Data center capacity planning is a fundamental element that requires maximum oversight. Without it, the data center is exposed to real difficulties that accelerate its loss. The performance of its applications and servers are at stake.
Data center capacity planning is the development of of an organizational strategy By the IT managers or director. This strategy consists of matching computing resources, electrical load, cooling capacity as well as workload storage.
How data center capacity planning works
To ensure results, the process requires sophisticated load calculations. It should be noted that this normal capacity is determined by comparing operations with simulated or actual load tests. This is supplemented by trend analysis or modeling using tools designed for this purpose.
In addition, there are, software tools for capacity planning. They help calculate the resources and power consumption that the data center must support. These amounts are calculated based on current operations and future forecasts. The tools range from simple spreadsheets to 3D renderings with automated resource discovery and documentation. In addition, some tools are more sophisticated. They offer outsourcing options when major power, space and cooling upgrades at the physical site are costly or time-consuming.
In the process, virtualization should also be considered. It allows center managers to consolidate servers. It is also required to stack multiple workloads on a physical server while turning off the others. Capacity planning is more flexible with virtualization and cloud computing. It scales up and down without individual investments in power or IT systems.
Why is this planning important?
“When organizations lose sight of what is happening or could happen in their environment, performance issues and capacity gaps can occur, which can lead to lost revenue, reduced productivity and an unacceptable customer experience,” says John Miecielicaformer product manager responsible for marketing at capacity management provider TeamQuestnow consultant for Stratagem, Inc.
In general, the energy consumption, space requirements as well as the cooling within a datacenter are limited. Moreover, the loads can change in an instant of an hour, a day, a week or a year.
However, performing a too large capacity for data workloads wastes capital expenditures. This over-provisioning not only leaves servers idle, but also causes costs to keep rising. Over-provisioning of the computer room air conditioners is also causing below optimal efficiency operation.
Yet, the ability to under-plan can weaken business operations. Without adequate power and cooling for the center’s workload, failures are also more frequent. The lack of computing, network and storage capacity leads to bottlenecks bottlenecks at the application level. They may even stop working or take too long to launch.
Perenniality of a datacenter is mostly based on planning the capacity of a datacenter. The success of the latter depends greatly on its ability to Run its IT resources quickly, efficiently and securely. In addition, capacity planning is an ongoing process as the influx of business-critical services continues to increase.
First of all, capacity planning not only achieve efficient use of the physical infrastructurebut also to point out potential problems. Then, it allows to predict failures and to significantly improve the efficiency. And finally, the process intervenes to ensure perfectly the quality of the commercial service. In addition, the ability to identify bottlenecks within a datacenter helps eliminate hundreds of underperforming virtual machines (VMs). As a result, scheduling plays the primary role Avoiding high infrastructure costs.
EHI, for example, opted for demand simplification. So the world’s largest car rental service provider really got its planning strategy wrong. Yet, after good study, it was the planning itself that got it out of reactive mode. He was able to understand the changes as they occurred. As a result, the necessary actions to keep the system running smoothly are always taken in time.
Tips for good planning
“Data center managers need to ensure that business capacity, service capacity and component and resource capacity meet current and future business requirements in a cost-effective manner. This has everything to do with managing and optimizing the performance of your infrastructure, applications, and business services,” says further John Miecielica. Thus, managers must always ensure that their strategy is ahead of the organization’s expansion needs.
The need for a strong DCIM
A datacenter without Infrastructure management software (DCIM) is like a computer without an operating system. Without DCIMdatacenter capacity planning is more or less impossible.
One of the main functions of DCIM is the aggregation and analysis of metrics across the data center. It looks at environmental conditions, power consumption, the condition of the equipment in use and more. On a day-to-day basis, it helps staff to maintain operational efficiency in early identification of sources of waste or potential causes of unavailability. As a result, DCIM allows operators to easily perform capacity planning tasks. Sunbird’s dcTrack DCIM software displays all assets in the center in 2D and 3D. It feeds network connectivity at the click of a button, making it an indispensable tool for accurate and reliable capacity management.
In summary, the new tools Cloud-based DCIM enable to safely and efficiently optimize power, cooling and storage capacities. They have the ability to improve the availability of physical infrastructure systems and corresponding IT workloads. These tools simplify and automate many data center management activities, allowing professionals to focus on other issues and tasks.
Clyde Sconce’s advice
Clyde Sconce is a former computer systems architect at EHI. He learned several lessons after strategy mistakes at his company. Sconce warned data center managers to Be careful with exceptions which can distort predictions about the planning strategy. According to him, it is also important Align data forecasts with current and historical business transactions.as this is ultimately the whole point of the exercise.
Sconce also advised to Base data center capacity forecasts on cyclical growth as well as linear projections.. This approach to strategy accounts for potential jumps in demand due to seasonal peaks or campaign launches.
The progressive approach and its advantages
Therefore, the incremental approach is recommended as a excellent alternative for capacity planning within a data center. First, it consists of understanding the initial requirements for powering the computing load, specifically the power requirements of servers, storage, and network devices. Then, a incremental build strategy is established, based on the expected extensions of the computing load. In fact, the strategy proceeds by developing a conservative future estimate of the maximum and minimum possible final computing load. It also takes into account the ramp-up time to reach the final computing load. From this information, A statistically “expected” load can be estimated. The approach takes into account both the capacity of the electrical infrastructure needed to supply the load and the amount of cooling required.
The incremental stepwise approach allows the power and cooling capacity to increase proportionally with the computing load. Therefore, Capital and operating expenses for equipment that are not yet required are avoided. However, the DCIM management tool cloud-based tool facilitates the implementation of the approach. As explained earlier, this tool correlates power, cooling and space resources to individual servers. As a result, it proactively provides real-time knowledge of remaining computational loads, power capacities, and cooling capacities. Although at each new stage of development, it is always possible to reassess whether future growth is still required.
So, compared to forward planning for final data center capacity, the incremental approach is more advantageous. Ideally tactical, it allows not only to reduce energy costs, but also maintenance costs. In addition, it also avoids as much as possible the unused capacity.
Source: searchconvergedinfrastructure – Credit: