The cloud journey is anything but a short, straight line. The road to cloud adoption ranges from strategy formulation in the early stages to optimization in the later stages. The road is divergent and rocky, and strewn with traps and pitfalls every step of the way.
Many organizations fall into one or more of these traps at some point on their cloud journey. Several myths that permeate the cloud act as lures, drawing organizations into those traps. Knowing the following myths can help you to avoid the traps.
Myth 1: Costs will Be Self-regulating in a Consumption-based Model
Many traditional IT organizations allocate direct and indirect costs back to their users based on some type of service-costing approach. There is a lot of guesswork involved in this approach, particularly for indirect costs that can’t easily be traced back to the consumer of the IT service. One complaint about this model (particularly in showback vs. chargeback environments) is that it encourages irresponsible behavior by the consumers of IT services (i.e., it can be an “all you can eat” type of approach to delivering IT services). A myth related to cloud is that by moving to a consumption-based model to provisioning services, cost overruns will be a thing of the past, because users will self-regulate now that their services are metered.
Nothing could be further from the truth. While it’s true that cloud services are much more readily metered and costs tend to be easier to allocate to a user, cloud services typically are also much more readily available, leading to a highly decentralized approach to provisioning. Translation: The red tape that exists in a highly centralized environment acts as a natural governor on excessive spend, but is dramatically reduced in the cloud (particularly public cloud), as cloud spend tends to be highly decentralized. The solution is to have a control plane in place that allows you to get the best of both worlds: a high level of agility for rapid time to value (the promise of cloud) coupled with appropriate controls to manage a highly decentralized environment.
Myth 2: Optimization of Costs and Usage is an ‘IT Finance Thing’
While this statement held true in the traditional IT world (IT finance was where most of the cost controls were managed), in the cloud world, I am seeing customers demand a single tool that services the needs of both IT finance and IT operations. IT finance typically is more interested in the dollars (cost), and IT operations typically is more interested in the units (performance).
Ultimately, it’s the same data (usage and cost information coming from the cloud provider), and the only thing that differs is how that information is used. The management and optimization of a cloud requires a much deeper partnership between IT operations and IT finance, due to its highly dynamic and decentralized nature.
Myth 3: Your Traditional ITFM Solutions will Work with your Cloud
Many companies attempt to retrofit their traditional IT Financial Management (ITFM) solutions (home grown or purchased) that were designed to handle the allocated world of IT services onto their cloud environments, and almost without exception they have failed. There are a couple of reasons for this failure. The first reason is data latency. In the old world of ITFM, there would be a big accounting exercise at the end of each month to apportion the costs related to IT services delivery to different internal consumers. This is primarily an accounting exercise for the purpose of showback or chargeback. In the new world of cloud, managers want near-real-time usage and spend information so that they can optimize services on a regular basis. When consuming cloud services, waiting until month’s end for the information needed to make decisions simply doesn’t make any sense. At that point, it is too late to take corrective action to optimize your usage or spend.
The second reason is that the highly decentralized nature of cloud usage requires a toolset that is approachable by your average user. Traditional ITFM solutions typically are highly specialized and require a lot of interpretation by an intermediary, like a financial analyst or service manager, and aren’t easily used by a consumer of the service. In the cloud, the provisioning decisions (and, therefore, cost creation) are being handled by a much larger audience, so the tool that you use to monitor, control, and optimize has to have an ease of use comparable to a consumer product.
Myth 4: You Should Focus on Getting your Cloud Operational, then Invest in Building a Control Plane
Ask anyone who has implemented a cloud project and then tried to go back and retrofit it with appropriate tags to achieve some sort of control plane (reporting by department, project etc.), and they will tell you that it’s about as much fun as getting your teeth pulled. It’s a classic BI problem, in which the people responsible for data quality (in this case, the people tagging the resources at the time they are provisioned) are not the same people who rely on those tags to be correct (the people who need to attribute usage and cost correctly). If you are responsible for data quality but don’t benefit from that data quality being high, the result is predictable: bad tags. This leads to major headaches down the road when trying to get control of your cloud.
For this reason, it is recommended that you invest in a cloud control plane very early in your cloud initiative so that you can get a clear picture of where any gaps exist. This approach gives you time to come up with solutions before issues become big problems. As they say, an ounce of prevention is worth a pound of cure. When your users start seeing reports with usage and cost information, they can provide very specific feedback on how things need to improve or change. Best to show them these reports as early in the project as possible.
Myth 5: All Cloud Cost and Optimization Tools Handle Multi-cloud Environments Well
While most vendors claim that they can elegantly handle the management of different clouds in the same tool, the truth is that most can’t. The underlying data from each of the different cloud providers is wildly different, with different quirks in the way usage and cost is metered and reported. This variability is difficult to grapple with, so you should take a very close look at the multi-cloud capability claims of different vendors. Even if you are starting your project with a single cloud (AWS, for example), you always should run a proof of concept to test multi-cloud capabilities or you may be in for an unpleasant surprise after you have selected a vendor claiming multi-cloud support. Cloud is all about choice, and if you choose a control plane that does a less-than-stellar job of handling multiple clouds, you are effectively locking yourself into a given cloud providers’ ecosystem. Not a great idea. Most vendor claims can be tested easily with a simple multi-cloud proof of concept or trial. If your vendor drags their feet on this, then my advice is to run in the other direction as fast as you can!
When it comes to the cloud, as with any business proposition, debunk the myths to harness the value.
Fraser McKay is Head of Product at Cloud Cruiser. He is an expert in creating and launching successful financial BI products for the enterprise, Fraser most recently worked at Apptio, where he led product management and helped the company achieve consecutive years of explosive growth. Before this, Fraser served as the head of BI strategy for the Microsoft Dynamics ERP group, where he oversaw the development of a product roadmap for corporate performance management solutions.
Prior to Microsoft, Fraser held multiple senior management positions at Business Objects and SAP. Fraser holds a Bachelor of Business Administration degree with a major in Marketing and Management Information Systems from Simon Fraser University in British Columbia.
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