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xPatterns is a big data analytics platform as a service that enables rapid development of enterprise-grade analytical applications. It provides tools, API sets and a management console for building an ELT pipeline with data monitoring and quality gates, a data warehouse for ad-hoc and scheduled querying, analysis, model building and experimentation, tools for exporting data to Cassandra and solrCloud cluster for real-time access through low-latency/high-throughput apis as well as dashboard and visualization api/tools leveraging the available data and models.
In this talk I'll share some of the hard lessons we've learned in the past three years while leveraging Cassandra (and Hector) in large-scale enterprise-grade deployments. We will focus on three specific areas, in which we identified consistent best practices & design patterns: data model optimization as a result of exporting data from HDFS/Hive/Shark into Cassandra through Spark/Hadoop MR jobs under Mesos with throttling, instrumentation & resilience features, automatically publishing geo-replicated, instrumented and monitored REST API's on top of the exported Cassandra data, and lessons learned from running Cassandra at scale from 0.6 to 2.0.6, including performance tuning, tips & tricks.
Claudiu is Atigeo's Senior Director of Engineering, Platform Services, and oversees agile engineering teams in the US and Romania while also acting as Lead Architect in building and operating xPatterns, an enterprise-class, Big Data Analytics platform. Claudiu has 17 years of industry experience in various roles, with a strong passion for Software Architecture leveraging industry best patterns and practices and contributing with a significant level of innovation. His experience spans across the Open Source, Big Data and Microsoft's Windows/.Net technology stacks.