The Covid-19 pandemic has driven the rhetoric around cloud computing into overdrive. However, there is a right size for everything, including the corporate commitment to cloud.

When public cloud computing first hit, early adopters and pundits were quick to say it was the future, full stop. Later on, as the market has continued to mature, there is now a second generation adding to the chorus of all-cloud computing.

General cloud and SaaS technologies have a lot going for them. Between simplification, ease of access for employees not on site, and the reduction of equipment and software that IT staff have to maintain, cloud technologies can do wonderful things for a business.

But the absolutist position that everything has to go into the cloud is one that most companies should avoid. Because no matter how accommodating and easy to use cloud is, it represents a loss of control. Decisions made by a third party, or even mistakes made by a third party can have detrimental effects. For a lot of functions, considering the good track record of the major cloud suppliers to date, this is a pretty easy risk/benefit calculation to make.

However, things that are core to the company, things that have a direct effect on serving the customer, such as manufacturing control for instance, require a different risk/benefit calculation. Systems that are absolutely critical to the core function of a company require a more hands-on approach, where keeping these functions in house, or at least redundant in house should be considered.

The rise of Edge Computing, systems designed to be near the end point to handle fast response and local data processing is the perfect example of the cloud model not really being one-size-fits-all. Edge Computing wouldnt exist otherwise. Locations with limited or poor connectivity are another good example of how cloud cannot do it all.

Companies can and should embrace cloud computing and in some cases even move the majority of their IT functions to the cloud. However, the core tenant of digital business is improved customer experience and engagement. Viewed in that light, cloud might be the solution for many problems, but not all problems.

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Why cloud computing isn't the answer to all business problems - Verdict

Analysis I have worked on SAP engagement for enterprise customers for almost 30 years. While SAP continued to develop application features and content during these years, generally the hosting of SAP fell into the same classic selection process as any application: what is the service level, what is the cost, who has the happiest customers?

However, with the advent of public cloud (IaaS), those tried and tested criteria no longer give customers an accurate evaluation of each option. As such, here are some of the key criteria SAP customers need to include in their evaluation of hosting options.

Of course, cost comes first in most scenarios. Nothing happens in an enterprise without a good business case. However, at first glance, negotiated costs can be deceiving. Enterprise agreements, short-term discounts, migration funding and more can all muddy the waters when it comes to getting a clear perspective of the pricing you are signing up for. In order to best predict what future costs will look like, its important to understand the hyperscalers attitude towards cost, and then extrapolate their pricing history.

Additionally, with hyperscaler infrastructure comes the great benefit of metered charging, where you only pay for what you use resulting in variable costs. While this is actually a very good thing in general, it can cause headaches for procurement and necessitate new processes for IT to properly manage these variable costs. When selecting a provider, you need to understand which hyperscaler/partner can best help you see and control ongoing metered costs.

Nowadays, we expect public cloud to be more resilient than on-premise. And, while this is generally true, not all clouds are equal especially for applications such as SAP. You will need to evaluate the amount of downtime each hyperscaler has experienced over the last 12-18 months to get a sense of how they compare. SLAs are one thing historic performance is a much better guide.

Publicly published statistics on hyperscaler downtime show that AWS fares far better than Azure and better or similar to Google Cloud Platform. SAP, as we know, is very sensitive to downtime especially unplanned downtime. Choosing the most stable platform is an important part of the selection criteria for all your systems but particularly for SAP given its criticality to the business.

The best innovation is happening in the cloud these days and, as everything is or will be in the cloud eventually, innovation and speed to innovation needs to be an integral part of your IT road map for the next 10 years at least. Right now, AWS is the leader in getting new innovations and new ideas to the market quickly. Azure categorizes itself as fast followers, which is an important but safer position in the market. Google, while very good at what they do around data items and other categories, does not display the same customer obsession and innovation focus in its cloud capacities as its competitors.

Why does this matter? When looking at innovation, particularly the speed of innovation, you need to also consider the technology adoption cycle. This is the timeframe from when the new technology is introduced to when it is ultimately retired. When the adoption cycles of innovation among hyperscalers reach a one to two-year difference, this becomes a critical differentiator. Some would say that right now, AWS is already one to two years ahead of its competitors meaning that the technology that gets introduced by them will release, runs its cycle and be retired by the time it gets to other cloud providers. Selecting the most innovative platform is critical for any long-term strategic decisions.

