Whether you need to analyze large data sets or deploy a cloud, building big infrastructure is a big job. StackIQ makes the job easier by offering a comprehensive software suite that automates the deployment and management of big infrastructure. If your environment has hundreds or thousands of servers supporting Big Data, Analytics, or High Performance Computing, our Rocks+ management software may be just what you’ve been looking for. Use Rocks+ to get the most out of your expensive hardware, free up your IT team, and have the flexibility to pick and choose the right components for your solution.
Deploying Big Infrastructure with Rocks+ Rolls
By using Rocks+ to select from the wide range of software modules (Rolls) StackIQ offers, you can create the right software stack for your application. Our software is designed to let you get the most from your physical or virtual infrastructure, every time. Once you have chosen the software stack you need, the Rocks+ parallel installer brings up every node, networking, and storage appliance in exactly the state you need—ready to go. The engineering and testing effort behind our big infrastructure solution frees administrators from the do-it-yourself, on-the-fly approach some other vendors offer, replacing it with a predictable, single step approach to a working solution.
One Customer’s Story
Rocks+ is the fastest way to spin up Big Infrastructure from bare metal. A hyper-scale web company recently used Rocks+ to deploy their custom Hadoop distribution across a large data center. As the metric for their proof-of-concept, they successfully leveraged Rocks+ to upgrade and redeploy the entire cluster from bare metal in less than 30 minutes.
“Big Data” refers to the tools and technology for managing and analyzing very large data sets. Commercial, scientific, and government organizations use Big Data to do all kinds of things like spotting business trends, optimizing ad placement, preventing disease, and fighting crime. Processing data that is measured in petabytes requires a special kind of cluster. Rocks+ lets you build highly scalable clusters using Hadoop software to crunch those numbers.
The Hadoop Roll adds a complete Hadoop stack to Rocks+, reducing your time to production. By integrating the powerful Rocks+ management interface with Hadoop distributions from Apache, IBM, Cloudera, MapR, we make it easy to customize your Hadoop cluster. For example, you can run multiple MapReduce instances over a single Hadoop Distributed File System, or partition, scale, and upgrade clusters with ease. If your Big Data needs call for NoSQL data, StackIQ has you covered with Rolls for MongoDB and Cassandra.
Using Rocks+ on Amazon Elastic Compute Cloud is the simplest way to manage large, connected clusters for Big Infrastructure in the cloud. It brings together all the power of Rocks+ with the convenience of on-demand cloud computing so you can spin up fully configured clusters, quickly, consistently, and reliably. Rocks+ on Amazon Elastic Compute Cloud includes support for all the same software our users leverage in physical environments, such as Hadoop, MongoDB, Cassandra, and all of the HPC Rolls. Rocks+ also provides a powerful framework for defining your own server types and adding software into the distribution to meet the specific needs of your organization.
The open source Rocks Cluster Distribution has been the de facto standard for building and running compute clusters for more than a decade. Rocks+ HPC is the commercial edition of Rocks that provides an end-to-end cluster operating environment to manage the Linux operating system (Red Hat Enterprise Linux 6, CentOS 6, Oracle Linux 6), cluster management middleware, libraries, compilers, and monitoring tools. All the software you need to build a robust, state of the art HPC cluster is available, including OFED, Intel Developer, Moab, Univa Grid Engine, PBS Pro, Intel Cluster Ready, and more.
Rocks+ includes software developed by the Rocks Cluster Group at the San Diego Supercomputer Center at the University of California, San Diego and its contributors.
