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Hadoop Cloud: No one can deny the importance of cloud computing and Big Data analytics these days. As public clouds like AWS become more and more popular, businesses are trying to run all their workloads in clouds to benefit from faster innovations, business agility and cost savings. Hadoop is open source programming framework based on Java which can allow you to store and process large data sets. When data gets generated in cloud, public cloud based Hadoop is beneficial. When data resides on-premise, on-site Hadoop Cloud deployment is recommended. It is believed that Hadoop will ultimately reside in hybrid cloud. But to deploy Hadoop for data analytics in a public cloud, there are some steps that you have to consider:
1. One of the first things that you must consider is whether your cloud set-up can guarantee consistent performance. Hadoop has been primarily designed to guarantee steady performance to achieve business goals faster. When you deploy it in a public cloud, you therefore have to ensure that the provider is able to guarantee this reliability of performance. You must also know costs entailed for such a performance. When you share the infrastructure with other companies you may not have control over the server your virtual machine is using. So, you can very well face problems from neighbors if they run rogue on the server in which your virtual machine is operational.
2. Another important factor to check for is whether your cloud provider can guarantee the kind of availability which your Hadoop deployment offers. Hadoop offers many architectural guidelines to make sure that there is availability against failure of hardware. In a cloud you will not have “rack awareness”; so, you need to know how high availability will be guaranteed particularly to safeguard against rack failures.
3. You must also find out whether the cloud offers cost-effective and flexible resources. Hadoop will require linear scaling of resources because the data you need continues to expand rapidly. You have to therefore understand the implications on costs if you have to scale the infrastructure every time. Not every compute node is designed to be equal; you will find some to be heavy on the processors while others will offer more memory. So, you need to select compute nodes which have better processors and higher RAM.
4. You should also find out if the cloud will provide guaranteed bandwidth for the Hadoop operations. Hadoop Cloud will need a lot of network bandwidth for running its tasks faster because the aim is to accomplish business insights quickly. When you have cloud based deployments, you know that guaranteed bandwidth comes with costs. Since in a cloud, the physical network gets shared among many tenants, you must first make sure you understand all the Quality of Service policies for bandwidth availability before you install Hadoop.
5. You have to also find out if the cloud can provide flexible and economical storage facilities. Performance and capacity are the most important considerations in order to scale Hadoop. The traditional Hadoop installation will need replicating data thrice over to protect it from losses because of hardware failures. So, this means that you will also need three time storage capacity apart from the network bandwidth specifications. As far as performance goes, Hadoop needs availability of high bandwidth storage in order to carry out sequential reading-writing of data to get jobs done faster. For better performance, you can use servers having DAS storage or shared storage options which are resilient to disk drive failures.
6. Another step to consider when deploying Hadoop in the public cloud is whether data encryption options are available or not. This is a prime security policy especially for businesses in healthcare sector. So, you need to inquire if the Hadoop deployment can support data encryption and learn about the scaling, performance and pricing implications.
7. You should also learn how economical and simple it is to get data in or out of the cloud before installing Hadoop. The cloud will offer different pricing structures for feeding, storing and shifting data outside the cloud. Not all features that you require will be present in all cloud sites. So, you may have to establish the Hadoop cluster in certain specific locations. This is why you need to know how much the costs will be for moving data in or out of a cloud location.
8. Finally, you must learn how simple it is to handle the Hadoop Cloud infrastructure inside the cloud. With deployments growing, you may need backup services or disaster recovery solutions. So, you should ideally take into account management implications of expanding your Hadoop cluster.
To conclude, Hadoop Cloud based data analytics have been attracting many people and most have started using it in their on-site data centers. The public cloud has grown in the recent years and today there are many businesses which are keen to explore its benefits. The above mentioned factors need to be considered when you are considering Hadoop deployment in the public cloud.
