IT facility management has gravitated its focus towards security in recent years.  Due to the sheer amount of sensitive information stored in servers with increased Internet commerce, a security breach can harm a business, and its customers.  High-profile information thefts have cost businesses millions of dollars and hurt reputation.  Other instances have seen important digital assets destroyed.  As a result, security protocols have been tightened and further access and identification measures have been implemented.  Protecting crucial assets and information really comes in two forms, physical and digital security.  However, they often go hand in hand.

 ”It is easier to break into a system once you are in a facility and have crossed into their logistical zone.  It is easier to log in and get information, ” says Jordan Ferrantelli, a security consultant at Aon Security Consulting.

PROACTIVE SECURITY:  Do No Harm

Loss of sensitive information can come as a result of theft.  But another pitfall is information lost because of environmental factors, or failed equipment that was not properly monitored.  Lost databases and information can be a potentially heavy blow for companies, especially those that rely on large databases to conduct business.  A hospital that has gone paperless relies on their servers for every aspect of organization, from payment services to private medical records.  Losing these records could be catastrophic for what it means to patients, and the hours or work lost.  Having security personnel on site to watch over servers is not a competent solution to protect these assets.  Temperature and humidity, as well as other factors, can cause server failure, but are undetected without the right environmental monitoring tools.  The first step in security is to be able to monitor the health of the servers, and prevent a problem before it happens.

PROACTIVE SECURITY:  Digital Threat and Virtualization

Stolen information has become a major security threat for governments and businesses alike.  The first step is to make sure the right personnel are accessing the facility.  Large- scale security breaches are an easier task once someone is on the inside and can log-in on the network.  Tracking facility site users and keeping records of those that access the site are important measures to keep a site secure.  In addition to using card-readers to allow access, have server cabinet doors trigger an alert when opened.  With proactive remote monitoring, data center managers can be alerted when there is any movement towards accessing the servers.

IT security is a battle outside the facility as well.  Extranet connections, supply chain transactions, and other digital communications have made protecting the network a more daunting task.  Virtualization in computing has also posed new risks.  As a result, new DCIM measures are being taken, with complex routing topology and more robust multi-layered encryption.  These days, attacks are being launched directly at applications like XML and SQL because such protocols are easily accessed.  Data Center Infrastructure Management solutions by companies such as IBM and Cisco offer data center security that are constantly evolving.

CLOUD COMPUTING:  Increase Risks

As more businesses move to the cloud, increased security risks are surfacing.  Because all information is transferred via Internet, data is more easily accessed remotely.  APIs that manage the content being transferred can also be breached without proactive security.  Another risk is the third party providing the cloud service.  Rigorous control of access on site is a fantastic step, but who is keeping employees of the cloud service accountable?  This boils down to faith and firm trust in the cloud provider.

INCREASE SECURITY: Uptime Devices

Uptime Devices has been a leading innovator in environmental monitoring, power monitoring, and security, for over a decade.  Their original SNMP-based monitoring unit Sensor Hub™ has been the standard for monitoring and protecting assets, while the expandable design of Remote Physical Monitor CM has allowed for unparalleled flexibility to cover multiple stations on just 1U of rack space.

Uptime Devices’ monitoring tools cover more than just natural environmental conditions.  They also offer solid security solutions.  Implement the 360° Motion Detector to trigger when there is unsolicited movement on site.  Connect the Security Sensor to Sensor hub™ to send an alert to the facility manager when a server door is opened.  There are a range of solutions through Uptime Devices to increase security for your IT environment, including network cameras, sirens, and more.  As highlighted by the most recent major security breach last week, which saw 780,000 Medicaid recipients’ data exposed, protecting your site with proactive security monitoring is a necessity.

 For more information on how Uptime Devices’ products can help protect your assets and provide solid security for your data center or IT facility, please visit our site:www.uptimedevices.com/products , or email: sales@uptimedevices.com

The predicament is two-fold.  On one hand, data centers are struggling with a physical lack of space.  Resource demands are on the rise.  A recent Information Week survey found that 54% of data center respondents said their resource demands were increasing.  On the other hand, this is causing electrical loading capacity to be maxed out.  Instead of utilizing potential power to bring in more operations that generate profit, data center operators are forced to direct their resources to cooling and network resources.

As a result of poor planning and the capacity issues mentioned above, a lot of data centers are seeing the lifetime of their infrastructure dwindle.  This is leading data center managers to implement proactive environmental monitoring to warn of potential threats to their assets.  Nevertheless, the fact is, the hardware used for environmental monitoring is also a draw on electrical capacity.  Many environmental monitoring consoles support only a handful of sensors.  This forces data center operators to buy scores of hardware devices— all of which take up valuable space and consume power.  It is clear that environmental monitoring is a need though. American company Uptime Devices designed the Remote Physical Monitor (RPM CM) with these realities in mind.  Unlike other environmental monitors, RPM CM uses efficient Daisy Chain Sensor® technology that allows up to 250 different sensors to be connected to one hardware unit.  Instead of being forced to invest in a growing number of bulky hardware units, operators can monitor efficiently with a RPM CM unit that grows as the business operations grow.  The bottom line— with the RPM CM, data center operators are able to monitor large amounts of units from one hardware piece.  Using other environmental monitoring providers, data center operators are forced to buy sizeable quantities of hardware that consume infrastructure and electrical capacity.  As data center capacity becomes an issue, consider an environmental monitoring choice that doesn’t add to the capacity problem.

For more information on how Uptime Devices’ Environmental Monitoring products can help protect your assets business implement a more profitable billing structure, please visit our site:www.uptimedevices.com/products , or email: sales@uptimedevices.com

Data centers are starting to rethink how they manage their billing structure. Most data centers do charge for things like storage and network bandwidth.  However, the energy and heat produced by frequently engaged servers leads to a lot of extra costs for data center operators.  Consider all of the extra power consumption.  Cooling becomes more costly— not solely because of the energy cost, but also because of the ongoing maintenance needed for a constantly blowing HVAC.

Many businesses have usage-based billing structures that take in consideration the consumption of their company’s billable resources.  The most obvious example is a phone company. Usage charges range from time-of-day based rates to minutes used.  Many Internet providers are exploring a similar course, billing their customers if they exceed a defined limit of bandwidth.

For the data center there is a clear advantage to usage based billing.  Offsetting the costs of busy servers has to come from somewhere.  If 5% of a data center operator’s clients are responsible for 85% of energy usage, is it fair to pass the costs on to everyone? Raising prices on every client risks scaring away loyal customers and hurting the bottom line.  The answer is to pass the costs to the clients responsible for the excessive energy.

How does a data center operator pinpoint which of the client’s servers are consuming the most power?  Submetering.  Intelligent power submetering is an effective way to measure where the costs are coming from.  By providing an accurate picture of where the energy costs are coming from, a data center operator can confidently translate where the excessive energy is produced into hard figures.  Over time, daily readings can give a good overall picture, thereby allowing a business to determine their billable resources.  The result is a profitable billing structure that stabilizes the growing costs of a business’ energy.