AWS has always led the way on the most performant technology, both on storage and compute. What AWS has done recently is launch all of their instances based on their nitro hypervisor which takes all the hypervisor load off the VM and allows the workloads to get access to all of the resource on compute. Nitro was, in effect, an add-on component to every VM. This allows for unparalleled performance.

Additionally, AWS is innovating into its own chips and own chip design, and is releasing its G Class of families which have already shown to be not just cheaper but higher performing than other chip providers. This gives every indication that AWS will continue to lead the way on performance. When running SAP, one of the biggest complaints end users typically have is a lack of performance. Overall performance and performance when you need it is one of the biggest benefits IT departments can give to their customers so choosing the most performant platform for your systems is table stakes.

Another benefit of public cloud is that it has an open API. This means that it is a publicly available application programming interface so developers in offices (and garages and living rooms) all over the world are coding. This is an example of hyperscalers and their partner ecosystems adding a significant amount of additional innovation that their customers can access directly. As a result, we consistently see brand new use cases for BI, speech, chatbotting and other great technologies that can integrate very simply with public cloud.

This proves once again that public cloud is a platform best suited for future innovation. It also suggests that the amount of innovation is directly related to the number of partners that hyperscalers have as part of their ecosystem. AWS has, by far, the most, and that is very important if you want to have access to these third-party capabilities. You will probably find that they enable these capabilities for AWS before any other hyperscaler. The more customers that are on a platform, the more partners will do development there which means the more traction there is for the new customers. This network effect is something that AWS has done well for 10 years and is something that is very difficult for others to catch up on.

Ultimately, automation is the most important secret ingredient of them all. Automation not only allows you to do things automatically, remotely and quickly, but also with more quality. Quality builds for installed software systems, like SAP, are essential.

Classically run on-premise, most people spend their time trying to keep the lights on for SAP and maintaining and fixing things manually. The downside of that is people make mistakes. Manual steps are inherently risky, and you could end up with situations where Dev might have a different kernel patch version than COS, which might have a different version than Production. Suddenly, you get unexpected defects when you run workloads on production. The way to avoid this is through automation. Automation will remove the manual errors and ensure that there is a repeatable and reliable process for both the build and maintenance of the SAP landscape. This higher quality ensures that you can reduce the noise in the environment and reduce the amount of work and cost to maintain the system.

Another plus of automation is the agility it enables. Suddenly, you can do things faster. So, when users want a system refresh, or a restore from a backup, or to patch a system, these things can now be done much more quickly. And, with automation, you can surface it into a portal that will allow end users or project team members to self-serve on the maintenance of the landscape. This agility delivers satisfaction to the project team as they can try out new ideas quickly. This is, of course, the fundamental premise of innovation the ability to try something quickly, fail at it fast or, if it does work, promote it quickly into production. If you want to innovate, you need to be agile, and if you want to be agile you must automate.

Picture credit: SAP

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AWS, Azure or Google? Six steps to decide the best cloud for SAP implementations - Cloud Tech

The news: IBM has built a new chemistry lab called RoboRXN in the cloud. It combines AI models, a cloud computing platform, and robots to help scientists design and synthesize new molecules while working from home.

How it works: The online lab platform allows scientists to log on through a web browser. On a blank canvas, they draw the skeletal structure of the molecular compounds they want to make, and the platform uses machine learning to predict the ingredients required and the order in which they should be mixed. It then sends the instructions to a robot in a remote lab to execute. Once the experiment is done, the platform sends a report to the scientists with the results.

IBM RESEARCH

Why it matters: New drugs and materials traditionally require an average of 10 years and $10 million to discover and bring to market. Much of that time is taken up by the laborious repetition of experiments to synthesize new compounds and learn from trial and error. IBM hopes that a platform like RoboRXN could dramatically speed up that process by predicting the recipes for compounds and automating experiments. In theory, it would lower the costs of drug development and allow scientists to react faster to health crises like the current pandemic, in which social distancing requirements have caused slowdowns in lab work.

Not alone: IBM is not the only one hoping to use AI and robotics to accelerate chemical synthesis. A number of academic labs and startups are also working toward the same goal. But the concept of allowing users to submit molecules remotely and receive analysis on the synthesized molecule is a valuable addition of IBMs platform, says Jill Becker, the CEO of one startup, Kebotix: With RoboRXN, IBM takes an important step to speed up discovery.

