cloud infrastucture

Cloud Transformation, Private Cloud Deployment, Digital Wallets, Datacenter Disruption

Posted on 08. Apr, 2018 by in big data, Cloud, cloud infrastucture, Developement, Hosting, IAAS, internet, linux, Open stack, SAAS, Web Hosting

Cloud Transformation, Private Cloud Deployment, Digital Wallets, Datacenter Disruption

Global Digital Infrastructure Trends

April 6, 2018

In This Issue

Where Are You On the Cloud Transformation Journey? – A 451 Research model shows enterprise cloud costs over time, and enables IT managers to track their progress and experiences relative to other IT organizations.

The Quick and Easy Way to Private Clouds – The build-operate-transfer (BOT) model enables enterprises to tap the expertise of open source providers in order to rapidly build and deploy private clouds – with the option of taking control down the road.

Digital Wallet Usage Steady – The biggest players, Apple Pay and PayPal, remain on top in terms of planned and current use as well as satisfaction, but the field is becoming more crowded with banks and retailers joining the fray with their own payment apps.

Top Ten Technologies to Disrupt the Datacenter – Distributed resiliency topped the list of emerging technologies that will disrupt datacenter operations, but there are nine other potential candidates. In all cases, disruption is good.

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In Case You Missed It

1. Where Are You On the Cloud Transformation Journey?

451 Research’s cloud transformation journey model (see Figure below) shows the enterprise cloud cost experience over time. It identifies the cycles of cloud consumption – migration and implementation, cost savings and cost increases, governance and optimization, and transformative value.

The ups and downs of this journey and the time required to realize value vary by company and by application; with experience and automation, the amplitude of the curve flattens and the time to value shortens.

The Cloud Transformation Journey

Great Expectations

According to a 451 Research survey of IT managers, a primary motivator for cloud adoption is cost savings compared to traditional IT models (see Figure below).

CIOs have great expectations about the cost savings that can be achieved in migrating to the cloud.

But cost isn’t the only driver: The inherent nature of pay-as-you-go pricing and the scalability and time-to-market it enables are also major drivers, as are availability and uptime.

As cloud implementation begins, expenditures grow for migrated applications as a result of switching (migration) costs, but then money is saved by reducing dependence on dedicated IT personnel.

For net new applications, infrastructure costs slowly but surely ramp up. Developers and administrators spin up resources, and then spin up more and more as demand dictates.

However, at this early stage there aren’t enough resources in use to justify tight controls or cost optimization.

Switching cost: For applications currently in use, there are switching costs. At the simplest level, this could be the time and resources associated with migrating applications. At a more complex level, it could be re-architecting and rebuilding entire applications.

But once done, the investments should be worthwhile due to the savings realized.

Consolidation: As enterprises migrate old platforms to the cloud, there are cost savings from increased labor efficiency and higher resource utilization.

Wuthering Heights

Despite the excitement, costs begin to ramp up toward wuthering heights. Post migration, cloud costs are the number one pain point (see Figure below).

Costs increase for two reasons:

  • The Jevons Paradox: Ease of access to technology and lower costs drive developers and administrators to consume more, increasing total costs.
  • Resource sprawl: With ease of access, some resources get orphaned with no ownership, yet these resources continue to incur costs. And some resources are overprovisioned to provide extra capacity as a ‘just in case’ solution.

Unfortunately, the IT department typically has limited visibility or control of these items.

War and Peace

Enterprises now look to reduce costs by purchasing cloud services in alternative ways.

There is a battle between flexibility/convenience and control/governance: Developers want to ‘go to war’ with new capabilities and capacity; administrators want the peace of control and governance.

Price model optimization: To save money, administrators start using alternative pricing models, such as AWS’ reserved or spot instances, Microsoft’s Enterprise Agreements, or Google’s sustained-use pricing models. According to 451 Research’s Cloud Price Index, the average discount is 38%.

Resource governance: Many administrators employ third-party reporting tools to limit usage, based on policy (e.g., project, department, privilege level). Others set up an approval hierarchy for consumption.

Bolder administrators introduce showback and chargeback, making individual departments responsible for their cloud consumption, which reduces expenditures.

Most enterprises are performing some sort of governance, but more than 20% do not track cloud costs (see Figure below).

Repatriation: Some enterprises – typically larger ones – bring workloads back in house. For these organizations, labor and utilization have reached a threshold where private cloud can be cheaper than public cloud (see chart on right below).

