innovations, mergers & acquisitions, latest developments, joint ventures, collaborations, and partnerships.

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Market Growth & Trends

The growth of the agricultural tractor market is driven by the need to increase yield and increase cultivation activities in limited arable land. Moreover, the inclination of farmers toward high-powered tractors to raise productivity, the introduction of driverless tractors, and other technological innovations are also helping to propel market growth. Further, the market growth trend is exponential growth in the worldwide population and supportive governments' policies. Some key market trends are technological innovation, limited labor accessibility, rapid urbanization, and increasing food consumption. Moreover, when simple supply-demand economics and the flow of labor from urban to rural places are considered, farm labor prices are directly correlated with the percentage of a nation's entire population utilized in agriculture.
Additionally, farmers are anticipated to boost their yields as the population & demand for food rise. Thus, agricultural tractors play a vital role in increasing agricultural output in India. These factors help to drive market growth. Further, the improved efficiency & productivity of crop yield and the increasing awareness of progressive farming techniques are also helping to boost the market growth.

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Key Findings

• In 2021, the 41 HP to 99 HP segment dominated the market with the largest market share of 29.17% and market revenue of 18.45 billion.

The horse powers segment is divided into more than 150 HP, 100 HP to 150 HP, 41 HP to 99 HP, and below 40 HP. In 2021, the 41 HP to 99 HP segment dominated the market with the largest market share of 29.17% and market revenue of 18.45 billion. This growth is attributed to the adoption of row-crop farming structures and horticulture.

• In 2021, the 4-wheel drive (4WD) segment dominated the market with the largest market share, 56.11%, and market revenue of 35.48 billion.

The drive segment is divided into the 2-wheel drive (2WD)) and 4-wheel drive (4WD). In 2021, the 4-wheel drive (4WD) segment dominated the market with the largest market share of 56.11% and market revenue of 35.48 billion. This growth is attributed to increased fuel efficiency, stability, safety, and driving control.

• In 2021, the irrigation segment dominated the market with the largest market share of 42.14% and market revenue of 26.65 billion.

The application segment is divided into seed sowing, harvesting, and irrigation. In 2021, the irrigation segment dominated the market with the largest market share of 42.14% and market revenue of 26.65 billion. This growth is attributed to the increasing adoption of intelligent technologies.

• In 2021, the orchard tractors segment dominated the market with the largest market share of 30.02% and market revenue of 18.98 billion.

The tractor type segment is divided into row-crop tractors, pedestrian tractors, wheeled tractors, orchard tractors. In 2021, the orchard tractors segment dominated the market with the largest market share of 30.02% and market revenue of 18.98 billion. This growth is attributed to the requirements of an expanding population and increasing food demand.

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Regional Segment Analysis of the Agricultural Tractor Market:

• North America (U.S., Canada, Mexico)
• Europe (Germany, France, U.K., Italy, Spain, Rest of Europe)
• Asia-Pacific (China, Japan, India, Rest of APAC)
• South America (Brazil and the Rest of South America)
• The Middle East and Africa (UAE, South Africa, Rest of MEA)

Asia-Pacific region occurred the largest market for the global agricultural tractor market, with a market share of 48.32 % and a market value of around 30.56 billion in 2021. Asia-Pacific currently dominates the agricultural tractor market due to the raised demand for large farm tractors. Additionally, the ever-increasing disposable income among the farmers and the fact that a higher proportion of the population is involved in agriculture in nations like India are also helping to drive market growth. Furthermore, the North American region is expected to show the fastest CAGR of 6.04% over the projection period. This growth is attributed to the rising mechanization of agriculture equipment and the growing adoption of automated methods. Moreover, the increased product output by supply chain procedure optimization will likely support the market's growth during the projection period.

Key players operating in the global agricultural tractor market are:

• Mahindra Group
• Deere & Company
• Yanmar
• Kutoba Corporation
• Dongfeng
• Massey Ferguson
• SDF Group
• Farmtac
• New Holland
• Kioti Tractor
• Argo Tractors S.p.A.
• Valtra Tractor
• CNH Industrial N.V.

This study forecasts revenue at global, regional, and country levels from 2019 to 2030. The Brainy Insights has segmented the global agricultural tractor market based on below mentioned segments:

Global Agricultural Tractor Market by Horse Powers:

• More than 150 HP
• 100 HP to 150 HP
• 41 HP to 99 HP
• Below 40 HP

Global Agricultural Tractor Market by Drive:

• 2-Wheel Drive (2WD)
• 4-Wheel Drive (4WD)
Global Agricultural Tractor Market by Application:
• Seed Sowing
• Harvesting
• Irrigation

Global Agricultural Tractor Market by Tractor Type:

• Row-crop Tractors
• Pedestrian Tractors
• Wheeled Tractors
• Orchard Tractors

About the report:

The global agricultural tractor market is analysed based on value (USD Billion). All the segments have been analysed on global, regional and country basis. The study includes the analysis of more than 30 countries for each segment. The report offers in-depth analysis of driving factors, opportunities, restraints, and challenges for gaining the key insight of the market. The study includes porter’s five forces model, attractiveness analysis, raw material analysis, supply, demand analysis, competitor position grid analysis, distribution and marketing channels analysis.

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The Brainy Insights is a market research company, aimed at providing actionable insights through data analytics to companies to Boost their business acumen. We have a robust forecasting and estimation model to meet the clients' objectives of high-quality output within a short span of time. We provide both customized (clients' specific) and syndicate reports. Our repository of syndicate reports is diverse across all the categories and sub-categories across domains. Our customized solutions are tailored to meet the clients' requirement whether they are looking to expand or planning to launch a new product in the global market.

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Wed, 03 Aug 2022 00:17:00 -0500 en-AU text/html https://au.sports.yahoo.com/agricultural-tractor-market-size-reach-121700495.html
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