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IBM has built a new drug-making lab entirely in the cloud - MIT Technology Review

To provide detailed information about the key factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the growth of the market.

This press release was orginally distributed by SBWire

Northrook, IL -- (SBWIRE) -- 08/26/2020 -- According to a research report "Cloud Computing Market by Service Model (Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)), Deployment Model (Public and Private), Organization Size, Vertical, and Region - Global Forecast to 2025", size is expected to grow from USD 371.4 billion in 2020 to USD 832.1 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 17.5% during the forecast period. The flexibility and agility of cloud-based models would support the IT service needs of enterprises. The leading CSPs/hyperscalersMicrosoft, Alphabet, IBM, and AWSare expected to increase their CAPEX primarily for data center expansion to support the increasing workload for their internal and external stakeholders. The increasing volume of data generation in websites and mobile apps, rising focus on delivering customer-centric applications for driving customer satisfaction, and growing need to control and reduce Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) are a few factors driving the growth of the emerging technologies. The emerging technologies, such as big data, Artificial Intelligence (AI), and Machine Learning (ML) are gaining traction which is ultimately leading to the growth of the cloud computing market, globally.

Browse 360 market data Tables and 75 Figures spread through 320 Pages and in-depth TOC on "Cloud Computing Market - Global Forecast to 2025"

Download PDF Brochure: https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=234

The sudden shutdown of offices, schools, colleges, and physical retail stores has massively disrupted operations; this has led to an increase in the demand for digital workplace tools and services, such as Zoom, Slack, Blackboard, Lynda, Canvas, Google Classroom, AnyMeeting, and Moodle. AWS, Microsoft, and Google host and manage all applications in a public cloud environment. Increased spend on cloud services by select industries due to COVID-19. Industries, such as IT and ITeS, telecom, online retail/commerce, media, and BFSI, are expected to increase spending on cloud-based services to sustain their business. Highly regulated and cash-rich industries, such as BFSI, are also expected to move selective workloads to public cloud environments.

Growth of IaaS to be driven by increasing need of enterprises to shift enterprise workloads to cloud

The key features of IaaS include automated administrative tasks, dynamic scaling, platform virtualization, and network connectivity. The ever-changing business environment and customer demands encourage enterprises to increase their focus on their core business operations. IaaS enables enterprises to leverage their IT infrastructure without paying for the construction of the physical infrastructure. Moreover, it provides flexibility, mobility, easy, and scalable access to applications, and enhanced collaboration to help enterprises focus on their core businesses.

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Lower cost and increased security capabilities result in rising popularity of public cloud

The services offered over the public deployment model are either free or offered under a subscription model. The advantages of using the public cloud include simplicity and ease of deployment. Moreover, the initial investment required for the deployment is minimum, and there are no responsibilities involved in managing the infrastructure.

North America to dominate the global cloud computing market in 2020

North America is a mature market in terms of cloud computing services adoption, owing to a large presence of enterprises with advanced IT infrastructure and the availability of technical expertise. BFSI, IT and telecommunications, and government and public sector verticals majorly adopt cloud computing services. As the benefits of adopting cloud computing services are becoming more evident, more companies are expected to implement cloud computing services. The US and Canada are the top countries contributing to the growth of cloud computing market in North America.

The report also studies various growth strategies, such as mergers and acquisitions, partnerships and collaborations, and developments, adopted by the major players to expand their presence in the global cloud computing market. The cloud computing market includes major vendors, such as AWS (US), Microsoft (US), Google (US), Alibaba (China), SAP (Germany), IBM (US), Oracle (US), VMware (US), Rackspace (US), Salesforce (US), Adobe (US), CenturyLink (US), Fujitsu (Japan), Workday (US), Infor (US), Sage Group (UK), Intuit (US), Epicor (US), IFS (Sweden), ServiceNow (US), OpenText (US), Cisco (US), Box (US), Zoho (US), Citrix (US), Upland Software (US), DigitalOcean (US), Bluelock (US), OVH (France), Joyent (US), Skytap (US), Virtuestream (US), Tencent (China), DXC (US), NEC (Japan), and Navisite (US).