When IT managers were asked, ‘Within the last 12 months, has your organization migrated any applications or data from a public cloud to a private cloud or non-cloud environment?’ a whopping 38.6% said ‘yes’ (see chart on left below).

A Brave New World

The key objective now is to squeeze costs while enabling flexible IT consumption. This is the brave new world of utility computing.

Waste management: With governance in place, expenditures slow but inevitably there is waste. Waste management technologies can:

  • Right-size instances
  • Terminate unused resources
  • Ensure that all resources are being consumed

Cost optimization: Manual price optimization struggles to keep up with the complexity. (451 Research’s Cloud Price Index, for example, tracks more than 400,000 SKUs from AWS alone.)

Cost optimization tools and consultants can determine the best combination of resource models to keep costs low while meeting IT requirements. A third party may buy on the user’s behalf to keep costs low, and to balance resources across multiple providers.

Value-adding consumption: Total costs grow at a steady (yet relatively low) rate, although unit costs are low as a result of governance and the use of new pricing models.

At this point, every resource should be delivering value to the company (e.g., revenue increases or productivity gains).

Rising costs are a good thing at this stage because they are enabling the business to grow and scale, which is the greatest value of cloud.

At this stage, the cloud transformation is near completion.

Conclusion

451 Research studies show that most enterprises are currently in the War and Peace stage, and are combatting spiraling cloud costs. Many are using governance tools to control consumption, and are doing some rudimentary cost optimization.

A Brave New World will be the next phase, and some companies have already entered this stage, often leveraging third-party tools and managed services.

However, ‘invisible infrastructure’ that ‘just works’ could still be years away.


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2. The Quick and Easy Way to Private Clouds

Many enterprises want to outsource the building of private clouds but fear lock-in to proprietary platforms.

An emerging solution to this dilemma is build-operate-transfer (BOT) contracts from open source providers.

The BOT model offloads the heavy lifting of do-it-yourself deployments while reassuring customers that they can assume operating control when they’re ready.

Providers offering these arrangements – including Canonical, Mirantis and Joyent (now owned by Samsung) – report keen interest in the BOT model.

However, they acknowledge that transfers are rare: once enterprises become accustomed to dedicated managed infrastructure, most prefer to pay the price so in-house staff can focus on higher-level services.

BOT contracts have historically been used for public works projects, in which a private company receives funding from a public sector organization to build and operate a facility (e.g., a refinery or airport) for a certain period of time, after which operation is transferred back to the funding entity.

Key Players

Canonical was the first to apply the BOT concept to private clouds, offering BootStack (‘Boot’ stands for ‘build, operate and optionally transfer’) in late 2014.

The company found that few enterprises – especially those wanting to avoid public clouds for some applications – had the resources or expertise to build and operate OpenStack clouds on their own.

With BootStack, Canonical leverages its OpenStack distro and engineering expertise to build private clouds and operate them remotely as a managed service, while giving customers an ‘out’ if they want to assume control of the infrastructure later.

Mirantis started offering BOT contracts when it acquired TCP Cloud in 2016.

The company includes BOT as part of the value proposition of its Mirantis Cloud Platform, a managed service launched last year that incorporates Kubernetes for multi-cloud orchestration.

Joyent unveiled its BOT service in mid-2017 as part of its Private Regions offering, which devotes a dedicated, isolated portion of its public cloud to individual customers, with 100% open source and fully transferable infrastructure.

Joyent’s BOT service is called Triton Private Regions.

BOT Benefits

The BOT concept can be compelling because:

  • Enterprises get a made-to-order private cloud that avoids lock-in to proprietary platforms.
  • Providers receive steady revenue (license/subscription, managed services, hosting, support).
  • Both enterprises and providers can focus on what they do best, while sharing the risk of cloud migration.

451 Research’s Private Cloud Price Index service found that labor costs are the biggest issue affecting OpenStack TCO: OpenStack engineers are significantly more difficult to find and they cost far more than VMware and Windows engineers.

BOT is an alternative that enables organizations to outsource the expertise-intensive work of designing and building open source private clouds with the ability to assume control of IT operations once the cloud is up and running.

