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Schneider Electric - Solutions Feature

Digital Remote Monitoring and How it Changes Data Center Operations



Executive summary

Today's data center power and cooling infrastructure has roughly 3 times more data points / notifications than it did 10 years ago. Traditional data center remote monitoring services have been available for over 10 years but were not designed to support this amount of data monitoring and the associated alarms, let alone extract value from the data. This paper explains how seven trends are defining monitoring service requirements and how this will lead to improvements in data center operations and maintenance.

Introduction

Data center digital remote monitoring services1 have been around for over 10 years but older offline traditional services are limited compared to new digital2 services available today (see Table 1 for comparison). These new services incorporate technology such as cloud computing, analytics, and mobile apps.

Inside a data center today, a manager has no idea when they should replace a component in their UPS or cooling unit that is about to fail. In contrast, outside the data center, a driver gets an instant notification on their smart phone that their normal route is backed up 20 minutes with a recommended alternate route. This disparity has prompted us to look at how advancements and trends in IT are changing data center monitoring and, in turn, how digital remote monitoring will change data center operations and maintenance.

The general concept of monitoring today is widely understood and anyone with a fitness tracker, continuous glucose monitor, or a learning thermostat has had firsthand experience in how advances in IT have improved their lives. In particular, users benefit from immediate knowledge from their devices (e.g. calories burned, blood sugar level, etc.). However, most data centers today are not benefiting from big data analytics and machine learning. These and five other trends are poised to revolutionize how managers operate and maintain data centers.

This paper explains seven trends that are defining next-generation data center monitoring and its benefits. We describe the requirements to attain these benefits, and describe how data center operations and maintenance will evolve in the future.

Table1

Table 1 — Comparison between traditional and digital remote monitoring

Difference between traditional and digital

A key differentiator between these two types of remote monitoring comes down to the definition of online3 – "connected to a computer, a computer network, or the Internet"

Traditional remote monitoring is not an online service therefore it cannot provide real-time monitoring. Instead it relies on intermittent status updates (usually via email).

Digital remote monitoring is online and connected to a data center (usually through a gateway) which allows for realtime monitoring. In addition it uses IT services such as cloud storage and data analytics.

Trends Influencing Monitoring

Schneider

Monitoring services available 10 years ago were desktop-based, limited in data output, and largely reactionary (i.e. depended on humans to interpret what was wrong). Digital remote monitoring has resolved these limitations through technology, and over the next few years more limitations will be addressed by technology. We see seven technology trends that are influencing data center monitoring.

  • Embedded system performance and cost improvements
  • Cyber security
  • Cloud computing
  • Big data analytics
  • Mobile computing
  • Machine learning
  • Automation for labor efficiency

We briefly describe these trends in this section and, in the next section, we describe the digital remote monitoring requirements needed to comprehend, mitigate, or take advantage of these trends.

Embedded system performance and cost improvements

Embedded systems are found in nearly all data center devices including cooling units, PDUs, UPS, chillers, etc. and basically control the operation of these devices. Without the outputs from these embedded systems, there would be nothing to monitor. Embedded systems have improved significantly over the years in terms of computing capability, data storage, communications, and pricing. This means data center devices today can provide much more data today than they could 10 years ago. We estimate that the total number of alarms and notifications available from power and cooling devices have increased over 300% over the last ten years. This increase comes from a combination of more sensors, more features, more algorithms, and higher sampling rates. The more data available, the more digital remote monitoring can infer helpful information from data center devices, as we describe later in the paper.

Cyber security

Cyber security is one of the biggest concerns5 among data center managers around the world. Not only are they concerned about IT equipment vulnerability, but also physical infrastructure equipment that has been exploited as "backdoors" into the IT network. Digital remote monitoring, as well as other cloud-based services, must comprehend cyber risks even before the product or service is created. Digital service providers need to demonstrate their secure development lifecycle (SDL) practices and policies. Ask for their SDL policy, and validate that the lifecycle includes phases that focus on training, security requirements, design, development (e.g. coding standards), verification, release, deployment, and response. In terms or architecture, there should be a single point of entry into your network using a gateway (usually software), and all devices communicate with the gateway. Figure 1 illustrates a recommended digital remote monitoring architecture.

There are several other factors that data center managers and security stakeholders must consider when evaluating a vendor and their digital remote monitoring service, therefore we discuss this topic further in White Paper 239, Addressing Cyber Security Concerns of Data Center Remote Monitoring Platforms.

Figure1

Figure 1 — Recommended digital monitoring architecture

Cloud computing

Cloud computing is a highly scalable method of storing data and processing that data. Cloud computing is what enables digital remote monitoring services. IT services such as predictive analytics and machine learning can run on a cloud computing platform to further increase the value of data center monitoring.

Big data analytics

Big data analytics may seem far from the mainstream but it applies to activities performed today such as condition based maintenance (also referred to as predictive maintenance) for plane engines and predicting how many products manufacturers make for the holidays. A spreadsheet or database can only go so far to identify patterns in data. Big data analytics is required when6:

  • data volumes increase (e.g. petabytes of data)
  • data becomes unstructured (i.e. data variety like emails, free-form text fields, or trouble tickets)
  • data is processed in real-time (this is known as velocity)

Mobile computing

Global use of mobile phones to access the internet has grown year over year for the last several years while access through desktops has decreased year over year7. This trend applies also to data center managers who are increasingly asked to do more with fewer resources. Mobile computing helps alleviate this burden by allowing managers to float between locations without being disconnected from daily operations.

Machine learning

Machine learning is related to data analytics in that it uses data to make predictions but it's different in that it improves the model by using results from previous learning8. Machine learning can be used to drive an autonomous vehicle, recognize speech, recognize images, chose a Netflix movie, or accurately model the PUE of a very complex Goggle data center. In all of these examples, the driving, the recognition, etc. improves over time.

Automation for labor efficiency

Automation for labor efficiency is not a "hot" trend but it's particularly relevant to data center managers in an increasingly competitive business environment where they are being asked to do more with less. This is where automation through digital remote monitoring can help.