For more information on how Uptime Devices’ Intelligent Power Meters can help your business implement a more profitable billing structure, please visit our site: www.uptimedevices.com/products , or email:sales@uptimedevices.com

Rising energy costs have created more discussion on the need for accurate energy use monitoring. At Uptime Devices, we made sure our newest infrastructure monitoring solution, the RPM Console Manager, came equipped to host ANSI billing class power meters.

Uptime Devices is based out of Austin, Texas, and, the problem of rising energy prices has been illustrated perfectly in our own backyard. Currently, City of Austin Electricity is negotiating with Austin City Council on sizeable electric bill hikes from small businesses to homeowners. While schools get a deserved break on the proposed new rates, unfortunately, according to the Austin-American Statesman, “businesses such as hospitals and data centers would see rates rise as much as 20 percent”.

With the upward trajectory of green energy, many electric utilities are seeing their profits diminished as more businesses switch to alternative solutions for their power. As a result, electric companies are increasing bills. There are several arguments for accurate power metering.

Load Profiling and Benchmarking

Monitoring your energy enables a business to see if the load profiling they are getting from the electric company is accurate. It also allows for pinpointing where excessive energy might be cut and makes for more efficient energy use.

Data Center Tenant Cost Allocation

Accurately monitoring power in a data center means being able to assess which users are using the lion’s share of resources. For example, if one customer is utilizing 25% off all resources with busy servers, action can be taken to minimize costs.

Net Metering

For businesses employing renewable energy resources, monitoring energy usage can mean more money back in incentives. Intelligent power meters relay TOU (time of use) and allow for strategic planning for electricity minimization.

Green Building Initiatives and Energy Conservation

While initiatives vary from country to country and state to state, a growing number of places, such as California, are executing large initiatives meant to protect resources and protect the environment. Reporting energy efficiency can also be a great public relations tool, not to mention the satisfaction of being a responsible member of the community.

For more information on Uptime Devices’ Intelligent Power Meters, please visit our site: www.uptimedevices.com/products

The truth is, there is a tremendous business value in proactively implementing data center infrastructure management (DCIM). With the right monitoring tools, the need for maintenance can be minimized. Moreover, staff can be equipped with accurate symptoms that can prevent costly breakdowns.

As old data center architectures are getting deteriorate, inefficiencies are surfacing that reveal an ongoing extraneous cost. As upper management become more informed on the benefits of DCIM technology, they are progressively setting aside budget dollars for DCIM. Instead of another cost, it is seen as a significant cost-saver.

Here are a handful of facts and data that support DCIM and the modernization of data centers.

IT architectures are changing, but shedding assets is a costly option.

Replacing IT hardware is a costly undertaking. Investing in new data center infrastructure means swallowing the cost of the initial investment. Financially, this is difficult to justify. Technology is always changing, and by the time the old infrastructure is replaced with the new the industry is already on to the next thing. What results is a vicious cycle of unsustainable cost. The prudent approach is to maximize the full lifetime value of the existing IT assets available through proactive infrastructure management. A flexible DCIM allows business to expand its capabilities to meet new needs.

Energy Costs will always be unpredictable.

No matter where a business’ data center resides, it is certain that energy costs will remain volatile. Energy costs will always be on the rise due to more demand. Optimizing energy loads can go a long way in energy savings. This can be achieved through proactive environmental monitoring and data center cooling. As an added incentive, the public face of the business can be enhanced by touting green credentials.

Building new data center facilities is costly.

Many data centers are approaching capacity due to poor facility designs, lack of space, or unsustainable power load. Others are struggling with integration as they move their data centers into adopted facilities. DCIM can often circumvent the costly endeavor of building new data centers and allow for flexibility and breathing room for a business’ growing assets. DCIM can also make the migration into an adopted data center more manageable.

Incorporating physical monitoring is crucial.

Physical monitoring is an essential part of DCIM. Introducing hardware can provide a complete picture of the health of a data center. In addition to maximizing energy efficiency, monitoring can make sure your assets are secure and safe.

Conclusion

Businesses are always looking to maximize the return on their assets and mitigate risk. Building a case to upper management should not be communicated solely in technical terms. Modernizing a data center with DCIM is actually putting money in the bank. It is an investment that pinpoints inefficiencies and maximizes business potential. Harkening back to the automobile metaphor, what if you knew how and why your infrastructure was behaving at all times? It would be like driving a car with a mechanic in the passenger seat at all time. Fortunately, implementing the appropriate monitoring tools is a one-time investment with an ongoing return. DCIM has not only immediate tangible short-term return, it extends the life of a data center and protects a business’ assets. It is clear why more and more businesses are becoming mainstream and implementing DCIM.

To learn more about Uptime Devices’ monitoring solutions, visit uptimedevices.com, or email: sales@uptimedevices.com
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The data center environment is growing, and it has become even more important to properly manage server logs. Keeping an eye on servers, firewalls, appliances and even switching infrastructure event logs can help IT administrators do much more than just check for reactive issues – when log management is kept accurate, engineers are actually creating a proactive environment capable of spotting and controlling problems before they even come up. Let’s review some tips to help you make the most of server log data.

With effective log management, administrators are able to accomplish the following tasks:

•Create an audit trail for forensics analysis. There are times when an intrusion is suspected or a data loss event has occurred. A good audit trail allows forensic data center engineers to retrace the steps taken by anyone who has entered the environment recently, and then correlate that data into usable information.

•Manage and monitor intrusion. Active server log monitoring can help prevent both accidental and malicious intrusion into the system. When logs are setup properly, all vital systems are monitored and an immediate red flag can be raised if unauthorized activities occur.

•Incident containment. If an unauthorized event occurs within a data center, properly setup logs can alert engineers to the event quickly. With good log management, engineers can immediately see where the problem occurred and isolate that network or server segment so that further damage is not done.

•Proactively protect their environment. Baseline analysis and log management tools can help an organization be proactive in its security methodology. By catching holes in security or problems with existing systems, engineers can resolve issues before a serious problem occurs. This can mean the difference between simply patching a server port or having to deal with data loss if logs are not monitored or configured properly.

•Real-time alert configurations. Data centers act as the core business IT operations center. Log management is important, however, equally important is the ability to access and monitor real-time alerts. With a good alerting design, administrators can know what is happening to their environment and resolve issues without having to waste time. If an intrusion or a critical event has occurred, every second is valuable.

•Manage active network logs and create a usage baseline. Logs can also help an environment plan for the future. For example, network logs can be used to create a baseline for the existing environment. From there, engineers can see where they are lacking and how they can efficiently plan for growth.

