Hiring a digital marketer starts as soon as you plan to launch a prototype of your innovative idea. But, without knowing anything about digital marketing, you may not be able to reach out to investors and target audiences. You can follow the following basic points to know the significance of digital marketing even if you are not doing it on your own.

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Research published earlier this year by the Cloud Industry Forum (CIF) revealed that the rate of cloud adoption by UK-based businesses has reached 88%. The top three reasons respondents gave for cloud take-up were delivery flexibility, operational cost savings and scalability.

For many businesses, public cloud has been an attractive, effective way to build out their existing models and experiment with new ones, but it has often been oversold and under-performed. In my view, we’ll see a retreat from the public cloud in 2018, especially for storage of highly critical applications, and a return to on-site solutions for various reasons.

First, public cloud still requires an army of people to manage it. While many public cloud companies provide the cloud platform, they don’t provide the manpower or resources to manage it. This means the company utilising the platform has to provide the resources and time required to maintain it, both of which cost money. For anything other than short-term storage, these costs eventually add up. In particular, management costs for the public cloud are more expensive than organisations first expected.

Second, the availability of the public cloud was well-publicised in 2017, but so were the failure issues that came with it. For example, Amazon’s S3 service experienced an outage in February after an employee accidentally typed an incorrect command in the system, resulting in platforms such as Slack and Quora being down for four hours. Other public cloud giants that experienced significant outages in 2017 include IBM and Microsoft Azure. This highlights the risks associated with companies using public cloud to store critical or sensitive data, and has emphasised the importance of companies keeping greater control over that data. We predict this will lead companies to reconsider their storage strategies moving forward, particularly from a data protection, storage and management point of view.

Finally, as alluded to above, many organisations are realising that – at least for long-term storage – public cloud can more often than not turn out to be more expensive than similar on-premises solutions. To start, the advertised price of the public cloud often demonstrates the initial cost of use, but, as organisations become tied into paying recurring monthly fees, and gather larger amounts of data and deploy more extensions, the cost continually increases. Some public cloud platforms also charge per user, so although public cloud promotes unlimited scalability, it can come with a heavy price tag.

New technology that is coming through the pipeline will make it easier for businesses to orchestrate servers and VMs, providing on-premises solutions at a lower cost, and making them as easy to manage and scale as if on a public cloud platform.  That is why, in 2018, I predict that we will see a return to on-premises solutions as companies realise that adopting public cloud may not actually be cheaper or easier to use, particularly with the issue of data security coming to the fore. The adoption rate of public cloud will slow significantly next year as newer, better on-premises solutions come into play.

Ignore the doom and gloom, artificial intelligence (AI) will become a positive job motivator. Moreover, 2020 will be a pivotal year in AI-related employment dynamics, according to the latest worldwide market study by Gartner.

The number of jobs affected by AI will vary by industry. Through 2019, healthcare, the public sector and education will see continuously growing job demand, while manufacturing will be negatively impacted. Starting in 2020, AI-related job creation will cross into positive territory, reaching two million net-new jobs in 2025.

Artificial intelligence market development

"Many significant innovations in the past have been associated with a transition period of temporary job loss, followed by recovery, then business transformation and AI will likely follow this route," said Svetlana Sicular, research vice president at Gartner.

AI will improve the productivity of many jobs, eliminating millions of middle- and low-level positions, but also creating millions more new positions of highly skilled, management and even the entry-level and low-skilled variety.

Unfortunately, most calamitous warnings of job losses confuse AI with automation, that overshadows the greatest benefit from the technology — AI augmentation — which is a combination of human and artificial intelligence, where both can complement each other.

IT leaders should not only focus on the projected net increase of jobs. With each investment in AI-enabled technologies, they must take into consideration what jobs will be lost, what jobs will be created, and how it will transform the way workers collaborate with others, and make decisions.

"Now is the time to really impact your long-term AI direction," said Ms. Sicular. "For the greatest value, focus on augmenting people with AI. Enrich people's jobs, re-imagine old tasks and create new industries. Transform your culture to make it rapidly adaptable to AI-related opportunities or threats."

