Data centers form the foundation of the IT stack and underpin advancements in the Internet of Things (IoT) revolution. Data loggers capturing IoT sensor data in real-time transmit information to backend systems running in data centers in-house or across the cloud network. Keeping data centers alive and available to process the necessary computing operations requested by front-end IoT applications is the key prerequisite of effective IoT systems.

Failing to achieve these goals with high data center uptime is catastrophic. A recent Ponemon Institute research study suggests the average cost of data center downtime is close to $7,900 per minute for organizations of various industry verticals spanning at least 2,500 sq. ft. in size. Most of this cost is associated with keeping data centers alive to maintain service uptime. These services are naturally tied with data that must be always available, with or without service uptime itself.

Power Planning and Energy Efficiency

Energy-hogging microscopic transistors processing millions of discrete computing steps in semiconductor chips housed within heaps of closed server boxes stacked all over the data center are bound to produce immense heat-loss. Running these machines on the national power grid or alternative backup power supplies is both costly and prone to outages due to overwhelming energy requirements. Adequate power utilization planning and investing in energy-efficient hardware is the critical requirement for resilient, always-alive datacenters. Data center temperature management practices such as ventilation and server positioning further improve data center efficiencies and ensure maximum service uptime while reducing operational costs. IoT-based monitoring solutions for data centers enable proactive strategies to prevent power outages, regulate data center temperature and streamline ventilation mechanisms.

Resilient System Architecture

Maintaining resilience and service availability is an ongoing process, and goes well beyond investments in power supply. The system architecture of resilient data centers is designed to manage and spread load across all machines for maximum processing efficiency and service uptime. With the concept of virtualization for data center resilience, hardware resources are masked from end-users and pooled across the user-base to accommodate peak-load spikes and maintain the wider system alive even when a few individual core components have stopped working. For instance, data loggers feeding sensor information to the backend database will almost always have the virtualized storage drives available for communication in event of unforeseen system glitches.

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Microsoft Bing data centers field 3.6+ billion searches every day

Data Feed Redundancy

Keeping data centers alive 100 percent of the time may be virtually impossible, but avoiding costly gaps in data feeds that occur due to network outages is possible, practical and in fact, critical to maintaining true service uptime. And unlike data centers that get up to speed once the system recovery process completes following an outage, front-end IoT systems capturing data cannot recover any information that’s lost during an outage unless backup storage systems are in place. The ability of data loggers to store critical sensor information allows the wider IoT network to retain and utilize information that’s not immediately transmitted to the data center or loss during transit due to an outage, otherwise causing gaps in data feeds to the backend infrastructure.

Failure to address the issue of prolonged gaps in data feeds presents chilling repercussions for organizations on various fronts. Risks include the inability to maintain regulatory compliance, compromised accuracy of the information underpinning strategic business decisions, shrinking useful life of sensitive data center equipment and jeopardizing customer confidence in the organization’s data-driven services.

Progressive IT organizations running data centers pursue cost-effective IoT-based initiatives such as redundant data loggers to serve the primary purpose of keeping data centers alive that goes well beyond maintaining service uptime: establishing a system of continuous data feeds to and from the data center.

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