Break IT down: Five ways capacity management analytics can address workload balancing issues

By: Ken Christiance

Most organizations today combat risk in virtualized infrastructure by significantly over-provisioning hardware. Excess capacity is a cost viewed as a necessity because of the complexity of these new environments. But this inefficiency can be avoided by optimizing workload placements and right-sizing virtual machine (VM) allocations to simultaneously combat both risk and capacity waste.

Capacity Management Analytics (CpMA), powered by Densify cloud optimization technology, is a SaaS solution that combines industry-leading analytics and expert insights from trusted advisors to enable IBM and its customers to optimize the use of hybrid cloud resources.

As environments grow and workloads change, what was once optimal may no longer be so. CpMA, a capability of IBM Services Platform with Watson, predicts when changes in the environment are required and autonomously rebalances workloads in real time as conditions change, thereby avoiding performance issues and dramatically reducing VM motioning and volatility.

CpMA finds the best possible hosting environment for your applications, whether that’s on-premises, in the public cloud or on bare metal servers, considering all utilization, technical and business requirements. The technology can also automate the process in real time for fast access or to reserve capacity for future placements.

CpMA provides detailed reports and prescriptive, automatable recommendations to address the following issues:

  1.      Over-allocated VMs are a common area of waste, particularly in cloud environments where self-service models allow users to determine allocations. CpMA helps ensure that service levels are   met according to policies and specifies exactly how much resource each workload requires so you can confidently reclaim and reallocate resources.
  2.      Inefficient workload placements are resolved with precise placements that safely “densify” server capacity and fit the workloads onto the minimum amount of infrastructure.
  3.      Under-allocated VMs are reassigned to help right-size VM loads, whether you are using a standard instance catalog for clouds or custom VM allocations.
  4.      Host and environment imbalances are remedied so that each workload gets the resources it needs and changes are made in advance to avoid performance issues.
  5.      Inadequate capacity at the cluster and environment levels is addressed through visibility into resourcing status at a cluster or environment level to aid in procurement decisions and forecasts.

CpMA offers visibility into workloads operating in internal VMware and IBM PowerVM environments as well as in Microsoft Azure, Amazon Web Services and IBM Cloud environments, providing a single point of control for all your workloads. With CpMA, you get:

  • Visibility across all workloads in your hybrid cloud to help ensure no workload goes unmanaged
  • Right-sizing for workloads so that they get the right amount of resources to keep costs under control and ensure performance
  • Routing analysis to determine the right hosting location for workloads, whether in the public cloud or internal VMware or IBM PowerVM infrastructure

Start your free trial of Capacity Management Analytics today and learn more about IBM Services Platform with Watson.

 

Brett Philp, IBM Partnership Technical Architect and Director at Densify, contributed to this article.

About The Author

Ken Christiance

IBM Distinguished Engineer

Ken Christiance is an IBM Distinguished Engineer with 30 years’ experience and a member of IBM’s Technology, Innovation and Automation team that supports architecture and solution design for system automation, virtualization, and distributed server management. Ken is patented and published in technologies that provide usage accounting and billing, policy-based automation, network design, virtualization, and service... Read more