•Create living log workbooks capable of change as IT demands evolve. Keeping an active log book that tracks all logs across an environment can help all aspects of a data center. By understanding what various systems are doing, where they are under/over performing, and how they are being utilized allows engineers to shape their infrastructure as business demands change. A live log workbook allows future data center engineers to see and learn how their environment is behaving.

It’s important to understand that every environment is unique and will have different requirements when it comes to server log management. Government regulations may require some data centers to keep their logs for a certain period of time. Other requirements may include producing an audit trail for compliance standards such as SOX or HIPAA – this is an increasingly vital process for many enterprises across multiple industries – and there can be serious liabilities in an ineffective log management process, both tangible and intangible. This can include loss of data, security breaches, or increased risk of data and environment compromise.

Enterprises that analyze their log data efficiently can easily recognize the positive value and impact on their IT and overall operations. Properly correlated log data can show data center engineers how well their environment is performing in conjunction with other systems in their infrastructure. For example, log data can show how a network switch can be better optimized for access to a storage area network. Information that is continuously gathered by log analysis and reporting tools can also help enterprises determine their existing security environment as well as cut down on costs on extensive regulatory audits and recovery measures. By keeping your log environment healthy and up to date, engineers receive needed insight into the health and accessibility of networks, systems and applications.

Although best practices should be developed by each individual organization based on its particular environment, there are some general best practices which can be universally applied.

Use third-party tools wisely. Too often an engineering team will purchase a server log management tool that they will never use properly. For example, prior to making a purchase, an inventory should be done of the existing infrastructure. From there, engineers should see if the proposed log management tools are able to handle log collection activities for those specific devices. Make sure to understand what the logging demands of your organization are – and what you want to get out of it – before spending potentially thousands of dollars on a log management tool. Another example is security – if security is a primary control objective, look for vendors who can provide proactive alerting with their software. Ineffective tools can create a log environment that makes it difficult (if not impossible) to find the data you need.

Check logs routinely. Many organizations look at logs as a reactive means of finding information or troubleshooting, instead of using that data to spot trends. But proactively checking and analyzing log data takes a concerted and disciplined effort.

Large environments must make log management a daily task to keep up with the many logs available. By checking logs daily, we are able to stay on top of our environment and look for issues before they arise. Also, by monitoring logs regularly, we are able to learn more about our environment and how it functions in conjunction with other systems. Even if compliance is not a major concern, checking logs on a set routine can save a lot of time and money should an incident occur. For example, active security alerts should be setup covering all access into an environment. If an organization properly sets up its rules, it will know if an intrusion has occurred before any damage can be done. By proactively catching security issues, companies can save thousands, even millions, of dollars with the prevention of data loss.

Create monitoring and alerting systems. Many server log management tools will have this feature built in. However, many environments set their alerting system up to only focus on compliance-based issues, ignoring other potentially important logs. When managing logs, it’s important to set up alerts for security and system monitoring that falls outside of the area of compliance as well. This way, administrators are able to see the bigger picture in the overall health of the environment. For example, core data center networking devices all have logs that can be collected, monitored and then used. By effectively utilizing these logs, administrators can quickly see port misconfigurations, security holes and how to most efficiently utilize their switches. Even more important is the fact that with good alerting, proactive actions can be taken within an environment to help keep the data center functioning and healthy.

Use an internal log management policy. With log management, regular server log analysis becomes a key day-to-day procedure. Administrators need to develop a policy that requires regular log reporting. Once these reports are gathered, they must be analyzed for consistency and for any gap in procedure. Many times an aggregate log report can show where a security feature is failing or if a system component is not properly working. For example, large enterprises will have distributed data centers with a variety of devices. A good log management policy will look at all end-point infrastructure components and relay that information back to a centralized log management tool. Engineers are then able to look at load balancers, security gateways, and other data center appliances to see any discrepancies or faults between locations. Also, with a good policy, we are able to gather reports of a long period of time. By looking at logs over a set span we can correlate very important security and system data. This helps with further intrusion prevention as well as system health management.

Test your log management. Penetration testing or internal compliance testing will help determine if your logs are gathering the right information. Even more important, through testing we are able to establish if we are collecting and alerting against the right events. It’s an opportunity to review and refine the process. Regular testing can help an organization hone its log management environment and make it even more effective. When testing is taking place, engineers not only look at the logs from a test perspective, they are also able to see if there are any unauthorized system applications running or if there was a breach that may have been missed.

Lock down your logs. Server log management should be conducted by an authorized team. Only a limited number of authorized people should be responsible for log management and logging activities. Giving access to numerous people can potentially lead to an accidental (or malicious) deletion or modification of the existing log environment which undermines the integrity of compliance or regulatory logging requirements.

Effective logging will help protect an environment

When working with log management, it’s vital to understand the process that logs play inside of a data center. Firewall, server and application logs can all work together to create a much more secure environment. Remember, by proactively scanning logs and setting up logging alerts, administrators can quickly catch security faults inside of their own environment. With this type of proactive logging activity, data center engineers are able to secure their environment from potential breaches. Even more important is the security of the corporate data. Log management plays a big role in data loss prevention. A single security breach can cost a company dearly both from a dollars and reputation perspective.

By having an effective log management policy, administrators are able to create a healthy, well-monitored environment capable of proactive data center security.

Bill Kleyman, MBA, MISM, is an avid technologist with experience in network infrastructure management. His engineering work includes large virtualization deployments as well as business network design and implementation. Currently, he is the Virtualization Architect at MTM Technologies Inc. He previously worked as Director of Technology at World Wide Fittings Inc.

Stephen J. Bigelow, Senior Technology Editor, DataCenter News

It’s just not enough to install new servers, set them up, install applications and then walk away. Servers need regular performance monitoring to ensure that your hardware investment will deliver the service you expect – and provide ample early warning of impending trouble, such as resource shortages or hardware issues. Performance monitoring tools can provide a wealth of useful information, but only when those tools are set up and running properly. Fortunately, a few important insights will help any administrator get the best results from performance monitoring.

Achieving accuracy in performance monitoring
Monitoring is useless if it delivers erroneous information, so ensuring accurate data should be one of your first considerations. There are several aspects to accuracy, including interoperability, sampling window, tool architecture, virtualization awareness and calibration.

Interoperability. For this discussion, interoperability is basically the ability of a performance monitoring tool to access and read data points from the various pieces of hardware within your data center environment. Homogeneous environments focused on a single vendor’s product line can take advantage of performance monitoring tools that use hooks deliberately integrated into the hardware. These hooks can deliver detailed information to the tool.

The situation can be far more challenging for heterogeneous environments, where tools and hardware don’t mesh. A vendor’s tool may look for data that certain pieces of hardware simply cannot provide with the required level of consistency (if at all). It’s a similar problem for third-party performance monitoring tools that often cannot detect every sensor or hardware nuance on every possible device, and instead rely more on operating system-level data, which usually lacks granularity. In either case, the result is missing data or inaccurate data points that reduce the insight gained from performance monitoring.

This unavoidable correlation between tools and hardware requires comprehensive testing. For example, run the tools before you buy them, and verify compatibility with a long-term proof-of-principle project that will take the tool from a lab setting into a production environment. But the problem also extends beyond the initial purchase to future upgrades and technology refresh cycles. When you change hardware or update the tools, you’ll need to test interoperability to ensure the continued integrity of your performance monitoring system.

Sampling. Accuracy will also depend on the sampling window used to gather data. This is particularly important when workloads or operating parameters can change radically over time. Ideally, performance monitoring should capture the entire “operational cycle” of the machine. The trick is to determine what that “operational cycle” should be. It will depend on the way that each workload and host machine is used. For example, watching the memory performance of a server may require a fast sampling rate with a window that spans just a few minutes. Conversely, watching the CPU utilization of a corporate HR system may require monitoring at a lower rate, but over a 30 day period or longer. There is no single answer, and various system attributes may be monitored at several different rates and windows.

“If you’re testing how well a server environment will work during a usage spike, the administrator should set their schedule that will look at regular operations, then the performance spike, and finally the return to normal operations,” said Bill Kleyman, virtualization architect at MTM Technologies Inc. “Setting the schedule too far back will capture useless data, and setting scheduling too short will miss some of the important data-at-rest statistics prior to the performance peak.”

Tool architecture. Performance monitoring tools rarely operate without the use of agents or drivers installed on each host system (or even each virtual machine). Agents are mixed blessings. They are useful because agents can collect and deliver far more granular information than “agentless” monitoring tools. However, agents are also software “clients” reporting back to a central server that collects and processes the data. So each agent also requires a certain amount of computing resources that can potentially impact the performance of the related workload.

“All the computers in my environment have two agents,” said Chris Steffen, principal technical architect at Kroll Factual Data. “An application agent monitors the health of our applications, and we have System Center [Virtual Machine Manager] agents on all virtual machine hosts.”

The negative impact of agents is generally lower now than in years past, but their influence should still be evaluated, especially on mission-critical or performance-dependent workloads. In addition, Steffen also notes that emerging tools may provide features that can automate the installation, reinstallation and maintenance of agents within the environment.

Virtualization awareness. Virtualization software works by abstracting the application workloads from the underlying hardware. When traditional performance monitoring tools attempt to report within a virtual environment, the abstraction layer often causes erroneous results because the older tool may attempt to monitor hardware directly rather than through the hypervisor, which controls computing resources. Considering the popularity and importance of virtualization technology, administrators should certainly select performance monitoring tools that are virtualization aware. This allows performance monitoring to take place in both physical and virtual targets, and administrators can gather accurate information about the system’s resource utilization and behavior.

“Administrators will sometimes gather metrics of the VMs and the physical host that they are running on,” Kleyman said. “This way, performance can be monitored at the virtual and physical level to ensure the best workload performance and a solid end-user experience.”

Sensor calibration. Don’t overlook the importance of the sensors themselves. Digital data produced from the network switch or server may be quite reliable over time. But some sensors, such as temperature, humidity, air flow or other environmental sensors with an analog element, may also require regular calibration and periodic battery replacement to ensure reliable long-term operation.

Making the most of performance monitoring tools
Tools have little value if they are not employed productively. In far too many cases, performance monitoring tools are deployed, but there is no clear plan on how to use the vast amount of detailed data that the tool produces. The tool winds up being marginalized as administrators only use it for spot checks or occasional troubleshooting; it’s a wasted investment.

Experts suggest boosting the value of your performance monitoring tool by understanding the business implications – why it’s needed and how its data will be used – long before the tool is actually deployed. Also, take full advantage of the tool’s analytical features to help evaluate and report on collected data. It may take time to configure the tool’s reporting features for your specific environment, but the insights gained from proper analytics are worthwhile.

Performance monitoring reports can also provide a factual foundation for capacity planning or help make a case for technology refresh projects. “Performance metrics can help show ROI [return on investment],” Kleyman said. “By knowing what older systems did and how well new ones are performing, we are able to put a dollar figure on our environment and garner more funding for further improvements.”

But Steffen also suggests caution, urging a “trust by verify” attitude to performance monitoring tools, noting that some server tools have proven to be quite accurate when compared against similar tools, but recalls that some network tools produced inconsistent responses. Good business decisions require good data, and tools with inconsistent or unverifiable results make it difficult to formulate critical business decisions confidently.

The first decade of the 21st century was one of rapid growth and change for data centers. For most of the decade, data center managers were forced to react to rapid, continuous changes dictated by the capacity and availability requirements of their organizations, and the density of the equipment being deployed to meet those requirements.

Now, data centers must enter a new stage of maturity marked by a more proactive approach to management to enable increased efficiency, better planning and higher levels of service. Achieving actionable visibility into data center operations requires the ability to collect, consolidate and analyze data across the data center, using advanced devices, sensors and management software.

The ten steps outlined in this paper provide a systematic approach to building the foundation for data center infrastructure management by deploying and leveraging measurement, intelligent controls and centralized monitoring and management. Data centers employing these 10 prescribed point solutions for infrastructure performance monitoring stand to gain an operational, strategic and transformative advantage for their enterprise or business.

1. Sensing temperatures
2. Monitoring power
3. Monitoring rack conditions
4. Detecting fluid leaks
5. Intelligent control of precision cooling
6. Intelligent control of critical power
7. Managing alerts and alarms
8. Monitoring energy efficiency
9. Monitoring batteries
10. Monitoring and managing remotely

Through these 10 steps, data center managers can automatically collect data from infrastructure systems and sensors placed strategically within the physical space and use this data to gain higher availability, increase efficiency, enhance the value of virtualization and consolidation efforts and improve planning.

Introduction

During the first decade of the 21st century, the data center emerged as a significant corporate asset, playing a vital role in business management and customer service. Throughout this period, the data center underwent an evolution as computing and data storage capacities increased significantly. Consider these trends:

Global server shipments grew from 7.5 million annually in 2005 to 9 million in
2008, according to Gartner (Figure 1)

Average rack density grew from 6 kW in
2006 to 7.4 kW in 2009, according to the
Data Center Users’ Group (Figure 2)

Data center power density increased an average of 15 percent annually between
2000 and 2009 according to IDC

Chips in blade servers are now generating
100 watts per square centimeter and growing

Data centers have traditionally been designed with extra headroom to accommodate growth, but during the last decade demand escalated so quickly that added IT capacity consumed available headroom and outpaced supply in terms of floor space and power and cooling capacity. This created conflicts as facility personnel struggled to supply IT’s demand for server capacity.

These problems were further exacerbated by two trends that emerged in the second half of the decade. The first is the increased focus on data center energy consumption. With both the density and quantity of servers rising, data center energy consumption became a significant factor in terms of IT cost management and, in some companies, response to concerns about global warming. Early efforts to reduce data center energy consumption focused on reducing costs around data center cooling, which accounts for approximately 35 percent of data center energy consumption. Subsequent efforts took a more holistic approach that recognized the interdependency of data center systems and shifted the focus to the IT systems that create the need for cooling.

