Simplify Spark deployment and boost performance with a converged, enterprise-grade solution
Organizations seeking to gain competitive advantage from their big data analytics are turning to Apache Spark in increasing numbers. To help organizations overcome barriers to adopting Spark in production environments, IBM has developed IBM® Platform™ Conductor for Spark. This multi-tenant solution allows organizations to deploy Spark efficiently and effectively so they can take advantage of the higher-performance processing Spark delivers compared to MapReduce.
Implementing Spark can pose significant challenges, including investment in new expertise, tools and workflows. Additionally, setting up ad hoc Spark clusters can lead to inefficient use of resources, management challenges and security issues that all impede deployment of Spark in a production environment.
IBM Platform Conductor for Spark is designed to address these issues in an enterprise-grade solution. A proven, efficient resource scheduler provides fine-grain resource allocation, helping to deliver improved resource utilization and a faster response to business-critical demands. The solution also includes a framework for workload management, monitoring and reporting—as well as highly effective storage management.
Unlike competitive open source offerings that require piecemeal assembly of components, IBM Platform Conductor for Spark is a converged solution that is backed by IBM services and support. For organizations looking to realize faster time to insight for big data analytics, IBM Platform Conductor for Spark offers compelling advantages over open source schedulers such as YARN and Mesos.
IBM Platform Conductor for Spark enables organizations to:
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