Security and Disaster Recovery for Your Hadoop Clusters

Meetup has been updated. RSVP soon. Refreshments and food will be provided.

Part I: Securing Your Hadoop Cluster—Challenges and Lessons Learned

Security is an integral part of big data platforms. The big data community has been making great strides in recent years to secure Hadoop clusters where all aspects of security are now covered—authentication, authorization, encryption of data-in-transit, encryption of data-at-rest, and centralized auditing. At the same time, many challenges are still facing cluster administrators who are responsible for setting up security, and developers who are charged with integrating new services into existing secure clusters. In this talk, we’ll cover basic concepts that form the foundation of big data security such as Kerberos/SPNEGO, impersonation, TLS and encryption key management. We’ll discuss challenges we’ve had in deploying the Hadoop clusters in real-world scenarios and lessons learned when integrating new components/services into secure clusters.

Presenter: Richard Ding, IBM
Richard Ding is big data architect for IBM, who is responsible for the security aspects of IBM Open Platform and IBM BigInsights, IBM’s 100% open source Hadoop distribution. Over the past years, he has been working with customers to setup secure Spark/Hadoop clusters and helping developers to integrate new services into secure clusters.

Part II: Disaster Recovery on Hadoop

As organizations’ maturity levels around big data technologies increase, we’re seeing a rise in the use of Apache Hadoop as a component of business-critical systems which raises new risks from an IT management perspective. They need the same kind of protection as any other tier-one system, in terms of high availability and disaster recovery capabilities. In this meetup we will focus on different replication strategies that can be leveraged based on RTO and RPO requirements and their pro's and cons.

Presenter: Vinayak Agrawal, IBM
Vinayak (Vin) Agrawal is the Product Manager for Big Replicate at IBM. He started his career with IBM after earning his masters from Carnegie Mellon University, Pittsburgh. He has worked in multiple technical roles for BigInsights product. He has been working on the Hadoop platform and other open source technologies for 5 years and has deep understanding of these technologies. He has implemented Hadoop projects in various industries for multiple mission critical use cases.