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Nowadays, guess what’s buzzing around in the business domain? Cloud computing! With momentum going away from typical data storage to cloud computing, enterprises are really considering to move the workloads to the cloud. However, there are certain issues around data security, multi-tenancy, data integration, software license and more, which have to be kept in mind before enterprises can run into the same bandwagon. At present, Big Data Hadoop with Cloud Computing has been on the chartbuster as a big data technology, which allows enterprises analyze as well as store massive amounts of data without breaking their banks. As businesses start analyzing Hadoop, one question that pops out automatically is “Can Hadoop be run in the cloud?”
Well, to answer this, let’s take a look at the key aspects of Hadoop:
Hadoop Vs. Physical Severs: It runs best on physical servers. A Hadoop cluster is made of a master node known as name node, and multiple child nodes are known as data nodes. These data notes work as separate physical servers with their own dedicated storage, for example, the hard drive of your computer, regardless of a typical shared storage.
Hadoop is “Rack Aware”: The data nodes also called servers are installed in racks. Each rack features multiple data node servers that work for network communication via a top of rack switch. This means that data can be written to 3 (by defaults) different data nodes, which do not reside on the same physical rack. This helps check data loss in the case data node or data rack undergo a failure. The system admin of this latest storage manually maintains the rack awareness info for the cluster, since this cluster is bombarded with a lot of network traffic, it is suggested that it should be isolated in its own way, instead of implementing VLAN network.
Options to run Hadoop in the Cloud:
As a Service in Public Cloud: You can launch as well as run the Hadoop distributions on the public clouds including like MS Azure, AWS, IBM SmartCloud, Rackspace, and more that present infrastructure as a Service. In a public cloud, the infrastructure is sharable with other customers as a result of which you get a very restricted control over which the server VM is being turned & what others are running on the same physical server.
In private Cloud: The same considerations can be taken for a private cloud deployment as well. As compared to the public cloud, you may have more control over the infrastructure that will let you stipulate bare-metal server or create your own separate network. You can also leverage these private cloud solutions, which offer a Pass later that facilitates pre-build patterns for the deployment of Hadoop clusters. With the private cloud, your data would be secured and you will have the access control of your Hadoop infrastructure.
A few pointers that you must mull over before deploying Hadoop in the cloud:
Make sure your enterprise assesses the security criteria for the deployments of workloads in public cloud prior to shifting any data into the Hadoop cloud. The security of Hadoop cluster is very restricted and there is no native protection for data that will satiate enterprise data protection needs around PII, SOX, HIPPA and more.
Keep a check on Hadoop distributions that you would like to implement and the OS standards of your enterprise. If possible choose distributions that are similar to the open source Apache distributions.
Observe the entire Hadoop network & not only the basic Hadoop cluster. The analytics and data visualization are the key values, which can be applied on big data sets. Make sure that the tools you want to use for insights or analytics are accessible for use on the cloud provider.
Get informed of where the data to be loaded in the Hadoop comes from, would it be possible to load data from your internal systems, which are not on the cloud or are you going to load the data, which is already in the cloud. Most of the public clouds charge nominal fees for data transmission.
So, for Big Data Hadoop with Cloud Computing, which one are you gonna choose from?
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