IBM Spectrum Conductor

Confidently deploy IBM Spectrum Conductor and other services for a multitenant enterprise environment, both on premises and in the cloud

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What IBM Spectrum Conductor can do for you

IBM Spectrum Conductor® is an enterprise-class, multitenant platform for deploying and managing Apache Spark, Anaconda, Dask and other application frameworks and services on a common shared cluster of resources. It provides the ability to support multiple concurrent and different versions of these applications while dynamically allocating and sharing resources between tenants and applications. 

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Benefits
Increase utilization and lower TCO

Maximize usage of resources and eliminate resource silos that would otherwise each be tied to multiple instances and different versions of Spark and other applications.
Scale to meet current and future workloads

Get support for hundreds of applications and users and thousands of servers. Scale your IBM Watson® Studio AI jobs with distributed execution on an IBM Spectrum Conductor cluster.
Employ enterprise-class features

Protect data with this multitenant solution that provides end-to-end security and runtime isolation. Conductor offers Spark and application lifecycle management with IBM support and services included.
Reduce administrative costs

Consolidated framework for deploying, managing, monitoring and reporting reduces administrative overhead.
Gain a complete analytics solution

Run the included Spark distribution for easier deployment of a full analytics environment both for exploratory projects and production.
Accelerate time to results

Use efficient resource scheduling and shared infrastructure results for shorter application wait times, higher throughput and faster analytics.

Features

Highly secure multitenant support with runtime isolation

Get security-rich support for multiple users and groups with authentication, authorization and runtime isolation. Also includes multiple applications, frameworks and services, such as Spark, Python, Anaconda, Dask and others on shared resources.

 Automated and dynamic hybrid cloud bursting

Add and remove additional resources from your cluster automatically, based on policy and workload demand, with support for a hybrid mix of on-premises and cloud hosts.

 Dynamic resource sharing

Use independent scaling of compute and storage infrastructure, along with flexible allocation of resources, according to application requirements for compute resources and memory.

 Simplified Spark and application lifecycle management

Run multiple current and different versions of Spark and other compute frameworks and services concurrently on a secure multi-tenant platform.

 Single-pane management and monitoring

Simplify administration across a scale-out, distributed infrastructure.

 Integrated Spark distribution

Deploy and maintain Apache Spark with an integrated Spark distribution easily.

Resources

Community

Get technical tips and insights from others who use this product.

 Product documentation

Find answers quickly in IBM product documentation.

 Data sheet

Simplify Apache Spark deployments, speed time to results and maximize resource utilization

 Spark for Dummies

Learn how open-source Apache Spark is transforming the already dynamic world of big data infrastructure.
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