Cloud Optimization for More Efficient Knowledge Networks
Cloud Optimization for More Efficient Knowledge Networks
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Cloud computing has recently become an elementary business tool in practically all sectors. The majority of company leaders have taken notice to cloud computing and it's usefulness, but also to the ways it can be optimized. What was once a luxury is now a must-have.
Cloud computing optimization and cloud services became structural components in IT infrastructures and especially in knowledge networks, where people collaborate based on their expertise and solve problems together.
As the efficiency is probably the greatest advantage of cloud computing, companies must ensure that some results are seen. Keeping that in mind, here are some insights into cloud optimization and some of the ways to improve the efficiency of using cloud relating to knowledge networks.
Why the needs for optimization
First thing's first: the superiority of cloud networking over the traditional network is undisputed. However, there are ways the cloud itself can improve.
When cloud platforms first came out, they were housed in a small number of a huge, high-capacity data centers. So, the problem was a small number and huge centers. This is a problem because no matter now large the network is, the distance between the data center and the user is usually more than 1500 miles.
While these large data centers are good for providing capacity and scalability, their problem is performance, as it suffers with each mile between the user and the data center. With knowledge networks, speed is sometimes crucial. Imagine having a crisis and a solution takes ages to come. Not only that, but in the 21st century, we live in a world of fast data travel and impatient users. It's the users that bring you the profit so you always have to cater to their needs. Users want fast page loads and sadly for you, their tolerance drops while their impatience rises. This was best seen in the case or online retail space, noting the relationship between page loads and user abandonment.
Cutting down from four seconds of load time to two, and finally down to only one, the users were still losing their patience. Other types of users are not very different, even when it comes to knowledge networks. For example, The Water Network has a large number of users. In order for everything to run smoothly, some serious cloud optimization is required.
Creating a better user experience
The reason why cloud is such a great idea as the best platform to deliver dynamic site content is quite simple when you get down to it. It offers enormous ability and spaceto handle the growing amount of work in a capable manner. Compared to the traditional architecture, cloud's scalability is simply superior. What this means is that with cloud, you can give your users personalized pages with customization options; rich media content with close to HD quality TV; and in regards to the bandwidth-intensive applications, you can provide your users with web presentations and video conferences.
With knowledge networks, high-quality content is a must have, as a lot of users are visual types. Presentations and conferences come in a major asset here because some people just can't sit and read through on ocean of text.
More distributed cloud
In order to maximize performance, a more distributed cloud is needed. Its capacity distributed to many locations, becoming closer to users. This way, the number of network hops is reduced. The less of a distance, the lesser a number of hops, but greater the speed.
With better speed, the user experience also becomes better. Without this solution, a knowledge network runs slow and sluggish, and we're back to the previous issue of impatience.
Now, for users on a global base, you would need a global network of servers, naturally. Global servers mean each server closer to a group of end users, cutting down the number of network hops by a lot. This all depends on the user base, since it might require somewhere from a few servers or few thousand servers. Doing this, setting up servers globally, however isn't the complete answer.
The providers of the cloud (the knowledge network) would also need to incorporate the dynamic route optimization technology. It is a technology for identifying fast and better routes, in real time, as new users and user requests come in.
Spend time investing in cloud analytics
Cloud analytics are practically as must-have here. If you want your knowledge network to work properly, and not only that but at its highest, you must determine and answer the basic questions such as: why, where, when and who is using your cloud. Cloud Analytics help you answer those questions and bring you insight about your cloud users.
One more use of cloud analytics is tracking how the use of the cloud relates to it's cost over time. Without it, you might not know how and even if your network is being used. You might fail to see if the once-working service is now not an optimal solution. A good example of incorporating cloud analytics is TallyFox.
Developing a governance strategy
An important part of cloud optimization when it comes to knowledge networks is cloud governance. To put it in layman's terms it's a strategy for determining how a knowledge network will approach and oversee its cloud solutions, all through established policies. The network will grow, and new ideas will come.
It's fundamental that these ideas and solutions don't have a negative impact, but contribute to a better cloud. Protocols for utilizing and overseeing resources simply need to be applied. Without it, the network would have unnecessary wastes of resources and some ideas, while goodhearted might damage the overall shared experience and hinder progress.
In the end, it's all about getting the best user experience. Cloud optimizing provides knowledge network users with a more rich, faster and an overall better experience for them. It makes the network itself run smoother, with a lot of happy users.
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