The second trend was the adoption of virtualization technologies. In its annual survey of data center managers, the Data Center Users’ Group saw virtualization adoption rates of 81 percent in 2009. This has created a dynamically changing application environment layered on an essentially static physical environment, increasing data center complexity and introducing new challenges to physical infrastructure management.

In most organizations, data center managers lacked the tools to effectively address these challenges. The network management systems essential to IT personnel in monitoring and managing IT equipment did not address the critical issues of energy consumption, available rack capacity or ambient air temperatures that are essential to proactive data center management. Further, the building management systems used by facility personnel to monitor power and cooling in the data center failed to provide the alarm management capabilities required for critical systems and to account for the interdependencies between systems.

Evolving from a reactive to a proactive approach to infrastructure monitoring requires a new type of management system that provides visibility into the data center physical infrastructure within both the IT and facility domains and across these two domains.

The Emergence of Data Center Infrastructure Management

Data Center Infrastructure Management (DCIM) is a superset of infrastructure monitoring and encompasses the ability to manage the data center physical infrastructure to optimize data center resource utilization, efficiency and availability.
DCIM includes management of the data center infrastructure layer (power, cooling and the physical space), the IT infrastructure layer, (compute, storage and communications equipment) and the gap between the two layers.

By enabling management across the gap, data center operators have visibility into the true capacity of their IT and infrastructure systems, allowing them to manage closer to actual capacity, rather than the conservative estimates that leave some percentage of capacity unused as a buffer. Emerson Network Power has identified four successive stages of DCIM progression:

1. Monitor and Access, which provides the ability to quickly react to potential problems in the data center infrastructure and improve management. With monitoring and access, data center personnel have visibility into equipment operating status and receive real-time alerts and alarms to notify them of potential equipment operating problems. Remote access can also speed the response to equipment problems while real-time monitoring data can be used
to populate planning tools with actual performance data.

2. Data Capture and Planning, in which data center personnel have the ability to automatically collect data about what assets are in the data center and where they are located, as well as how they are interconnected. This data can be used to address key planning issues including, is there enough space, power and cooling to meet future needs and how can equipment be commissioned and decommissioned more efficiently.

3. Analyze and Diagnose, which provides data center personnel with the ability to respond more quickly to changes in the infrastructure and manage more efficiently. Operating data available through monitoring and data capture initiatives can be used to extend the life of the data center, reduce mean-time-to-repair, synchronize infrastructure with virtualization automation and analyze performance against SLAs.

4. Recommend and Automate. The final stage of progression enables data center optimization by providing data center personnel with the visibility and control to optimize performance while maintaining or improving availability. With this level of progression, data center management becomes truly proactive as personnel can anticipate potential failures and automatically shift compute and physical resources to eliminate downtime while increasing resource utilization to optimize efficiency across the data center. Creating a comprehensive approach to data center infrastructure monitoring not only addresses the first phase of DCIM maturity but enables future phases. The remainder of this paper outlines 10 steps data center managers can take to create an infrastructure monitoring system that will deliver value today and create the foundation for holistic Data Center Infrastructure Management.

The 10 Steps to Effective Infrastructure Monitoring

Although sophisticated data center management tools have emerged in recent years, many facilities still lack the ability
to comprehensively monitor their physical infrastructure systems. This is partly due to the disparate systems that make up the data center infrastructure, partly the result of the rapid changes transpiring in the data center, and partly the lack of a clear and simple roadmap for bringing together these disparate systems into a common network. This paper attempts to address this last challenge by outlining a simple and logical 10-step process for moving toward comprehensive data center infrastructure monitoring.

Measurement
If you can’t measure it, you can’t control it. That’s why the first four steps in this 10- step approach prescribe the deployment of sensors that can collect critical power, cooling and safety data across the data center.

1. Sensing temperatures
One of the most significant consequences of the growth in data center density and complexity is the issue of heat density. As data center density has increased, cooling loads have grown and become more heterogeneous. It is no longer possible to manage temperatures on a facility level because rack densities may vary widely, creating hot spots in one zone while another zone is cooled below the desired temperature.

Installing a network of temperature sensors across the data center helps ensure that all equipment is operating within the ASHRAE recommended temperature range (64.4° F to 80.6° F). By sensing temperatures at multiple locations the airflow and cooling capacity of the precision cooling units can be more precisely controlled, resulting in more efficient operation.

Additionally, the network of sensors can reduce cooling costs by allowing safe operation closer to the upper end of the temperature range—operating, for example, at 75° F instead of 65° F. According to an ASHRAE paper developed by Emerson Network Power, a 10° F increase in server inlet temperatures results in a 30 percent reduction in compressor power draw. Assuming the Computer Room Air Conditioning (CRAC) units supporting the facility are equipped with digital or unloading compressors, this reduction in compressor power draw translates into a 21 percent reduction in cooling energy costs.

The data center cooling system typically measures return air temperatures and, in some cases, supply air temperatures. These measurements should be supplemented with sensors that measure server inlet temperature to enable more precise control of the air temperature at the server. With more cooling systems migrating to the row and rack, these sensors may be connected directly to a particular cooling unit, as is the case with the Liebert CRV row-based system, which can support a mini-network of sensors that measure server inlet temperature for adjacent racks and adjust cooling accordingly.

The best practice is to attach at least one sensor on every rack, and it is also acceptable to place a sensor on every other rack when racks are arranged in the hot aisle/cold aisle configuration, and there is uniform loading across the row. Sensors should be located near the top of the rack where temperatures are generally highest.

It is also advantageous to locate sensors near the end of the row where they can detect any hot air entering the cold aisle from the hot aisle.

There are advantages to connecting the temperature sensors directly to the cooling system, as with the Liebert CRV, as well as to a central monitoring system. When the sensors and cooling system are working in concert, the cooling system can automatically adapt its operation to eliminate hot spots, respond to heat load changes, detect obstructions and coordinate its operation with other cooling units working in the same zone.

ASHRAE provides more detailed guidelines for sensor location in the paper Thermal Guidelines for Data Processing Environments.

2. Monitoring power usage
With power densities and energy costs both rising, the ability to monitor energy consumption is essential for effective data center management. Where one measures power can have an effect on how efficiency is measured. See the discussion of PUE monitoring in Step 8 for more information on efficiency monitoring.

To gain a comprehensive picture of data center power consumption, power should be monitored at the Uninterrumpible Power Supply (UPS), the room Power Distribution Unit (PDU) and within the rack. Measurements taken at the UPS provide a base measure of data center energy consumption that can be used to calculate Power Usage Effectiveness (PUE) and identify energy consumption trends. Monitoring the room PDU prevents overload conditions at the PDU and helps ensure power is distributed evenly across the facility. The best view of IT power consumption comes from the power distribution units inside racks. Rack PDUs now feature integrated monitoring and control capabilities to enable continuous power monitoring. Because rack power consumption varies based on the specific equipment within the rack and its load, each rack should be equipped with a PDU— two for dual bus environments—capable of monitoring power consumption to the rack PDU, as well as overload-protected receptacle groups and, where required, at the receptacle level.

These systems can provide PDU, branch- level and receptacle-level monitoring of volts, kilowatts (kW), amps and kW per hour. This provides the most direct measure of power consumption available to data center management and supports both higher data center efficiency and availability. In addition to more effective power management, rack PDUs are used to support more accurate chargeback of IT services and identify stranded capacity.

Some models also enable individual receptacles to be turned on and off remotely to prevent the addition of new devices that could create an overload condition.

3. Monitoring rack conditions
With increasing densities, a single rack can now support the same computing capacity that used to require an entire room. Visibility into conditions in the rack can help prevent many of the most common threats to rack- based equipment, including accidental or malicious tampering, and the presence of water, smoke and excess humidity or temperature.

A rack monitoring unit can be configured to trigger alarms when rack doors are opened (and can even capture video of the event), when water or smoke is detected, or when temperature or humidity thresholds are exceeded. These “eyes inside the rack” can be connected to a central monitoring system where environmental data can be integrated with power data from the rack PDUs, while also providing local notification by activating a beacon light or other alarm if problems are detected. They should always be deployed in high-density racks and racks containing business-critical equipment.

4. Detecting fluid leaks
A single water leak can cost thousands of dollars in equipment damage—and lose many times more in lost data, customer transactions and enterprise productivity. Leak detection systems use strategically located sensors to detect leaks across the data center and trigger alarms to prevent damage. Sensors should be positioned at every point fluids are present in the data center, including around water and glycol piping, humidifier supply and drain lines, condensate drains and unit drip pans.

A leak detection system can be operated as a standalone system or connect into the central monitoring system to simplify alarm management. Either way, it is an important part of the sensor network that gives data center managers visibility into operating conditions.

Control

Current generation infrastructure systems are equipped with sophisticated controls that enhance reliability and enable
multiple units to work together to improve performance and increase efficiency.

5. Intelligent control of precision cooling Intelligent controls integrated into room and row air conditioners allow these systems to maintain precise temperature and humidity control as efficiently as possible. They coordinate the operation of multiple cooling units to allow the units to complement rather than compete with each other, as sometimes occurs when intelligent controls are not present.

For example, one unit may get a low humidity reading that could trigger
the precision cooling system’s internal humidifier. But before turning on the humidifier, the unit checks the humidity readings of other units and discovers that humidity across the room is at the high end of the acceptable range. Instead of turning on the humidifier, the system continues to monitor humidity to see if levels balance out across the room.

In one large data center’s carefully monitored retrofit application, adding intelligent controls to 32 Liebert Deluxe precision cooling units with integrated Liebert iCOM controls reduced energy consumption by 200 kW per hour, and generated a return on investment of 1.2 years.

Integrated control systems on room- and rack-based cooling systems can also be used to enable preventive maintenance programs and speed response to system problems. Data collected by these systems enables predictive analysis of components and proactive management of system maintenance. Event logs, service history logs and spare parts lists all support more
efficient service.

6. Intelligent control of critical power
UPS systems now include digital controls with the intelligence to alter and optimize the performance of the UPS. They automatically calibrate the system and ensure the UPS is working properly. In addition, they ensure that the UPS switches between traditional operation and bypass during overloads, protecting the UPS system and the overall power infrastructure. This minimizes the need to make manual adjustments based on site conditions. Instead of requiring a service technician to manually adjust the analog controls, the UPS system itself monitors the conditions at the site (power factor, load and ambient temperature) and makes adjustments to maintain optimum performance.

These controls also enable more efficient operation through energy optimization and intelligent paralleling features. Energy optimization mode increases UPS efficiency by powering the IT load from the bypass path while providing some power conditioning. An organization may choose to activate energy optimization during periods when utility power quality is thought to be particularly good or when availability requirements are not as high, such as nights or weekends. Energy optimization mode can improve UPS efficiency by as much as five percentage points, but also introduces the possibility of compromising total power protection. This risk can be mitigated when the controls are designed to keep the UPS inverter “hot” while the system is in energy optimization mode, allowing faster response to utility power disturbances.

Intelligent paralleling provides another option for improving UPS efficiency in multi- module systems. Intelligent paralleling manages the load across multiple UPS modules and can automatically deactivate
modules that are not required to support the load, while still ensuring that the system is providing adequate redundancy. For example, a four-module N + 1 system sized to support 700 kVA using four 250 kVA UPS modules can support loads below 400 kVA with only three modules. This capability can improve system efficiency by up to six percent without sacrificing protection.

Centralized Monitoring and Management
Current generation power and cooling systems feature sophisticated displays that provide a wealth of operating data. The Liebert CRV cooling system, for example, can show trending of server inlet temperatures for multiple racks. But in
the dynamic, every-second-counts world of the data center, local management
of infrastructure systems is typically inadequate to meet high efficiency and availability requirements. That has spurred the use of centralized monitoring systems.

Centralized monitoring systems are available today that operate across the existing IT network or across a dedicated network.
Sites smaller than 2,500 square feetgenerally choose to use the existing network rather than set up a separate network,
while larger facilities will benefit from a dedicated network that provides the ability to integrate with building automation and management systems and manage multiple facilities.

7. Managing alerts and alarms Minimizing system downtime has been the traditional justification for data center
infrastructure monitoring and it continues to be a powerful benefit. The ability to view immediate notification of a failure—or an event that could ultimately lead to a failure— through a centralized system allows for a faster, more effective response to system problems.

Equally important, a centralized alarm management system provides a single window into data center operations and
can prioritize alarms by criticality, to ensure the most serious incidents receive priority attention. Every alarm needs to be gauged for its impact on operations. For example, it may be acceptable to defer a repair of one precision cooling unit if 30 are working normally, but not if it is one of only two units.

Taken a step further, data from the monitoring system can be used to analyze equipment operating trends and develop more effective preventive maintenance programs.

Finally, the visibility into data center infrastructure provided by a centralized system can help prevent problems created by changing operating conditions. For example, the ability to turn off receptacles in a rack that is maxed out on power, but may still have physical space, can prevent
a circuit overload. Alternately, alarms that indicate a rise in server inlet temperatures could dictate the need for an additional row cooling unit before overheating brings down the servers the business depends on.

8. Monitoring energy efficiency
Energy costs consume a large proportion of data center operating costs, but many facilities lack energy monitoring capabilities.

Automating collection and analysis of data from the UPS and PDU monitoring systems can help reduce energy consumption while increasing IT productivity. Energy efficiency monitoring can track total data center consumption, automatically calculate
and analyze PUE and optimize the use of alternative energy sources.

Using data from the UPS, the monitoring system can track UPS power output, determine when UPS units are running at peak efficiency, and report Level 1 (basic) PUE. Monitoring at the room or row PDU provides the ability to more efficiently load power supplies, dynamically manage cooling and automatically calculate Level 2 (intermediate) PUE. Panel board monitoring provides visibility into power consumption by non-IT systems, including lighting and generators, to ensure efficient use of those systems. Finally, rack-level monitoring provides the most accurate picture of IT equipment power consumption and can support Level 3 (advanced) PUE reporting. The ability to automate data collection, consolidation and analysis related to efficiency is essential to data center optimization and frees up data center staff to focus on strategic IT issues.

In a study of organizations with service contracts for maintenance and remote analysis with alarm monitoring, ensuring regular preventive maintenance is performed, the Liebert Services business of Emerson Network Power found that customers using battery monitoring experienced half as many battery failures as customers that didn’t.

The potential for battery monitoring to reduce failures is even greater than that—customers who relied on Liebert Services Ntegrated Monitoring did not experience a single battery failure.

9. Monitoring batteries

To prevent data loss and increase uptime, most data centers require a dedicated battery monitoring system. According to Emerson Network Power’s Liebert Services business, battery failure is the leading cause of UPS system loss of power. Utilizing a predictive monitoring battery monitoring method can provide early notification of potential battery failure. The best practice is to implement a monitoring system that connects to and tracks the health of each battery within a string. The most effective battery monitoring systems continuously track all battery parameters, including internal resistance, using a DC test current to ensure measurement accuracy and repeatability.
Supported by a well-defined process for preventive maintenance, and

10. Monitoring and managing remotely Data center remote monitoring can lift the burden of infrastructure monitoring from internal personnel and place it with an organization with resources devoted to this task, as well as deep infrastructure
expertise. In addition to improved resource utilization, a dedicated monitoring organization can respond more quickly to portfolio issues.

For instance, in monitoring data across multiple facilities, they may be alerted to a problem caused by a certain manufacturer’s breaker. Very quickly, the manufacturer can be notified so as to avoid a potential problem occurring across hundreds of sites, many of which contain similar equipment.

An organization such as Liebert Services has engineers on staff that analyze data returned remotely and systematically examine that data. For example, remote monitoring tracks the inbound frequency of power provided to a UPS. If the UPS is receiving utility power, the input power frequency will be precisely 60 Hz. When the monitoring staff sees the input frequency vary within 58-61 Hz, they immediately recognize that the generator has started and is sourcing power—but potentially at the wrong time, and for the wrong reason. Finally, telemetry-based monitoring enables remote management of systems where authorized, allowing the monitoring partner to control systems remotely. This is particularly valuable
when a facility is undergoing changes and updates.

Evaluating the Benefits of Infrastructure Monitoring

The 10 steps presented in this paper deliver powerful, quantifiable benefits in the key areas of data center availability and efficiency.

By some accounts, data center cooling accounts for 35 percent of data center energy consumption. Monitoring provides multiple opportunities to improve cooling efficiency. From the more precise control of air temperatures at the server inlet, to the improved coordination between cooling systems enabled by intelligent controls, monitoring can reduce cooling energy costs or enable the existing cooling system to support higher capacities.

Power monitoring and control also delivers energy reductions. With in-rack power monitoring, managers can identify equipment that is using energy but not supporting business services, reclaiming or eliminating this stranded capacity. Controls on the
power system also create the opportunity to increase UPS system efficiency by up to six percent.

Virtually every monitoring step contributes to data center availability by providing advance warning of potential problems or faster response and recovery from actual events.

From systems that can show exactly what is happening inside a rack at any point in time, to centralized alarm management and
battery monitoring, infrastructure monitoring eliminates some of the most common causes of data center downtime. In many cases these systems are relatively simple to implement and, once installed, provide the visibility and control required for data center optimization.

Monitoring rack conditionsPrevent unsafe conditions inside the rack; respond quickly to problems
Avert organizational inefficiency created by server and application downtime

4Detecting fluid leaks
Prevent outages from water leaks
Reduce wasted energy caused by leaking equipment

5Intelligent controls cooling
Enhanced cooling system maintenance
Cut cooling costs by improving hot spot management; optimize operation of multiple units

6Intelligent controls power Enhanced ability to handle faultsGain three to five percent efficiency from energy optimization mode and one to six percent savings from intelligent paralleling

7Managing alerts and alarms
Faster response to events;
more proactive maintenance
Automate operations so personnel can focus on othe issues

8Monitoring energy efficiency
Optimize efficiency based on measurements of operating conditions

9Monitoring batteries
Reduce battery failures by half
Reduce operational downtime so enterprise stays productive

10Monitoring remotely
Enhanced data analysis and specialization reduces downtime; elminate battery-related downtime
Create efficient use of human resources allowing personnel to attend to strategic issues

The steps outlined in this paper represent proven strategies for improving data center efficiency and availability and create the foundation for holistic data center infrastructure management.

Conclusion

The next stage in data center management progression is automating and centralizing the management of the physical infrastructure to enable more effective resource utilization without compromising availability. Following the 10 steps outlined in this paper can help enterprises create the foundation for the future of data center management, while delivering value today by improving availability, efficiency and planning.

Data center monitoring is often focused on computers; monitoring system performance, tracking virtual workloads, and reacting to the inevitable warnings and alerts that spell trouble for servers, network or storage within the architecture. But modern data centers need a more holistic monitoring strategy that embraces environmental factors like temperature and humidity – not just within the room – but at a granular level within racks and servers. Let’s cover some key monitoring points for the environment and show you how to deal with environmental monitoring problems.

Aspects of data center environmental monitoring
Many data centers employ sophisticated management tools, but many tools still don’t provide granular insight into environmental conditions; or worse, data center owners simply don’t use the environmental data those tools provide. Part of the problem is heterogeneity. It simply may not be possible to use a single tool that can monitor voltages, fan speeds, temperatures, humidity levels, and other environmental factors across every possible system. In other cases, the availability and placement of necessary environmental sensors may be inadequate for proper monitoring. Yet another part of the problem is a lack of planning and coordination – IT administrators don’t worry about the data center environment as much as they should.

When you’re ready to extend data center monitoring to the environment, take time to consider the following monitoring points:

Sensing and monitoring temperature. One of the most significant results of data center growth is the issue of heat density. It has become much more difficult to manage temperatures on a facility level because rack densities (and corresponding rack heat) may vary widely. As a result, we see hot spots in one zone and cooler spots in another zone. Installing temperature sensors with network connectivity within the data center helps IT administrators look for those hot and cold spots to ensure that all equipment is operating safely. If not, early alerting can allow administrators to boost cooling, shift workloads, or take other pre-emptive action to avert failures.

A good metric to follow is the older ASHRAE recommended temperature range (64.4 to 80.6 degrees Fahrenheit) or the newer ASHRAE standard outlined in TC 9.9. Data center best practices recommend at least one sensor on every rack. If an environment has a hot-aisle/cold-aisle configuration, it becomes acceptable to place a sensor on every “hot” rack or row. Since heat also rises, it is recommended to place sensors near the top of the rack where temperatures are generally highest. Another recommendation is to place sensors near the end of the row where they are able to detect any spillover; hot air entering the cold aisle from the hot aisle.

• Establish precision cooling control. With large enterprise data centers, maintaining consistent levels of cooling and room/row air conditions is essential. Deploying intelligent controls, which are sometimes integrated into cooling and monitoring systems, helps data centers run as efficiently as possible. The goal of intelligent control is to allow multiple large systems to compliment, rather than compete with one another. Let’s take humidity control at a large data center as an example. Let’s assume that for some reason, one unit begins to report a high humidity reading from one of its sensors. Without an intelligent system, that unit’s remediation process may start. However, with an intelligent cooling system in place, the data center monitoring tools will first query the humidity status of all the other units in the facility. If it finds that the other units are operating within range, it will continue to monitor the situation to see if the levels even out. Otherwise, it will send an alert to an administrator or begin a pre-designed remediation process.
• Fluid and humidity detection. One chiller leak inside a data center can cost thousands, if not millions, of dollars in damage to a data center and critical business hardware. This type of damage will deal a serious blow to enterprise functionality and productivity. Use leak detection sensors strategically located within the data center to detect leaks, trigger alarms, and help prevent water damage. It’s highly recommended that leak sensors be installed at every location where fluids are present in the data center. Depending on the data center environment, leak sensors are able to operate as a standalone system or can be connected into the central monitoring system to simplify management. In large environments where cooling areas are numerous, leak and fluid sensors can also monitor for areas of condensation and excess humidity. Having humidity sensors as a part of the internal and external rack sensor array will maintain regular levels of humidity control. Drip pans and designated areas for liquid run-off will help curb the risk of a major leak.Humidity detection can also help detect excessively dry conditions that might precipitate electrostatic discharge (ESD) problems. Dry air is common when free air-side cooling technologies are adopted for the data center.
• Integrate the environment with other sensors. Temperature and humidity/liquid sensors are just the beginning of intelligent data center environment monitoring. Smoke/fire alarms are needed at several locations throughout the facility to detect impending fire. While these alarms are usually tied to the building’s fire suppression system, they can also be integrated into the data center monitoring system to provide administrators with an opportunity for early action before more dramatic gas suppression is released.Monitor power from each power distribution system (PDS) and integrate that data as well. Power monitoring can support a continuous evaluation of the data center’s Power Usage Effectiveness (PUE) and report power faults for early intervention by the IT staff. Some data centers also monitor and integrate data from intelligent uninterruptable power supply (UPS) systems as well, and can track UPS battery and alarm conditions.

  Room and rack access (security) sensors report on unauthorized access, alerting the IT administrators – and could even summon security assistance if necessary. As a minimum, such simple physical sensors can at least log door openings and closings to help narrow down the personnel present at the time.

• Managing alarms and notifications. Uptime and data center efficiency have been the main justifications for implementing some sort of environmental monitoring controls. This continues to be a main driver, since the ability to view immediate notifications of a failure or proactively monitor a situation to prevent a failure are critical data center tasks. A centralized and well-managed system allows administrators to respond quickly to emergencies and help retain a higher uptime. Creating a central alarm system is also very important for data center uptime and health. A good alarm system is able to prioritize issues by criticality, to ensure the most serious incidents receive priority attention. When setting up an alarm-based system, it is important to evaluate and designate every alarm for its impact on business and IT operations.
• Remote data center monitoring. Large environments often must leverage outside expertise when it comes to data center monitoring. Remote monitoring capabilities can help organizations keep an eye on their secondary or backup environments, or outsource the monitoring and management to a service provider. The ability to see the health of remote facilities can help IT administrators respond to emergencies faster and bring their environments back to a healthy state. By having external visibility into multiple sites, managers can keep track of alerts, alarms and general data center environmental statistics all in one central place.

Data center monitoring best practices
It’s important to remember that a data center monitoring infrastructure will require periodic maintenance and testing – just like any other part of the facility. In addition, the monitoring must change or scale to accommodate the data center’s evolution. Don’t ignore the sensors or allow their placement to remain static as other systems and racks move. Here are some other tips for data center environmental monitoring:

Testing and Maintenance. All sensors within a data center should undergo regular testing and maintenance. Faulty or erratic sensors should immediately be replaced. One way to identify a faulty sensor is to review readings from similar nearby sensors. For example, when several sensors within a rack report one temperature, but another sensor reports a surprising alarm, it should warrant immediate investigation, but should be approached with a modicum of skepticism until the root of the alarm can be identified and confirmed.

• Be ready for emergencies. Sensors do not prevent emergencies, so common-sense emergency planning should still be part of every data center manager’s agenda. A disaster recovery plan must include immediate personnel notification; know who your data center maintenance team is, and how to reach them quickly. When a cooling failure occurs, your first call will be to your data center HVAC engineers. Be detailed in the description of the problem, too. If your engineers need to bring spare parts, this will help them. When it comes to data center environmental emergencies, every second counts.
• Have a backup plan ready. Monitoring systems have the ability to set off different alarm levels. If your data center is in a hosted environment, it is very important to specify and understand emergencies in your service-level agreement. The hosting provider must have a contingency plan prepared in the case of a sudden disruption. In a private data center, always have sensor monitoring and alert systems operational. Cooling systems may warrant local backup units in the event of an emergency–even if this means using temporary portable cooling systems.
• Have an automated recovery plan. Some monitoring systems have integrated automation systems. In the event of an isolated rack emergency, some systems are able to shut off non-essential servers. Development servers are often big power users that don’t need to be run during production. Any test server that is not essential can be set to shut down when emergency conditions arise.
• As IT data centers continue to evolve, managers will begin to see more automated tools to help keep an environment alive longer and without disruption. Automating and centralizing the management of physical infrastructure components for effective resource usage will be the next step in data center design and implementation. They key will always revolve around strategic uptime capabilities. By proactively monitoring server room environmental variables, IT administrators are able to greatly reduce their risk of having extended downtime. This, in turn, creates a more robust and easier to manage data center.

The expenditures analyzed were:
-detection costs
-containment costs
-recovery costs
-ex-post response costs
-equipment costs
-IT productivity costs
-user productivity loss
-3rd party costs

The most costly catalyst of these incidents was IT equipment failure. The key causes of data center outages were IT demands exceeding capacity, rising rack densities, data center efficiency, and the need for infrastructure management and control. Regarding the latter, effective monitoring and control directly influenced the other key factors and the presence of intelligent management abilities could have prevented many of the problems that arose.

Download the study here: tinyurl.com/7mxtess