THINKstrategies conducted a recent survey of 341 IT professionals around the world to determine how Cloud Computing alternatives are affecting the IT Service and Client Management needs of organizations.
Among the many interesting findings from this survey, one in particular stands out: nearly half of the survey respondents verify that their currently installed Service and Client Management solutions – that serve as the backbone of IT organizations – are 5+ years old. As a result, many of these aging systems are being evaluated for major upgrades and/or replacement.
While the vast majority of respondents are deploying on-premise Service and Client Management solutions, the tide is shifting to cloud-based implementations.
And this raises big questions about the pros and cons of multi-tenant vs. single tenant cloud architectures that are increasingly relied upon to deliver Service and Client Management solutions ranging from running help desks and change management requests, to incident response processes, service catalogs and, in some cases, ITIL best practices.
The Cons of Single Tenant Cloud Architectures
Let’s examine some distinct disadvantages of single tenant cloud architectures.
For starters, they can only scale out to support new customers in a linear fashion, which means the costs to upgrade individual clients are prohibitive. The downside of this approach is obvious: vendors pass on some of these upgrade costs to customers.
In addition, single-tenant architectures require each customer to maintain a unique software code base that results not only in substantially higher technical support costs but makes software implementations and upgrades much more difficult to deploy than multi-tenant architectures. This approach also limits the frequency of functional upgrades that often times are limited to release cycles once every 12 – 18 months.
Simply put, maintaining multiple versions of an application makes it harder for a Service and Client Management provider to support individual code releases. Why? Technical support staff must be familiar with a broader range of technical issues associated with each release. And junior technical service personnel will often require the assistance of more senior staff as they run across issues that are not familiar with. he typical end result is a significant increase in customer support requests that can create service backlogs. This in turn can erode customer satisfaction levels.
Another drawback of single tenant architectures is that each customer is provided with a dedicated server, which at first blush may appear to be an advantage. However, since data centers charge per server and per virtual machine, each time a customer is added to a single tenant solution, costs to the cloud provider increase. And a portion of those cost increases are, in turn, passed on to the customer.
The Pros of Multi-Tenant Cloud Architectures
On the other hand, cloud-based Service and Client Management solutions based on a multi-tenant architecture maximize organizational efficiency and cost-effectiveness because they operate on an economy-of-scale basis by eliminating the need to expand data center infrastructure linearly. This significantly reduces the overhead associated with providing IT services, and as a result, lowers the costs levied on customers.
In addition, multi-tenant solutions allow software updates to be rolled out to all customers simultaneously. This standardizes software versions utilized by customers. Because each customer maintains the same application and same software version ensured through consistently applied upgrades, they are beneficiaries of more stable software, fewer bug fixes and less disruption to service operations. By eliminating version control issues, support staff can more efficiently respond to maintenance issues resulting in fewer instances of customer service backlogs.
With a multi-tenant architecture, each new customer is put on the same database rather than individual servers, so a provider that offers a multi-tenant solution will lease far less data center equipment compared to a provider offering a single-tenant solution supporting a comparable number of customers. Since each customer does not require its own data center equipment in a multi-tenant environment, the cost of adding customers is fractional compared to a single tenant solution.
The “landlord” analogy helps draw a distinction between single tenant and multi-tenant cloud approaches. Imagine having 100 tenants and you, as landlord, have the option of servicing those tenants in separate homes spread across multiple neighborhoods or in a single high-rise building. The high-rise option is intuitively obvious since you only have to “pay rent” on a single property versus a hundred dwellings and maintenance staff and managers are onsite without having to be dispatched to disparate locations.
While supporters of single tenant architectures will point to perceived security advantages offered by running clients on dedicated servers that don’t “co-mingle” accounts, multi-tenant cloud security advances mitigate this argument.
To quote Jeff Kaplan, Managing Director of THINKstrategies and recognized expert in cloud computing, “Properly designed and administered multi-tenant services can also be even more secure than traditional on-premises product or past ASP arrangements, because the vendor maintains full control of access to its system. In the same way that individual condominium units can be built in a secure fashion with solid walls and strong locks in a shared community, multi-tenant cloud services can also be architected to partition user data and safeguard it against internal and external security threats.”
Like every important choice, there are tradeoffs to consider when making a commitment, especially when it comes to selecting the right cloud architecture. Given the accelerating adoption of cloud computing to support critical IT Service Management functions across organizational business units, there is no substitute for conducting thorough due diligence into the pros and cons of multi-tenant and single tenant cloud options.
ABOUT Kevin Smith
Kevin Smith is responsible for the Cloud Business Unit, including all strategy; go to market and customer success activities for the growing portfolio of FrontRange Cloud applications. Smith has a deep understanding of the Service Management market, having previously been responsible for product management, product marketing and corporate marketing for all FrontRange product lines. Smith brings over 25 years of technical, management, and executive leadership experience in technology and software businesses.
Prior to FrontRange, Smith has held positions as VP of Solutions Management at Manugistics Inc., VP of Operations at Avyx Inc., as well as Flight Design Manager with NASA at the Johnson Space Center in Houston, Texas where he began his career in 1983.
Smith holds a Bachelor of Science in Chemical Engineering from Texas A&M University and a Master of Science in Computer Science from the University of Houston.
With 2017 behind us, the news cycle is still stirring up stories on artificial intelligence (AI) and machine learning (ML), but has some of the excitement worn off? We're witnessing a surge of activity in the space. Can actual examples of AI in the enterprise rise among some of the noise that's inundating the market and hindering the credibility of everyone? ...
Everyone wants to talk about how analytics is the future of network engineering and operations. The phrase "network analytics" is used by vendors of various stripes to imply that a particular technology is smarter and better than the average solution. But what is it? What does the term network analytics mean to the enterprise network infrastructure professionals? ...
Three out of four (76%) of organizations think IT complexity could soon make it impossible to manage digital performance efficiently, according to the Top Challenges Facing CIOs in a Cloud-Native World report from Dynatrace ...
The Global CIO Point of View report compiled by ServiceNow notes that 89 percent of organizations are either in the planning stages or are already taking advantage of machine learning. Nearly 90 percent of the CIOs surveyed anticipate that increasing automation will increase the speed and accuracy of decisions, and more than two-thirds believe that decisions made by machines will be more accurate than human-made decisions ...
The enterprise WAN is unable to keep up with digital transformation demands, according to Foundation for Digital Transformation, a new research report, authored by Ensemble IQ and supported by InfoVista. This challenge was universal across all three vertical industries surveyed — retail, manufacturing, and banking/financial services ...
Achieving optimum Java Virtual Machine (JVM) performance is key to ensuring proper memory management and fast application processing. According to a Cornell University study, a 1-millisecond improvement in the performance of a trading application can be worth $100 million a year to a major brokerage firm. Because of this potential for loss, IT teams owning banking, financial, trading and other Java-based applications place a high value on having a proper JVM monitoring strategy in place ...
APM had to evolve to keep pace with development velocity and maintain the service quality for the modern applications born out of digital transformation. Automation and artificial intelligence (AI) technologies are critical to the next step in APM evolution, helping to address speed, scalability and intelligence demands ...
A worldwide survey by Gartner, Inc. showed that 91 percent of organizations have not yet reached a "transformational" level of maturity in data and analytics, despite this area being a number one investment priority for CIOs in recent years ...
Mobile app performance is still a significant issue. In a new report from PacketZoom, The Effect of Mobile Network Performance on Mobile App Users, 66% of consumers said reliable mobile app performance is "very important" — second only to mobile app security ...