Workload Management

Turbonomic Showcases Workload Automation for Hybrid Cloud at Cisco Live Europe

Grazed from Turbonomic

Turbonomic, which delivers workload automation for hybrid cloud, announced details of its platinum-level sponsorship of Cisco Live at the Fira Gran Via in Barcelona. Experts from Turbonomic will demonstrate the latest technologies for automating and optimizing today's complex hybrid cloud infrastructures at booth P1. 

By 2020, 83% of enterprise workloads will be in the cloud (LogicMonitor,'Cloud Vision 2020: The Future of the Cloud Study'). This transformation introduces an ever-increasing set of complex tradeoffs for IT staff, such as whether to place workloads on-premises or public cloud, when and how to scale up or scale out workloads, and what resources to allocate without overprovisioning. To de-risk this transformation, IT organizations are turning to self-managing and real-time workloads. Ben Nye, CEO at Turbonomic, will explain how to use workload automation to optimize hybrid cloud estates at the C-Max Theatre on Thursday 1st February at 14:30 CET. In this session, Nye will also discuss how Turbonomic and Cisco are working together to assure application performance at the lowest cost, while maintaining compliance policies across hybrid cloud estates. 
 

Nimbix Teams with Xilinx to Expand FPGA-Based Workload Acceleration in the Cloud

Grazed from Nimbix

Nimbix, a leading HPC cloud platform provider today announced the immediate availability of the Xilinx SDAccel development environment for on-demand development, testing, and deployment of FPGA-accelerated workflows in the Nimbix Cloud, powered by JARVICE.  The SDAccel development environment combines the industry's first architecturally optimizing compiler supporting any combination of OpenCL, C, and C++ kernels, along with libraries, development boards and industry standard development and run‐time experience for FPGAs.

The new offering will dramatically lower the barrier to leveraging the high performance, energy efficient power of FPGAs to accelerate high end computational workflows across all industries.  Developers can now run these tools in the cloud and then test and deploy on the latest Xilinx-accelerated hardware with no upfront investment or equipment purchases.

Google Cloud Platform Supports Windows Workloads

Grazed from InformationWeek.  AuthorL: Thomas Claburn.

Add windows to a room and everything looks brighter. Add Windows to a platform and you open doors to new customers.  That's just what Google has done as it races with Amazon Web Services, Microsoft Azure, and other companies to attract business computing clients to the cloud.

Google on Monday said that customers now can use Windows-based workloads on Google Cloud Platform. The company is offering Microsoft License Mobility for Google Cloud Platform, which allows Microsoft customers to run Microsoft software on third-party services...

Best practices for moving workloads to the cloud

Grazed from CSOOnline. Author: Pierluigi Paganini.

The rapid diffusion for the cloud computing paradigm and promised benefits for the adoption of cloud infrastructure are attracting a growing number of businesses and organizations. Of course, it is essential for organizations to maximize the benefits of migration to cloud architecture by reducing costs and minimizing risks.

Cloud computing represents a fundamental change in how companies use and provide their services. For many small and midsize businesses, it represents a choice to compete in a business environment with powerful competitors. IT managers are today inundated with countless business proposals. For this reason, I will give you some useful insights for moving workloads to the cloud...

Heirloom Computing Partners With CloudBees to Move Mainframe Workloads to the Cloud

Grazed from Heirloom Computing. Author: PR Announcement.

Heirloom Computing Inc. today announced a new partnership with Java Platform as a Service (PaaS) provider CloudBees to speed the transition of mainframe workloads to the CloudBees PaaS. With the partnership, Heirloom will help IT managers lower costs and modernize their COBOL-based mainframe workloads by deploying them to the cloud, utilizing Heirloom Elastic COBOL and the CloudBees Platform. Deploying Heirloom’s Elastic COBOL on CloudBees is simple – watch this short video for a demo: http://youtu.be/4QmKvt0L9zo

Heirloom Computing is on a mission to efficiently modernize the world’s business-critical enterprise software applications. Heirloom seamlessly migrates legacy systems to private and public cloud computing infrastructures, enabling IT departments to reap the cost benefits of cloud computing and satisfy user demands for applications accessible via web browsers and mobile devices...

Consider the Cloud for Dynamic Workloads

Grazed from WindowsITPro.  Author: B. K. Winstead.

When you mention cloud computing, most IT pros probably think of outsourcing their company's applications and infrastructure. Certainly, that model is appropriate in some businesses. However, there are other circumstances that might call for cloud computing in a dynamic or temporary deployment, and a recent survey suggests that more businesses are looking at this model for uses such as big data or media files.

The survey was prepared by cloud security vendors CloudPassage and received input from 201 IT professionals ranging from C-level executives down to the systems administrators in the trenches. One of its key findings indicated that 70 percent more companies are planning to use public cloud environments for temporary workload or big data in 2013 as compared to 2012...

Cloud Computing: The Future of Workload Management

Grazed from HPCWire.  Author: Chad Harrington.

The essayist Paul Valery once quipped, "The trouble with our times is that the future is not what it used to be." Surely, there is truth in that. The future of workload management continues to evolve; it is definitely not what it used to be.

As we look toward the future of workload management, we see three major trends: application insight, big data awareness, and HPC clouds. The trends are inter-related and we'll discuss each in turn.

Application Insight

First, workload managers need to have greater insight into the applications they run. The more deeply the workload manager can understand the workload, the more efficiently it can schedule, manage, and adapt the computing environment. Today's workload managers understand basic workload requirements and can track an application's progress. However, there is more that can be done. In the future, we'll see more emphasis on understanding an application's purpose and key metrics. If the workload manager understands the application's current and future needs, it can make much more optimal decisions. Metrics such as I/O bandwidth, memory allocation, storage space, CPU and GPU cycles, etc., all help the workload manager understand an application in order to optimally manage it...