TORONTO--(BUSINESS WIRE)--CiRBA Inc., a leader in Data Center Intelligence (DCI) software, today announced new cloud planning analytics that streamline and improve decision-making processes around cloud migration. Available with CiRBA Version 6.2, these new analytics support organizations in determining how to set up their internal cloud environments, as well as determining the optimal environment, placement, instance size and software profile to migrate individual workloads to.
For organizations looking to determine which workloads should migrate to cloud infrastructure, CiRBA’s analytics factor in all the critical characteristics of physical and virtual workloads ranging from utilization patterns and personalities to configurations and governing policies. These workload profiles are assessed against possible environments, available capacity, instance catalogs, software stacks and costs to determine the optimal placements and configuration choices. Leveraging packaged analytics not only ensures consistency and accuracy in determining where workloads should go, but it also enables organizations to execute on migration strategies with vastly greater speed, lower risk and lower cost.
“Cloud migration planning can be far more complex than pure virtualization planning, partly due to the added variables of instance sizing and costs, but primarily because policies take on an even more critical role in the decision of where to place workloads,” said Andrew Hillier, co-founder and CTO of CiRBA. “When presented with pre-packaged capacity and multiple hosting options, clear guidelines are needed in order to make the right decisions. Rather than leaving this up to end users, CiRBA 6.2 provides customizable policies that govern where things go and how much resource is allocated, accelerating adoption and minimizing mistakes and rework along the way.”
CiRBA’s analytics for planning cloud migration support the end-to-end process of cloud migration planning, including:
- Qualifying & profiling workload candidates to determine suitability for migration to the cloud
- Sizing workloads and assessing workload history, patterns and profiles
- Assigning policies that impact placement decisions such as SLA requirements, privacy, security, DR, HA policies, regulations, utilization limits, etc.
- Determining the best match with suitable environments, cloud instance size and software stacks based on existing configurations, migration policies and costs
- Determining specific workload placement and resource allocation requirements
- Enabling automation through the generation of machine-readable extracts that feed provisioning tools
For organizations that are very early in the planning stages for an internal cloud, CiRBA’s analytics support key decisions around instance catalog and software stack design to align with the needs of the applications being hosted. CiRBA also enables organizations to optimize choices on hardware purchases through what-if analysis of different server configurations and specifications. These decisions are essential to ensuring service levels, performance and cost control in an internal cloud.
“Setting up an internal cloud from scratch is a very real challenge facing organizations,” said Hillier. “If the instances are not defined in a way that matches the types of workloads being hosted, then overall capacity becomes fragmented, wasting valuable resources. Moving to cloud implicitly involves standardization, which is difficult enough as it is. Standardizing on the wrong standards is an even more costly mistake that organizations cannot afford to make.”
Rounding out CiRBA’s new release are new reports that enable teams to share placement decisions and configuration choices with application owners. This level of visibility into decisions provides the business owner with the opportunity to understand the fit between applications and their chosen destinations, warding off potential conflicts.
CiRBA Version 6.2 is scheduled for release in July 2011.
About CiRBA Inc.
CiRBA Data Center Intelligence (DCI) is analytics software that determines the optimal workload placements and resource allocations required to safely maximize the efficiency of Cloud, virtual, and physical infrastructure. For more information, visit http://www.cirba.com.