What is the need for data center virtualization? What are the benefits of data center virtualization?

Data center virtualization 

  • Data center virtualization is the process of designing, developing, and deploying a data center on virtualization and cloud computing technologies.
  • It primarily enables virtualizing physical servers in a data center facility along with storage, networking, and other infrastructure devices and equipment. Data center virtualization usually produces a virtualized, cloud, and collocated virtual/cloud data center.
  • Virtualization, Offering profound changes to the way data centers perform, virtualization makes sense on multiple levels. 


The benefits of data center virtualization are as below:

1. Less heat buildup

Millions of dollars have gone into the research and design of heat dissipation and control in the data center. But the cold, hard fact is, all of those servers generate heat. The only way around that? Use fewer servers. How do you manage that? Virtualization. Virtualize your servers and you're using less physical hardware. Use less physical hardware and you generate less heat. Generate less heat in your data center and a host of issues go away.


2. Reduced cost

Hardware is most often the highest cost in the data center. Reduce the amount of hardware used and you reduce your cost. But the cost goes well beyond that of hardware — lack of downtime, easier maintenance, less electricity used. Over time, this all adds up to significant cost savings.


3. Faster redeploying

When you use a physical server and it dies, the redeploy time depends on a number of factors: Do you have a backup server ready? Do you have an image of your server? Is the data on your backup server current? With virtualization, redeployment can occur within minutes. Virtual machine snapshots can be enabled with just a few clicks. And with virtual backup tools like Veeam, redeploying images will be so fast your end users will hardly notice there was an issue.


4. Easier backups

Not only can you do full backups of your virtual server, but you can also do backups and snapshots of your virtual machines. These virtual machines can be moved from one server to another and redeployed easier and faster. Snapshots can be taken throughout the day, ensuring much more up-to-date data. And because firing up a snapshot is even faster than booting a typical server, downtime is dramatically cut.


5. Greener pastures

Let's face it: If you're not doing your part to help clean up the environment, you're endangering the future. Reducing your carbon footprint not only helps to clean up the air we breathe, it also helps to clean up your company image. Consumers want to see companies reducing their output of pollution and taking responsibility. Virtualizing your data center will go a long way toward improving your relationship with the planet and with the consumer.


6. Better testing

What better testing environment is there than a virtual one? If you make a tragic mistake, all is not lost. Just revert to a previous snapshot and you can move forward as if the mistake didn't even happen. You can also isolate these testing environments from end users while still keeping them online. When you've perfected your work, deploy it as live.


7. No vendor lock-in

One of the nice things about virtualization is the abstraction between software and hardware. This means you don't have to be tied down to one particular vendor — the virtual machines don't really care what hardware they run on, so you're not tied down to a single vendor, type of server (within reason of course), or even platform.


8. Better disaster recovery

Disaster recovery is quite a bit easier when your data center is virtualized. With up-to-date snapshots of your virtual machines, you can quickly get back up and running. And should disaster strike the data center itself, you can always move those virtual machines elsewhere (so long as you can re-create the network addressing scheme and such). Having that level of flexibility means your disaster recovery plan will be easier to enact and will have a much higher success rate.


9. Single-minded servers

I've never been a big fan of all-in-one services. Not only are you looking at a single point of failure, but you also have services competing with resources as well as with each other. Those all-in-ones are purchased to save money. With virtualization, you can easily have a cost-effective route to separating your email server, your web server, your database server, etc. By doing this, you will enjoy a much more robust and reliable data center.


10. Easier migration to the cloud

With a move to virtual machines, you are that much closer to enjoying a full-blown cloud environment. You may even reach the point where you can deploy VMs to and from your data center to create a powerful cloud-based infrastructure. But beyond the actual virtual machines, that virtualized technology gets you closer to a cloud-based mindset, making the migration all the easier.

Comments

Popular posts from this blog

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?

Suppose that a data warehouse consists of the four dimensions; date, spectator, location, and game, and the two measures, count and charge, where charge is the fee that a spectator pays when watching a game on a given date. Spectators may be students, adults, or seniors, with each category having its own charge rate. a) Draw a star schema diagram for the data b) Starting with the base cuboid [date; spectator; location; game], what specific OLAP operations should perform in order to list the total charge paid by student spectators at GM Place in 2004?

What is national data warehouse? What is census data?