Datamation content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.
“Private cloud” is a term heard a lot these days, but what does it actually mean?
Before trying to pin down this elusive beast, it’s useful first to think about what’s meant by cloud computing. Defining “cloud” is not easy, but a cloud computing solution will almost certainly offer:
- Elasticity and scalability. This encompasses the idea of computing on demand, and the ability to increase the supply of computing resources as they are needed to deal with spikes in demand for a particular application or service. There’s also the idea of turning computing resources into a commodity so more can be added over time, as needed, to ensure systems are almost infinitely scalable.
- Pay as you go computing. This involves paying for the computing resources you use for the amount of time that you use them. In a private cloud, customers are generally be individual departments or business units.
- Service level agreements. In many ways what drives the cloud computing model is the need for set performance levels. Elasticity, scalability and the pay-as-you-go model all follow from the need for an economical way to get set desired service levels at all times, even when demand spikes unpredictably.
- Lower costs. A fundamental attraction of cloud computing is that it can provide an opportunity to reduce costs. Savings come from the use of computing resources based at one or more low-cost locations, which are managed efficiently using automation, and by realizing economies of scale stemming from the use of specialist staff members managing large quantities of computing resources
.
Read the rest at ServerWatch.
RELATED NEWS AND ANALYSIS
-
Ethics and Artificial Intelligence: Driving Greater Equality
FEATURE | By James Maguire,
December 16, 2020
-
AI vs. Machine Learning vs. Deep Learning
FEATURE | By Cynthia Harvey,
December 11, 2020
-
Huawei’s AI Update: Things Are Moving Faster Than We Think
FEATURE | By Rob Enderle,
December 04, 2020
-
Keeping Machine Learning Algorithms Honest in the ‘Ethics-First’ Era
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 18, 2020
-
Key Trends in Chatbots and RPA
FEATURE | By Guest Author,
November 10, 2020
-
Top 10 AIOps Companies
FEATURE | By Samuel Greengard,
November 05, 2020
-
What is Text Analysis?
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 02, 2020
-
How Intel’s Work With Autonomous Cars Could Redefine General Purpose AI
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 29, 2020
-
Dell Technologies World: Weaving Together Human And Machine Interaction For AI And Robotics
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 23, 2020
-
The Super Moderator, or How IBM Project Debater Could Save Social Media
FEATURE | By Rob Enderle,
October 16, 2020
-
Top 10 Chatbot Platforms
FEATURE | By Cynthia Harvey,
October 07, 2020
-
Finding a Career Path in AI
ARTIFICIAL INTELLIGENCE | By Guest Author,
October 05, 2020
-
CIOs Discuss the Promise of AI and Data Science
FEATURE | By Guest Author,
September 25, 2020
-
Microsoft Is Building An AI Product That Could Predict The Future
FEATURE | By Rob Enderle,
September 25, 2020
-
Top 10 Machine Learning Companies 2021
FEATURE | By Cynthia Harvey,
September 22, 2020
-
NVIDIA and ARM: Massively Changing The AI Landscape
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
September 18, 2020
-
Continuous Intelligence: Expert Discussion [Video and Podcast]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 14, 2020
-
Artificial Intelligence: Governance and Ethics [Video]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 13, 2020
-
IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI
FEATURE | By Rob Enderle,
September 11, 2020
-
Artificial Intelligence: Perception vs. Reality
FEATURE | By James Maguire,
September 09, 2020