How to choose the right DCIM tool for better configuration
DCIM tools can ensure your data center runs efficiently by keeping track of hardware, software and the physical environment. Here's what you should consider before choosing one.
DCIM tools come in many varieties geared toward the different management needs of organizations. Each offering usually contains multiple modules, and some include cloud-based SaaS tools. It therefore takes time to configure each tool to reap its benefits.
Before adopting a DCIM tool, you should examine whether a vendor's APIs can integrate with the tools already used in your data center.
Consider what your data center requires in terms of comprehensive infrastructure management. For example, an organization that houses most of its infrastructure in its own facilities might require more cooling data to keep its servers running, while those that rely on colocation might prioritize accurate power usage data to avoid overpaying vendors.
Before adopting a DCIM tool, you should examine whether a vendor's APIs can integrate with the tools already used in your data center. For example, DCIM offerings do not generally include network management capabilities. If you use tools to manage your network that are not part of an integrated DCIM package, you should ensure that any DCIM tool implementation doesn't disrupt your networking.
What to look for in a DCIM tool
You can't manage what you can't measure. Organizations with hyperscale data centers have proven that in spades. Profits from such businesses hinge on squeezing every bit of capacity and watt of power out of every piece of equipment. To effectively do this without pushing the data center too far, you must have access to good metrics and document every approach taken.
Power and cooling monitoring services should provide instant notification of any problems. Power usage effectiveness tracking can help you save on energy costs. If your organization operates remotely, asset management might be even more important -- especially if you have several colocated facilities.
When considering remote management tools, start by identifying and prioritizing what you must know about your infrastructure to keep it running efficiently. Configure your dashboards to provide just the information each user needs.
Asset management
In a nutshell, asset tracking keeps a record of the hardware you own, where it's located in your facility and what software runs on it. However, good asset management encompasses more than just asset tracking. It starts with building a good digital twin, then calibrating it regularly to ensure it continues to accurately reflect your real infrastructure.
Once configured, a good asset management tool provides you with more information than just rack and rack unit numbers, or which cables connect to which ports. It should also tell you what hardware and programs could be affected if a device is removed or fails. Asset management tools also keep track of software updates, which are a critical part of system security.
An asset manager can generate work orders. For example, it can provide explicit instructions to on-site personnel to unplug and reboot a specific server, or to remove or replace a piece of hardware. It should enable you to track task progress -- as it takes place and after the fact -- and tell you what happens when a task is completed.
An asset manager can also be used in conjunction with a predictive analysis tool to confirm you have the appropriate rack space, power and cooling capacity to install a specific device before generating a work order.
Manage remote infrastructure
The Covid-19 pandemic changed the way businesses value software management tools in their data centers. When operations staff could no longer work in their familiar computer rooms and large hosting sites banned customers from entering, organizations found they required strong remote management tools to keep their IT infrastructure in working order.
The very low latency demands of 5G and IoT make edge computing more important than ever. Smaller edge facilities must be just as useful as larger data centers, but should require little to no staffing. As a result, businesses using devices at the edge should have strong remote management capabilities and might consider AI for predictive analysis.
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