Ingredients for Success

Based on the experiences of BOT providers and customers, here are some factors to consider:

  • Eligible enterprises have data-intensive workloads, want to maintain single-tenant infrastructure, and have (or are willing to recruit/train) in-house engineering and cloud management teams.
  • Candidates include companies that are less inclined to use public cloud but want the option of being able to develop and deploy applications quickly. Examples include telcos, companies with video/data-intensive applications, fintech firms, online retailers and enterprises with strict compliance demands.
  • Builds can start small with enterprises migrating applications incrementally. For example, Canonical’s minimum configuration to start is 12 nodes in a single rack.
  • The build-operate phase will likely take at least a year, with two or three years before transfer (if it occurs).
  • The cost savings after transfer (i.e., the difference between the provider managing the infrastructure versus having a support contract only) ranges from 40% to 70%.
  • Underlying hardware can reside in a datacenter or colocation facility owned by the enterprise, the provider or a third party.
  • Provider training of enterprise IT operations personnel is crucial to enact a smooth transfer.
  • Kubernetes support is table stakes, because providers need to ensure access to public cloud capabilities while offering container orchestration across public, private and physical infrastructure.

Conclusion

It’s clear why the BOT model can appeal to some enterprises: They can start small, tap into the development velocity of the open source community and ‘rent’ expertise from providers for setting up, scaling up, and training in-house staff to ultimately take over operations.

While only a minority of businesses take the ultimate step of transferring management in-house, those that do can realize considerable cost savings while avoiding lock-in to proprietary platforms.


3. Digital Wallet Intent Remains Steady

Consumer use of digital wallets has remained steady over the past year as digital wallet services as a whole have not provided enough incentive to encourage wider adoption.

One-quarter (25%) of respondents in the 451 Research Leading Indicator panel say they’re likely to use digital wallets in the next 90 days – down 1 point from September and down 4 points year-over-year.

The biggest players, Apple Pay and PayPal, remain on top in terms of planned and current use as well as satisfaction, but the field is becoming more crowded with banks and retailers joining the fray with their own payment apps.

The latest survey on digital wallet trends, completed January 22, consisted of 3,568 primarily North American respondents from 451 Research’s Leading Indicator panel comprised of a targeted group of business and tech professionals, as well as early adopter consumers.

Key Findings

Among planned users, Apple Pay (55%) remains far ahead of the competition, although it is unchanged. PayPal (37%) is firmly in second place but down 2 points.

  • PayPal leads in satisfaction among current users with 71% saying they’re very satisfied, followed by Apple Pay (68% very satisfied).

  • Nearly two-thirds (63%) of respondents who are not likely to use digital wallets say security against fraud that is better than traditional payment cards would encourage them use digital wallets.
  • Mean security ratings have been rising for the past two years with a current mean of 6.2 out of 10. Users of Apple Pay (8.3) perceive their platform to be more secure than PayPal (7.7).

  • Those using iOS are more than twice as likely as Android users to say digital wallets are more secure than traditional credit cards (40% vs. 19%).
  • PayPal (64%) is by far the most used person-to-person payment app. About one-quarter (26%) say they use their bank’s app for person-to-person transactions, followed by PayPal-owned Venmo (13%).

4. Top Ten Technologies to Disrupt the Datacenter

To determine the top ten technologies that could potentially disrupt datacenters, 451 Research relied on input from more than 600 IT professionals – including C-level executives, IT and facilities managers, and datacenter design engineers – as well as experts from Uptime Institute (which is part of The 451 Group).

And the Winner is…

Although there was considerable diversity in the participants’ views, there was some consensus on the most disruptive technology: distributed resiliency – spreading critical workloads across many datacenters using networks, data replication and traffic switching to reduce the risk of failure.

Enterprises can spread applications and data across racks, datacenters and regions, protecting them from underlying datacenter or component failure.

Although a few operators have used distributed resiliency for more than a decade, it’s still nascent. Barriers to adoption include:

  • Scalability challenges
  • Increased complexity in IT and management software
  • Networking hurdles

However, distributed resiliency could result in much lighter-weight datacenters, with far less single-site redundancy.

Drivers for this technology include availability, efficiency and site-level redundancy.

As long as there are at least three datacenters and sufficient networking capacity, operators can achieve extremely high availability. The need for high levels of redundancy in power, cooling and IT resources at each site can be reduced, potentially saving huge expenditures.

In addition, enterprises can spread spare capacity across datacenters.

However, there are risks and limitations with distributed resiliency, and for some datacenter operators there are currently too many barriers to make the concept feasible. As such, adoption may be slow.

Following are brief descriptions of the other disruptive technologies, in random order.

Conclusion

Of course, assessing which datacenter technologies are likely to be disruptive is extremely challenging.

Different domain experts are likely to have different views on the impact of various technologies. And the same is true for datacenter operators, managers and designers.


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