Gartner identified additional predictions for AI:

• AI has already been applied to highly repeatable tasks where large quantities of observations and decisions can be analyzed for patterns.
• However, applying AI to less-routine work that is more varied due to lower repeatability will soon start yielding superior benefits.
• AI applied to non-routine work is more likely to assist humans than replace them as combinations of humans and machines will perform more effectively than either human experts or AI-driven machines working alone will.
• By 2022, one in five workers engaged in mostly non-routine tasks will rely on AI to do a job.
• Through 2022, multi-channel retailer efforts to replace sales associates through AI will prove unsuccessful, although cashier and operational jobs will be disrupted.
• In 2021, AI augmentation will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity.

"AI can take on repetitive and mundane tasks, freeing up humans for other activities, but the symbiosis of humans with AI will be more nuanced and will require reinvestment and reinvention instead of simply automating existing practices," said Mike Rollings, research vice president at Gartner.

Rather than have a machine replicating the steps that a human performs to reach a particular judgment, the entire decision process can be refactored to use the relative strengths and weaknesses of both machine and human to maximize value generation and redistribute decision making to increase agility.

Editor's note: Read more about artificial intelligence on our sister publication, AI News.

The Toyota Production System, a world-renowned production system is based on the “complete elimination of all waste”. The “Toyota Way”, grounded on continuous improvement dates to the 1860s. The methodology is widely proven to be successful yet there are still industries within and tangential to manufacturing struggling to adopt its core principles:
Jidoka: a process should stop when an issue is identified prevents releasing defective products

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Quantum Computing is becoming quite the hot topic lately. With research being done by Google, IBM, Microsoft, universities, and a number of other players, it’s looking this is really going to happen. In fact, Google may just be weeks away from announcing the Quantum Supremacy milestone. If you aren’t familiar with the concept of Quantum Supremacy yet, it’s basically the point where a quantum computer can complete a computation in a short time where a classical computer can’t complete it at all. This is a big deal. While there are some simple quantum computers out there right now (you can try out IBM’s via the Q Experience), this will be a big deal.

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For better or worse, big data has irrevocably altered the digital landscape. The explosion in variety, velocity, volume and value of information presents an abundance of previously unimaginable opportunity. But it also creates a number of challenges that need to be successfully navigated.
This reshaped technical world poses the following question to organizations: do you risk presenting, stale, incorrect or erroneous data to your customers? Because, with 2.5 quintillion bytes of data now being created every day, finding a way to manage and harness such potential is a new experience for everyone. And if you don’t take advantage, your competitors will.

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In his session at 21st Cloud Expo, Carl J. Levine, Senior Technical Evangelist for NS1, will objectively discuss how DNS is used to solve Digital Transformation challenges in large SaaS applications, CDNs, AdTech platforms, and other demanding use cases. Carl J. Levine is the Senior Technical Evangelist for NS1. A veteran of the Internet Infrastructure space, he has over a decade of experience with startups, networking protocols and Internet infrastructure, combined with the unique ability to iterate use cases, bring understanding to those seeking to explore complicated technical concepts and increase revenue across diverse sales channels.

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Net Neutrality rules were originally enacted to ensure that all Americans would have equal access to a free and open Internet. We can argue about what Net Neutrality rules did and did not accomplish in a moment, but now I want to explore the most sensational of all the post–Net Neutrality fears: the death of the Internet.
If you’re still reading, you know that the FCC voted to repeal Net Neutrality rules (aka the Open Internet) and replace it with the “Restoring Internet Freedom” order. The outcry from the Open Internet camp has been loud, hyperbolic, hypothetical, and mostly based on the fundamental principles of “what if.” For some background and my personal “what if?” musings, read this.

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Just a few years ago, not many predicted cloud computing would reach the heights we’ve seen in 2017 – 79 percent of companies now run workloads in the cloud (split almost evenly between public and private clouds). With the cloud bar constantly being raised, where do we go from here? Here are five predictions for the future of cloud computing in 2018.

