|By James Houghton||
|June 7, 2010 09:23 AM EDT||
A shift is finally occurring in the Cloud Computing discourse. Topics like "what is it" have been supplanted by more useful questions such as "should I do it?", "how should I do it?", and "when should I do it?" In appreciation of this new phase of Cloud Computing adoption, we'd like to offer some thoughts on some of the common pitfalls of both public and private Clouds so that you might avoid them as you evaluate and implement cloud solutions.
1. Not understanding the business value
It's important to weigh a Cloud solution versus the traditional approach through the lens of business value. If this is an existing service, can the Cloud truly provide a better solution than what you're currently doing? If new, what are the important business requirements that may drive you to select a Cloud deployment model? In the event of a service outage or a security breech, what's going to happen: is your plane going to drop out of the sky or just experience some minor turbulence?
2. Assuming server virtualization is enough
Running applications on virtualized servers increases performance metrics such as utilization and application portability, but server virtualization is just one component of a truly dynamic IT environment, one that can flex with changing application loads and business requirements. Holistic virtualization requires virtualization at all layers: network, server, storage, memory, data, middleware, and application. A narrow deployment of virtualization capabilities will reduce both the economic and performance advantages of a Cloud deployment, as well as limit your flexibility when dealing with external providers (think vendor lock-in).
3. Not understanding service dependencies
Given the challenges most enterprises have with executing server consolidation and/or data center optimization activities, there's no reason to believe that this will be done properly as companies migrate applications to private or public clouds. Put simply, most enterprises don't understand the multitude of interactions between services, data sources, and other applications that support their business functions over a daily/weekly/monthly cycle. Any attempt to port applications to the Cloud without this knowledge will likely result in broken applications, or worse...difficult to diagnose suboptimal performance.
4. Leveraging traditional monitoring
Even today, many enterprises rely on their end users to notify them of service outages or slowdowns (sometimes referred to as brownouts). When they finally become aware of a critical issue, the individuals responsible for each technology silo circle up on a conference bridge until the problem is isolated and resolved. The Cloud makes this remediation process difficult to execute: good luck trying to get your Cloud provider on that conference bridge! Cloud makes the underlying infrastructure supporting an application/service fluid, rendering traditional resource-based monitoring tools useless as in a diagnostic process.
5. Not understanding internal/external costs
It's a common misconception that moving an application to the Cloud relieves the enterprise of the burden of the people, process, and technology previously supporting that application. However, unless you can answer questions like "which operations person is going to be let go now that we've moved this application to the cloud?" or "what server/rack/row/datacenter can we shut down now that this application is in the Cloud?" you haven't reduced your costs - you've actually increased them. The harsh reality is unless you have the luxury of zero legacy IT, adopting a public Cloud service just increases the internal allocation of costs to the applications that remain in-house. Moving to a private Cloud has a different economic model, but still necessitates substantially different methods for cost tracking and allocation.
Our intent in sharing this was not to dissuade anyone from moving forward in the Cloud - quite the contrary. There are extraordinary business and IT benefits that can be reaped from effective leverage of a Cloud paradigm. The key word is effective - hopefully this post will help you more thoroughly consider the less-obvious elements necessary for successful Cloud adoption.
In the coming weeks we'll explore each one of these topics in more detail, providing specific insights on the challenges and offering potential solutions.
Back in February of 2017, Andrew Clay Schafer of Pivotal tweeted the following: “seriously tho, the whole software industry is stuck on deployment when we desperately need architecture and telemetry.” Intrigue in a 140 characters. For me, I hear Andrew saying, “we’re jumping to step 5 before we’ve successfully completed steps 1-4.”
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