There’s nothing cloudy about it – the Cloud offers a number of advantages over on-premises computing solutions.
As life sciences researchers work with higher volumes and more variety & complexity of data - and as the organizations they work for become more sensitive to the costs of dedicated IT resources - cloud computing emerges as a solution for a multitude of challenges.
Not surprisingly, Amazon Web Services, a provider of cloud computing services (which - full disclosure - PerkinElmer uses) identifies six main benefits of cloud over traditional computing:
- Trade capital expenses for variable ones: rather than invest in on-premise data centers and servers, cloud computing lets you “pay as you go,” more like a utility. You only pay for what you use, avoiding steep upfront capital costs.
- Gain massive economies of scale: sharing services with hundreds of thousands of cloud users lowers your variable cost.
- Eliminate guessing at capacity: on-premise requires precise forecasting, but too often you end up with either idle servers or overloaded ones. Cloud enables perfectly scalable, just-what’s-needed service - without the guessing.
- Increase speed and agility: the cloud lets you release new IT resources and updates in a click, for a “dramatic increase in agility.”
- Don’t pay to run and maintain data centers: spend instead on growing your business (or expanding your research), not “racking, stacking, and powering servers.”
- Go global in minutes: deploy applications in regional clouds worldwide to lower latency and enhance customer experience.
These are key advantages for any life sciences organization, and Amazon is not alone in its analysis. The Yankee Group found that, on average, the total cost of cloud-based Software-as-a-Service (SasS) offerings is 77 percent lower than systems on-premises.
Comparing the Cloud With Physical Infrastructure
Sure, you’ll pay more in subscription fees for cloud services versus licensing fees for software, but the costs for customization and implementation of licensed software, the hardware to run it, the IT personnel to manage and maintain it, and the time an expense of training add up to a total cost that far exceeds cloud computing.
Our own analysis, comparing PerkinElmer Signals for Translational to a popular open-source system based on a traditional software model shows total cost of the cloud model to be nearly half that of the on-premises one.
Advantages of the Cloud: More than Cost-Savings
|On-Premises Model||Cloud-Based Model|
|Requires new HW, SW, & IT support||No new HW, SW or IT involvement|
|Implement in months/years||Implement in days/weeks|
|Time consuming, costly upgrades||Automatic, disruption-free upgrades|
|No innovation velocity||Constant improvement, enhancement|
|Designed for techie users||Designed for business users|
|Time-consuming to rollout||Automatically accessible worldwide|
|High upfront cost and TCO||Low annual subscriptions and TCO|
|High risk: big upfront purchase||Low risk: try first, cancel at any time|
This chart shows several additional advantages of the cloud over the on-premise model. With the cloud, plan on scaling up more quickly and deploying complex algorithms more frequently. Accelerated and automated updates are less disruptive to your users, keeping them focused on answering the questions their research continually poses.
The cloud has also enabled a new way of working – distributed research and development. Whereas the old centralized mainframes both consolidated and isolated data, the cloud fosters collaboration with external partners and opens access to emerging markets and public data.
Cloud-Based Computing is Working
For proof the cloud is delivering on its promises, look no further than its use. Cisco, in its Global Cloud Index: Forecast and Methodology, 2014-2019 report, predicts that 86 percent of workloads will be processed using cloud data centers - versus only 14 percent by traditional data centers. Cloud data centers handled a workload density of 5.1 in 2014, but that will increase to 8.4 by 2019 – compared to just 3.2 for traditional data centers.
There is one caveat which we’ve addressed in this blog before – the issue of security in the cloud. While it is our opinion that there are solid technology solutions for security concerns, some in the industry are addressing this for now by using a hybrid of both private cloud and on-premise computing for mission-critical workloads.
Due to the “strengthening of public cloud security” however, Cisco predicts that public cloud will grow faster (44 % CAGR 2014-2019) than private clouds (16% CAGR for the same period). They estimate more workloads in the public cloud (at 56 percent) than in private clouds (at 44 percent) by 2018.