Life in a Multicloud World Vendors have developed clouds for an assortment of purposes. Instead of choosing just one cloud model, IT teams are investing in multiple platforms so they can create a color wheel of tools and workloads that don’t clash.

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Deployment Options Multiply

Early cloud efforts were seen by CFOs and CIOs as ways to trim IT costs through reductions in infrastructure, staff and operating expenses. The strategy of migrating the easi-est-to-move services has changed and matured into putting services and applications into the cloud that have the biggest positive impact on the business as a whole and the customer experience in particular.

The result is services and applications run-ning across a mix of private and public clouds, operated by providers with methods and tools that can be profound in their differences. For IT, deploying these diverse platforms is a chal-lenge that must be surmounted to ensure con-tinual operation and advancement.

Part one of this handbook is my examina-tion of the all-hands-on-deck coordination needed when deploying a multicloud infra-structure. With more than 80% of enterprises now embracing a multicloud strategy, deploying

services in a consistent and repeatable way is essential for IT to maintain control.

In part two, technology consultant Kurt Marko defines and examines the cloud deploy-ment models that exist for today’s enterprise applications. Marko scrutinizes public, private and hybrid cloud deployments and discusses when to make the transition from one model to another. He concludes with three ways to ana-lyze make-or-buy choices.

Marko returns for part three and looks at how to manage app deployments on multi-ple cloud-computing platforms. While care is needed to manage applications and infrastruc-ture configurations across cloud stacks that do not share a common API, he suggests that multiple platforms are often ideal to minimize dependence on a sole provider. n

Joel ShoreNews Writer, SearchCloudApplications

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Multicloud Deployment Acceptance Soars

Deploy your company’s compute load across multiple clouds, providers and services, and you’ll be better-protected against complete disaster if a server fails.

That’s an increasingly popular and practical notion. As a result, adoption of a multicloud approach, sometimes called a cloud portfolio, is growing quickly. In a report on the cloud, RightScale Inc.—a provider of cloud portfolio management services—noted that as of Janu-ary 2015, 82% of surveyed enterprises are now employing a multicloud strategy, up from 74% just one year earlier. Within that group, a mix of public and private clouds is favored by 55%, while those opting solely for multiple private or multiple public clouds are split almost equally (14% and 13%, respectively).

As companies simultaneously move applica-tions and data to the public cloud, keep others on-premises and integrate with software-as-a-service providers, it’s important for them to

deploy services in a consistent and repeatable way. “[Fail] to work this way, and IT operations will not be able to maintain control,” said Bai-ley Caldwell, RightScale’s vice president of cus-tomer success.

A cadre of nine Forrester Research analysts stated in a report that automating is the answer to the fundamental issues of scale, speed, cost and accuracy.

Commenting on the report in relation to cloud deployment, analyst Dave Bartoletti said, “You may have built a workload for Amazon [Web Services] that you now want to run in [Microsoft] Azure, or replace with a database in Salesforce, or use an ERP system like SAP in the cloud. You need a consistent way to deploy this.”

The problem, Bartoletti explained, is that businesses find deployment across these var-ied platforms difficult largely due to a lack of tools with cross-platform intelligence.

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“Traditionally, you’d use the tool that comes with the platform, perhaps vCenter Server for VMware vSphere environments or AWS OpsWorks to deploy on Amazon.”

The tools landscape is still adapting to the reality of multicloud. In a survey of hybrid cloud management offerings, Bartoletti ana-lyzed 36 vendors, several of which offer tools that manage multiprovider cloud platforms along with application development and delivery.

Consistency appears to be the keyword for existing in a multicloud universe. It matters because nothing stays still in the cloud for very long, including the apps and data you provide and the actual infrastructures, services and pricing of each provider.

“If you want to move applications, data and services among different providers—and you will as part of a continuous deployment strat-egy—it’s important to have consistency and a level of efficiency for managing those disparate environments,” said Mark Bowker, an analyst at The Enterprise Strategy Group.

Technical reasons for periodically fine-tun-ing a deployment strategy include:

■n Availability of new services from one pro-vider that constitutes a competitive or operational advantage;

■n Difficulties with a provider;

■n A need to mirror deployments across mul-tiple geographies to bolster performance;

■n A requirement to ensure that network communications paths avoid certain locales in order to protect data assets; and

■n A desire to bring analytics services to where the data resides.

