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Cloud Storage Case Study

Cloud storage is a good fit for real estate companies

What is typical about a real estate company when it comes to storage needs?

(1) Many mobile users.
Many employees need to go out and survey the properties, taking pictures and meeting potential buyers and sellers. These users need a solution to be able to access the property information from the field.

This is a typical use case for cloud storage – anywhere access.

(2) Sharing and Collaboration
It requires collaboration between the people back at the office and the people out in the field. They may need to share contract documents and property information.

This is a typical use case for cloud storage too – sharing and collaboration

(3) Outsourced IT department
Real estate companies are typical SMB companies that focus on the real estate. They need IT infrastructure for the information sharing. However, they prefer ways to outsource IT work and reduce the IT related cost.

This fits the cloud computing paradigm shift.

(4) Multimedia Rich Data
Real estate needs to store many pictures and possibility 360 degree videos about the property. Employees need quick local rendering such as viewing the thumbnails of properties all at once so to know the property quickly.

This fits the local + cloud hybrid use case.

As you can see from these four requirements, cloud storage is a good fit for real estate companies.

Reference Implementation

cloudafs-clouddesktop-work-together1

In this reference implementation, the back-end storage is Amazon S3, with a data set size from 50G – 300G.

The mobile users that needs to go out to survey the property and take picture of the property, they will have Gladinet Cloud Desktop installed on their laptops. This enables them to drag and drop to Amazon S3 from the mapped network drive to S3. The mobile workers will have easy connections to S3.

The office workers will access the Amazon S3 through a locally installed CloudAFS file server. For this server, we recommend Dell - Inspiron Desktop (Intel Core i3 Processor / 3GB Memory / 750GB Hard Drive ~ $500) with Windows 7 and CloudAFS installed. Server OS will work too. Any other desktop PC will do too (as long as the hard drive is bigger than the S3 dataset size).  The office workers will enjoy local performance with a hybrid local/cloud solution.

The CloudAFS cache setting will be set to contain all of the dataset so the CloudAFS is capable of mirroring what S3 has. It is OK if the CloudAFS cache size is smaller than the S3 dataset, in this case, there will be cache management overhead.

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Jerry Huang, an engineer and entrepreneur, founded Gladinet with his close friends and is pursuing interests in the cloud computing. He has published articles on the company blog as well as following up on the company twitter activities. He graduated from the University of Michigan in 1998 and has lived in West Palm Beach, Florida since.