Explore Cirba by Use Case
Cirba scientifically balances infrastructure supply and application demand - creating a demand-driven approach to virtual and cloud operations that maximizes efficiency and cost-savings while reducing risk.
Explore our solution by use case
Model & Define
Cirba enables organizations to gain a complete view of new demand, whether capturing new requests through integrations to a third-party self-service portal or by analyzing the transformation. This visibility enables organizations to accurately assess and determine the optimal way to provide resources to meet the coming demand.
Cirba for Transformation Planning
Cirba's analytics set the bar in transformation planning, enabling organizations to make moves faster, with less risk and significantly lower infrastructure cost.
Only Cirba's analytics determine which workloads can be transformed, how big to make the VMs (or which cloud containers are the right fit), which workloads can go together on the same hosts from a business and operational policy perspective, as well as how to optimally fit workloads together on physical hardware to optimize density and minimize infrastructure costs. This analysis provides a comprehensive view of potential transformation candidates, as well as the workload placements, resource and infrastructure requirements to achieve the optimal balance between financial objectives, risk tolerance and performance
Creating a Scalable "Transformation Factory" with Cirba
Automate Workload Routing & Capacity Reservations
Choosing the best environment for your workloads
IT organizations are now faced with a new challenge– they need to be able to determine where to host new workloads. However, most rely on spreadsheets and are ill-equipped to determine which internal environment is suitable, or whether should the workload be hosted externally?
Cirba takes the guesswork out of placing new workloads with its Reservation Console that examines the requirements of a workload and evaluates the suitability of target environments for workload placement based on relative cost, occupancy levels and fit for purpose criteria such as operating system, software licensing requirements, storage requirements, and policy requirements.
Learn more about automating workload routing with Cirba's Workload Routing API .
Capacity Reservations for Accurate Forecasting
Most requests new workload placements within an enterprise come with some duration of lead time. This means that rather than an immediate host-level workload placement, a reservation of capacity in the right environment is required to ensure availability and accurately forecast requirements. This requires a reservation system that not only determines the optimal environment for a workload (see above), but also takes a forward looking view and holds the capacity for that time frame. Through its Reservation Console, Cirba:
- Profiles all inbound workload placement requests (from self-service portals, transformation projects, etc.) to determine their business requirements, applicable policies and capacity requirements.
- Determines where the workload should go and whether there is capacity available to fulfill the request on the planned deployment date.
- Reserves the capacity for that workload.
- If there isn't enough capacity available, determines what action is required to fulfill the request such as adding a new host, increasing memory or CPU.
Place Workloads and Allocate Resources
Most organizations today combat risk in virtualized infrastructure by significantly over-provisioning hardware. Excess capacity is a cost that most organizations feel they have no choice but to incur because of the complexity of these new school environments. The solution is to optimize workload placements and right-size VM allocations to combat both risk and capacity waste.
Cirba Optimizes Placements
Cirba optimizes VM placements in virtual and cloud environments with its multi-dimensional analysis that considers all technical, business and utilization factors and constraints. Cirba accurately determines initial placements, and will also continuously adjust these placements across physical servers to rebalance workloads, avoid hot spots, and "defragment" capacity to free up space for new instances.
The Tetris Effect of Workload Placement
Only Cirba can place workloads considering their patterns, personalities, profiles and applicable policies in order to safely maximize density. With Cirba, wasted capacity is significantly reduced and organizations save an average of 30% on hardware.
Controlling Software License Costs with Placement
Data center class software licensing provides the opportunity to license an entire physical host server and run an unlimited number of instances on that machine. To take advantage of this requires VM placements that minimize host licensing requirements and maximize density.
When factoring software licensing considerations into Cirba's placement decisions, organizations can save an average of 55% per processor licensing packages such as Microsoft Windows Server - Data Center Edition, Microsoft SQL Server, Oracle Database, Oracle Weblogic.
Cirba's Software License Control module is an add-on to our award-winning Control Console that:
- Reduces the number of processors/hosts requiring licenses.
By maximizing VM density and isolating licensed VMs from those not requiring the licenses.
- Contains the licensed VMs on the licensed physical servers.
By restricting placements of licensed VMs to the designated physical servers ensuring ongoing licensing compliance and efficiency.
Cirba Optimizes Resource Allocations
VMs must be sized properly in order to service the applications within them. In cloud environments this means selecting the most suitable (and economical) instance size from a cloud catalog. Although most clouds require the end user to select this, they often get it wrong, as they may not know what their demands will be (or may not know how to express their needs in the language of Gigahertz and Gigabytes). Cirba optimizes VM sizing for custom allocations and cloud containers.
Rebalance and Right-size VMs
As environments grow and as workloads change, what was once optimal may no longer be. Cirba optimizes virtual and cloud infrastructure by rebalancing and right-sizing workloads as conditions change. Unlike a load balancer, Cirba's placements take a broader perspective and longer term view to avoid volatility and the hidden costs of unnecessary motioning.
Receive Daily Actions to Reduce Operational Risks
Cirba's Control Console provides a simple way of seeing where risks lie in an environment - any entity in the "Too Little Infrastructure" or red zone is at risk according to workload requirements or policies. Cirba also provides specific, detailed recommended actions that can be passed through to third party systems to automate remediation in accordance with change management policies for:
- Under-allocated VMs - Cirba enables you to right-size VMs whether you are using a standard instance catalog for clouds or custom VM allocations.
- Host and Environment Imbalances - VM rebalancing ensures that each workload gets the resources it requires to avoid potential performance issues.
- Inadequate capacity at the cluster and environment levels - Cirba also tells you when a cluster or environment is running the risk of not having enough capacity.
- Assess status of physical storage, datastores, VMware Resource pools and other resources and performance metrics - Universal Sensors provides support for analyzing additional resources to quickly understand, for example, which are low on capacity, which are appropriately utilized and those that have excess capacity. Users can also select a resource, such as a datastore, to identify which Hosts and VMs are related to it.
Receive Daily Actions to Maximize VM Density and Efficiency
Alongside recommended actions to reduce risk, Cirba produces daily actions that enable you to increase efficiency by reclaiming resources and optimizing use of existing capacity such as:
- Over-allocated VMs - Over-sized VMs are a common area of waste, particularly in cloud environments where self-service models allow users to determine allocations. Cirba ensures 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.
- Inefficient workload placements - Cirba analytics determines the precise workload placements required to safely "defrag" server capacity and fit the workloads onto the minimum amount of infrastructure.
Forecasting Capacity Requirements
Cirba provides an accurate view of future compute and storage requirements through its capacity reservations and utilization trending. Through the Control Console, Cirba enables you to:
- Predict Capacity Shortfalls
Cirba provides an accurate view of when a capacity shortfall will arise. Looking into the future, Cirba indicates when storage resources, environments, clusters and hosts will experience shortfalls and helps you determine when to take action. Cirba also enables you to determine how many VMs you can fit into an environment to "use up" spare capacity and make better use of your infrastructure.