About MarketsandMarketsMarketsandMarkets provides quantified B2B research on 30,000 high growth niche opportunities/threats which will impact 70% to 80% of worldwide companies' revenues. Currently servicing 7500 customers worldwide including 80% of global Fortune 1000 companies as clients. Almost 75,000 top officers across eight industries worldwide approach MarketsandMarkets for their painpoints around revenues decisions.

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Cloud Computing Market Witness the Growth of $832.1 Billion by 2025 - Press Release - Digital Journal

By Ashish Dubey, VP Solutions Architecture, Qubole

As more and more businesses move from on-premise infrastructure to the cloud to benefit from cost saving, efficiency, speed and a democratization of data access, CFOs are glancing nervously at the rising cost of cloud overruns. Cloud sprawl, an unfettered proliferation of your organizations cloud instances due to lack of real time control of cloud computing resources is a real problem plaguing data-driven organizations.

While recent competition between various cloud service providers (Amazon, Google and Microsoft) have benefited customers, failing financial governance of cloud computing costs threaten to dilute the delta gains companies have been experiencing as a result of harnessing the potential of big data like improved customer experience and product development roadmaps.

The Case for Strong Financial Governance

A marked difference between on-premise infrastructure costs (large upfront commitments for long term savings) versus cloud infrastructure is the on demand, per instance usage of cloud computing resources. A rather simplified comparison is signing up for a highly optimized data package from your ISP but burning through large usage pools of bandwidth without real time checks and filters. This can lead to unwanted surprises in your cloud bill. Governance is what keeps the checks and balances in place and is essentially a series of everyday tasks that are critical to keeping accountability and control on cloud spends.

Moving to the cloud has fewer risks today. The move, done with proper planning and POCs is easy and not very time consuming. Most cloud payment models are pay as you go and on-demand so organizations do not see a hefty upfront bill. Howeveras cloud projects mature, use cases and instances get layered, more complex; the danger for a runaway cloud bill goes up. Its easy to bucket some of the reasons for this. As application requests are not known in advance, server allocations are made in advance thereby increasing server running time. Most web applications are engineered to reduce latency (for better customer experience) rather than costs. This means we have to forego the on-demand advantage that cloud servers allow for changing workloads and leads to poor performance optimization.

While most applications are designed assuming gradual increase and decrease of data processing requirements, in the real world data can represent burstiness which sharply increases the need for more servers. This is complementary to the concept of idle time as well. Most web applications can have a steady traffic flow but large workloads can be scattered through the day, leading to idle times when usage is much lower.

How Can Organisations Strengthen Financial Governance?

One IDC report showed that cloud infrastructure spending went up 23.8% in 2019 from the year before and estimates that it could further go up by as much another 43% by 2022. Whilst traceability and predictability are important elements in financial governance policies, cost control, and expense reduction is usually the starting focus of any financial governance exercise. There are ways for organizations to mitigate these costs:

Optimize for performance while accounting for speed of query execution as well as timeliness of execution By prioritizing capacity management as an ongoing exercise by building systems that let teams build faster by nor worrying about unexpected costs by having financial guard rails tomaintain traceability and predictability on user, cluster and job cost metrics level.

Adopting Data Platforms with Built-In Financial Governance Metrics

More mature applications can leverage modern technology platforms involving AI/ML to drive stronger governance. Enterprises should look at platforms which enable Workload Aware Autoscaling in order to strengthen the financial governance within an organization. This will help support multiple teams run big data in a shared cloud environment or separate ones which can be combined to deliver more savings without compromising performance. Additionally, it also needs to include the strong tenets of Optimized Upscaling to reclaim and reallocate unused resources, Aggressive Downscalingto prevent cost overruns due to idle nodes,Container Packing as a resource allocation strategy and Diversified Spot which reduces the chances of bulk interruption of Spot nodes by your Cloud Provider.

To summarise, it is important to have a granular visibility of your infrastructure spend at a job, cluster, or cluster instance levels. This adds myriad benefits to track costs, monitor show-back, justify business plans, prepare budgets, and build ROI analyses. The foundation of robust financial governance of data costs is built by providing data teams the tools to view and make corrections to infrastructure needs immediately irrespective of application complexity and data analytics requirements.

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Financial Governance for Big Data in the Cloud - Express Computer