Nontechnical reasons might include changes to a favorable pricing model and the ability of one cloud provider to more fully follow an enterprise’s compliance and governance requirements.

Similarly, the degree to which a cloud pro-vider meets regulatory requirements can lead to redeployment of applications or data from one vendor to another, said Lief Morin, presi-dent of Key Information Systems.

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“When a business reaches a certain size, it has more leverage to dictate security terms to the provider; otherwise, the provider will dictate them down to the organization. It’s a matter of economics and scale,” he said. “In a multicloud environment, it gets more complicated. More providers mean more risk, so it’s crucial to work with them to ensure a consistent, standardized policy.”

A multicloud deployment model should be a quasi-permanent arrangement— quasi because nearly everything changes eventually.

“What you’re seeing today is movement toward an application-configured infrastruc-ture environment,” noted Roy Ritthaller, vice president of marketing for IT operations management at Hewlett Packard Enterprise. “At the end of the day, it’s not how well your cloud is organized or how shiny and new it is;

it’s about how well [do] the application and workload perform together.”

While matching the application and load makes sense, the elastic nature of the hybrid cloud environment offers opportunities for continual refinement of where they are deployed, according to David Langlais, Hewlett Packard Enterprise’s senior director of cloud and automation.

Like a swinging pendulum, a certain amount of back-and-forth between private and public clouds is natural, he said. “What’s important is to design applications in a way that can handle changing deployment models, all the way down to managing the data and connecting to it,” he explained. “Decisions that are made initially on the development side have to be handled in production for the long term. It also means understanding the cost profile and recalculating on a regular basis.” —Joel Shore

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Aim for Balance With Deployment Model Selection

There’s a lot of noise about the superiority of both hybrid cloud and public cloud deploy-ments. So which is it? Is internal IT infra-structure destined to extinction under a wave of public utility computing, or is public cloud a fad at the peak of inflated expectations set to crumble beneath the realities of real-world cost, integration and data protection?

Most likely, neither of these extreme posi-tions will prevail, at least in the near term. So IT teams face decisions about when, where and how to deploy public and private cloud. They must also try to make public and private work well together while consistently managing workloads, security and configurations.

Traditional enterprise data centers provide maximal control and flexibility over all aspects of hardware, software and system administra-tion at the cost of capital expenditures (such as facilities and equipment) and operating expenditures (such as utilities, staffing and

support contracts). The move to completely shared services eliminates most of these over-head costs by presenting users with a set of virtually abstracted infrastructure and appli-cation services that are bought and paid for as needed. As IDC Research advises, assess-ing on-premises versus cloud requires consid-ering the enterprise’s complexity and breadth of resources compared with those offered by a cloud provider.

Using a public cloud means ceding control over operational details, but it doesn’t imply taking undue risks. Contrary to the early con-ventional wisdom and fear sown by other ven-dors, the core infrastructure of public clouds is almost always more secure than enterprise data centers. Consider the highest profile data breaches in recent memory—incidents such as the Edward Snowden leak of NSA docu-ments, Target and Home Depot point-of-sale breaches and the hack of Sony Pictures

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Entertainment—almost all were against private infrastructure.

Although shared cloud services present a big target, providers have powerful business and regulatory incentives to maximize secu-rity by using the latest technology, disciplined processes and thorough audits. Still, there are good reasons for keeping some applications and their associated data and infrastructure in-house. Migrating legacy applications can be difficult, with their myriad dependencies on internal data sources and deep integration to existing and stable business processes.

Here are three ways to approach the make-versus-buy choice:

Start private by evolving virtual machine (VM)

farms into a cloud; add public for new or highly

variable workloads. The most common scenario for larger organizations that have already vir-tualized most, if not all of their applications, is to evolve from server VMs to full private cloud. According to the National Institute of Standards and Technology’s definition of cloud computing, the evolution means adding self-service provisioning on demand, resource

pooling across users and organizations, dynamic workload elasticity and scalability, and metered service with resources tracked and billed based on workload consumption.

