9 Tips for Securing Big Data
#7 Use secure automation:
In a multi node environment, it’s pretty important to ensure the security of data being used across the enterprise. Automation tools like Chef and Puppet are some of the best known tools across the enterprise platform. These tools help in patching, application configuration, updating the Hadoop stack, collecting trusted machine images, certificates and platform discrepancies.
#8 Add logging to your cluster:
"Big data is a natural fit for collecting and managing log data," Lane says. "Many web companies started with big data specifically to manage log files. Why not add logging onto your existing cluster? It gives you a place to look when something fails, or if someone thinks perhaps you've been hacked. Without an event trace you are blind. Logging MR requests and other cluster activity is easy to do and increases storage and processing demands by a small fraction, but the data is indispensable when you need it."
#9 Implement secure communication between nodes and between nodes and applications:
The best method to implement security between nodes and applications is by installing an SSL-TLS implementation which can protect the whole network. If the organization is using an average built network, then it is recommended to integrate the system with stack applications.
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