Given todays challenges with the at home economy, schooling & zooming, we need to focus more than ever on cleaning up our house and our Data Center. The ongoing trend toward multiple computing models, with workloads spread across on-premise, public cloud and hybrid environments, data center managers require more visibility and operational control than ever before. Subsequently, server asset management is essential when IT staff are making decisions based on the available computation and storage capacity. But with such an overwhelming number of IT assets to track and monitor, especially in large-scale data centers, the task of server asset management has gradually become an efficiency bottleneck.
Enterprises and cloud service providers (CSPs) very often manually maintain and manage server assets through a configuration management database (CMDB). Asset information includes CPU, memory, hard disk model, serial number, capacity and other information.
However, asset management solutions of this kind usually offer limited scope and cannot be easily integrated into existing systems. Moreover, this method presents a number of problems, such as low data entry efficiency, the failure to update data in real time, and the inability to track server component maintenance updates.
Additionally, many large data centers remain hamstrung by the outsourced hardware maintenance model.
With this approach, an operations and maintenance center confirms a hardware failure and then submits work orders to the onsite hardware supplier, and after the field personnel completes the batch replacement of parts, they provide feedback to the remote operations and maintenance center through the work order system.
This mode has glaring efficiency problems. The feedback information is slow, and manual remote login to the server is needed to confirm whether the parts were correctly replaced, as required.
Adopting a Lean Asset Management Approach for Improved Data Center Efficiency
Lean management practices, a function of lean manufacturing that sought to increase productivity and efficiency by eliminating waste in the automobile industry, date back to the 1940s and Taiichi Ohno, a Japanese industrial engineer, who is considered to be the father of the Toyota Production System, later adopted in the U.S., and worldwide.
With respect to lean asset management, Ohno advocated for a clear understanding of what inventory is required for a certain project, real-time visibility of what capacity is available and what is already committed, and a streamlined replenishment process. He also believed that inefficient processes will always cause delays, if not excess inventory (over-provisioning) and idle resources (underutilization).
Through the practice of lean asset management methodology in the data center, IT staff gain the ability to manage the server assets in a fine-grained manner, such as tracking the model, brand, capacity, serial number and other information of the main components of the server.
Lean asset management also enables IT teams to react quickly and efficiently when implementing change strategy. As any IT administrator will attest, change deployments and implementations can pose significant risk. When a deployed change affects systems in an unanticipated way, it can lead to service outages that negatively impact an organizations bottom line and its brand reputation.
By discovering changes in server components, it also becomes convenient for the operations and maintenance team to track changes in components in a timely manner, and improve the efficiency of the component replacement process. Its also easier to collect information concerning the data center computing resources on demand.
A Trusted Source for IT Asset Discovery and Management
Data center management solutions such as Intel Data Center Manager (Intel DCM) have the capability to automatically obtain server asset information such as CPU, memory, disk model, capacity, etc., for the various bands/models through out-of-band methods.
External applications can obtain server asset information through APIs, which are provided by the data center management solution. External systems can automatically compare device component information, find and identify information, and changes in parts.
The following is a typical scenario. The remote operation and maintenance center of a CSP discovers a server component is faulty, and requests that the supplier replace the parts onsite at the data center.
The operator has no need to double-confirm the component by logging into the server after the parts have been replaced. Furthermore, the real-time asset information of the entire data center can be reported to the IT staff at any time and before they make any decision.
To support lean asset management methodology, Intel DCM offers many asset management features, such as organizing systems in physical or logical groups, easily searching for systems using their asset tags or other details, and importing and exporting a data centers inventory and hierarchy.
Along with Intel DCMs real-time power and thermal monitoring, and its middleware APIs that allow the software to easily integrate with other solutions, these features assist companies to avoid investing in additional asset management tools.
As organizations continue to leverage multiple computing models, further dispersing their workloads, and the data center itself becomes more complex, manual processes cant keep pace with the rate of change in the IT environment.
By adopting a lean asset management approach, supported by a data center management solution with IT asset discovery and management capabilities, data center managers benefit from a trusted source of information about asset ownership, interdependencies and utilization so that they can make informed decisions regarding the deployment, operations and maintenance of their servers and systems.
So after youve cleaned our your 5th closet at home, think about cleaning your data center clutter using innovative automation tools to see these lean asset management principles at work, theres no question that Taiichi Ohno would be proud.
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