Workloads targeting customers or external business partners that are highly variable, sea-sonal or have few integration points with inter-nal systems may be better served by running on a public cloud. Migrating these is the first stage of hybridization.

Start public and add private if necessary. This is the path primarily taken by startups or small and medium-sized businesses, because some organizations may not have the capital or per-sonnel available to build a private cloud. These organizations are some of the most aggressive users of infrastructure as a service and software as a service, preferring to outsource backend IT and focus on developing applications and services that fuel new business. Although it’s impossible for such organizations to actually outgrow Amazon Web Services (AWS), Micro-soft Azure or Google, it’s possible for usage to outstrip their budgets.

Once companies find that their AWS bill

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is well into five figures per month, it’s time to pull workloads with the highest sustained demand in-house. If a business is using Azure, this is relatively simple because the service model and management interface is nearly identical between public and private clouds. Things are trickier for AWS or Google users; however, both OpenStack and Apache Cloud-Stack provide AWS API compatibility to mini-mize workload reconfiguration and simplify the transition.

Make new workloads all public and maintain

legacy applications as they are. Research com-pany Gartner proposes another, separate- but-equal cloud deployment model it calls Bimodal IT that segments services into catego-ries based on application service requirements, criticality, maturity and level of integration with existing business processes. As defined by Gartner, “Mode one is traditional,

emphasizing scalability, efficiency, safety and accuracy. Mode two is nonsequential, empha-sizing agility and speed.”

In practice, this means putting legacy appli-cations into maintenance mode—which could require years of support—and where invest-ments focus on security, reliability and main-taining performance. Meanwhile, new systems are cloud native and built with public cloud services and APIs.

Choosing a cloud deployment model starts with understanding your application portfolio and its specific needs. Use public cloud where you can, on-premises where you must and develop the wisdom and expertise required to integrate the two. Whether you start a private or public cloud, most organizations will likely end up with a mix of the two. The key is to find the right balance and minimize the friction of moving workloads between clouds. —Kurt Marko

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Juggling Application Deployments on Multiple Platforms

Conversations about cloud services often begin with Amazon Web Services, but for most organizations, it won’t end there. An increasing number are adopting multicloud strategies that include both public and private components to fight vendor lock-in, increase the diversity of available services, counter arbi-trage price disparities or maintain control over particularly sensitive information. Although using multiple cloud computing platforms can be a sound strategy, it can lead to application, API and configuration management problems.

It can be complex to manage applications and infrastructure configurations across cloud stacks that don’t share a common API and have very different service definitions and bill-ing models. It’s hardly a showstopper, how-ever, because a number of mature software and software as a service (SaaS) options are avail-able to automate deployments across a variety of cloud stacks. Yet all automation tools rely

on a common conceptual framework: treating cloud resources as abstract objects that can be configured, run and managed as software code. Hence, there’s an overlap with DevOps meth-odologies and organizational models.

THE MULTICLOUD IMPERATIVE

If you think using multiple cloud computing platforms works only for hyper growth cloud-native startups or multinational enterprises, think again. Fifty-eight percent of respondents to a RightScale report on the cloud use both public and private clouds. Furthermore, 14% have a multiple public-cloud strategy with another 55% working toward a hybrid mix of public and private. Lest you dismiss RightScale, a provider of cloud management software, of stacking the deck in favor of its product thesis, Forrester Research came up with similar data. The market research company found that 52%

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of large firms already use more than one public cloud vendor, with a third running on three or more cloud computing platforms.

The multicloud imperative is fairly simple. No organization wants to have critical infra-structure solely dependent on a single vendor, even one as large and reliable as Amazon Web Services (AWS). Indeed, without a proper AWS architecture that includes multiple availabil-ity zones, outages are a very real possibility as Amazon and others have found.

Yet, as Forrester points out, cloud heteroge-neity is causing angst among IT pros. Multi-vendor hybrid cloud models require decisions about how to manage different cloud com-puting platforms to provide consistent expe-rience to developers and business users of cloud applications. Inconsistent management and monitoring interfaces are particularly frustrating.

Indeed, RightScale’s survey found that a quarter of respondents say managing multi-ple cloud computing platforms is a “signifi-cant challenge.” Digging deeper, Forrester’s data shows the biggest issues in managing mul-tiple clouds are service consistency among

providers, workload migration among clouds, consolidating management across multiple clouds and supporting different cloud end-user portals. Cloud-agnostic deployment software can help with all four.

CLOUD-AGNOSTIC MANAGEMENT OPTIONS

Dozens of products are designed to automate infrastructure and application management across multiple clouds. Some focus on specific needs or usage scenarios. For example, Cloudyn is designed for asset and cost management and includes a workload optimizer to identify the most efficient cost-performance deployment option for a particular workload. Meanwhile, Computer Services Corp.—using the former ServiceMesh product—focuses on cloud gov-ernance, security and lifecycle management. Others, such as Cliqr, Cloudify and ElasticBox take an application-centric approach to cloud automation.

The most popular multicloud products are generally those used by organizations embrac-ing a DevOps approach to cloud management, a method that extends application programming

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into the realm of infrastructure configuration and management. Indeed, an important differ-entiator of each tool is its choice of program-ming language.

RightScale is on most people’s short list for cloud automation; however, its own sur-vey found that the most commonly used infra-structure DevOps tools are Chef, Puppet, Ansible and SaltStack.

Befitting its name, Chef turns infrastructure configuration, deployment and management into a set of recipes that can be interpreted by any system running the Chef client. Of course, there is some server complexity behind the scenes, but Chef can manage all parts of a cloud application deployment and can be run within the cloud itself. In other words, the Chef server, developer workstations, system nodes and ana-lytics engine all can run as infrastructure as a service. Chef supports the major cloud ser-vices including AWS, Microsoft Azure, Google, VMware and IBM Softlayer, as well as IBM SmartCloud Orchestrator and OpenStack.

Puppet is referred to as the granddaddy of orchestration software, and it’s both mature and widely supported. Puppet has a class-based

domain specific language that resembles JavaScript Open Notation. Although it has a Web user interface (UI), advanced configu-rations will require programming and using

the command-line interface. Razor, a newly released tool from Puppet, can auto-discover and inventory infrastructure and dynamically select a preferred system image for bare-metal provisioning.

An open source platform whose commer-cial version was recently acquired by Red Hat, Ansible doesn’t require a software agent; it operates completely via secure-shell connec-tions. Ansible uses YAML for its configuration “playbooks,” which are used for system config-uration, deployment and orchestration.

A relatively new platform that focuses on speed and scalability, SaltStack is available both

When picking an automation tool, consider the sophistication and scale of your infrastructure and the expertise of your IT or DevOps team.

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as an open source code and a supported enter-prise edition. SaltStack uses YAML to describe system states; however, the entire platform includes a complex set of components that means a steep learning curve, particularly for those not already familiar with another auto-mation platform.

RECOMMENDATIONS AND USES

Any of the major automation platforms described here will work on both private infra-structure and the major public clouds, but the integration details will vary widely.

The choice of product should be dictated

by the sophistication and scale of a compa-ny’s infrastructure and the expertise of the IT or DevOps team. Packaged SaaS products like Dell Cloud Manager, RightScale or Scalr are the easiest to deploy and operate because they all have comprehensive Web UIs with prebuilt templates and integrations to the major cloud services, although connecting them to inter-nal infrastructure may be trickier. Of the more general-purpose tools, Puppet is the most mature, making it quite popular with large enterprises. But because of its agentless design and simple YAML syntax, Ansible is probably the easiest to implement and learn.

—Kurt Marko

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ABOUT THE

AUTHORS

JOEL SHORE is a technology journalist, author and editor with nearly 30 years of experience. He is the co-founder and longtime director of the Computer Reseller News Test Center. He is a news writer for SearchCloudApplications. Email him at jshore@techtarget.com.

KURT MARKO is an engineer and technologist whose expe-rience ranges from sub-micron transistors to Web-scale infrastructure. He now applies the knowledge and skills from a 20+ year career in research and development and IT architecture to analysis, consulting and communica-tions. Email him at kurt.marko@gmail.com, and follow him on Twitter: @krmarko.

Life in a Multicloud World is a SearchCloudApplications.com e-publication.

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