True hybrid clouds emerge

Hybrid cloud is all the buzz. The ability for enterprises to have applications run in different infrastructures – public and private clouds and on-premise with common orchestration and management tools – is enticing. Multi-cloud, with different workloads running in different clouds and being managed separately, will become the dominant mode in 2018, while true hybrid clouds will start to emerge.

There are already key technology developments and partnerships forming to make this a reality. For example, Azure and Azure Stack from Microsoft provide a uniform set of infrastructure and API capabilities across public and private clouds; the partnership between VMware and AWS; and the teaming up of Cisco and Google. These mashups will create hybrid clouds that truly blend environments and further improve operational agility, efficiency and scale.

Kubernetes dominates container orchestration

The fight for container orchestration dominance has been one of the cloud’s main events for roughly the past two years. The three-way battle between Docker Swarm, Kubernetes and Mesos has been fierce.

Come 2018, however, Kubernetes is poised to take the container orchestration title belt and also become increasingly mainstream with mission critical, scalable production deployments. Its rich set of contributors, rapid development of capabilities and support across many disparate platforms make it a clear victor.

And it has the help of some very powerful friends: Microsoft Azure and Google Cloud have launched a managed Kubernetes services. IBM has announced its private cloud will support Kubernetes in its Bluemix public cloud; AWS is lining up behind it as well and has joined the Cloud Native Computing Foundation (CNCF) as a platinum member

All this combined pushes Kubernetes into more mainstream deployments with continued growth in large production workloads next year.

Analytics get an AI upgrade

AI is everywhere. It’s in our homes with Amazon Echo. And in 2018, it’ll be embedded more tightly in IT analytics systems making IT proactive versus reactive.

Through predictive analytics, IT and application owners will receive actionable information and recommendations. Add to that the ability to automate their response, and the power of AI becomes more relevant.

Analytics systems will have insight into the behaviour of the infrastructure, apps and clients. It will recognise anomalous performance or security behaviour and when an app or server is going to fail. Once that behaviour is noticed, automation can kick in to remediate the potential problem, i.e. firing up another server or load balancing the app. It’s like your infrastructure can say “Alexa, spin up another server.”

Serverless computing adoption spreads

One of the benefits of cloud is ease of use for spinning up additional resources and its pay by use consumption model. Nowhere is that more evident than in serverless computing. Previously, the unit for additional compute resource was an instance or VM. Now a “function” has become an even smaller unit of “use.” Putting the onus of managing and scaling up resources on demand on the cloud provider is cost-efficient and takes the heavy lifting off IT. And paying based on a consumption model makes it gentler on already strained budgets.

Currently available in the public cloud, next year will see serverless computing start to appear in private cloud deployments as well. While it won’t become mainstream, wider adoption will happen in the short term.

Serverless computing, coupled with the continue maturation of cloud, puts pressure on server and hardware vendors to transform their business models to maintain relevance in the new virtual, elastic and automated cloud-powered world.

Custom cloud instances proliferate

As cloud adoption grows, compute instance types will become further segmented and optimised for specific use cases; enabling improved performance and new use cases. Next year will see growth in the number of application-specific instance types within clouds – from big data and AI-optimised instances to high network performance and very large memory types. Custom optimised applications that take advantage of these capabilities will start appearing.

Bonus prediction: Kiss cloud security concerns goodbye

Security is noticeably absent from our list of cloud predictions. Why? Simple. It’s time to move on.

Yes, security is always important, and even more so in the cloud. But it’s no longer the hindrance it was when cloud was early stages. Over the years, cloud and services available on the cloud have matured. There is more security built in. More tools are available from vendors. Compliance in the cloud has caught up. As with all IT, it’s imperative to think about security capabilities, policies and governance when deploying clouds or making a major change to your infrastructure, but in 2018 cloud will no longer be considered not secure by default.

In the cloud world, things move swiftly. That’s just a snapshot of what we think will be the major trends of 2018. There will certainly be more big headlines in cloud as more people find innovative ways to consume it.