Mobile Devices And Applications: Challenges Of Asset Management

On 03.09.10, In Other, By Rajesh Kadam

Mobile devices are increasingly becoming a way of life for workforces. A steady stream of cool applications is making work a breeze and the productivity benefits outweigh the risk to security. Enterprise data managers see the point and are no longer obsessively wary of the data loss and management issues of integrating wireless applications, the growth of smart phones by employees expanded in 69% of North American companies in 2008. The fact remains that mobile devices and applications pose unique challenges. They are not updated as often as on-site applications and are, as a result, vulnerable to viruses.  Equally, mobile devices are more likely to be stolen or lost and valuable data could fall into the wrong hands. Mobile devices are not quite free birds and need remote technical and application support management. These concerns can be addressed by an inventory of mobile assets on the backend and data on the interdependencies between hardware and software assets.

Most security breaches happen when software is not updated regularly with patches. For in-house assets, automatic patch management is enabled when datacenters prepare an inventory of the hardware assets the status of their software updates. Upgrades to the software are downloaded as soon as they are available and an asset is known to need it. For mobile devices, the data center can keep track of updates and prompt upgrades when needed.

While on the road, sales people carry valuable information such as customer lists, network log-on information or product launch plans. Smart phones these days can store a lot with those flash devices. They could easily lose their devices while dosing at airports or while moving in and out of hotels. To safeguard against such risks, the devices and their applications could be disabled remotely. This would be possible if the data center has an asset inventory with the lost mobile device listed; the salesperson could use drag and drop commands from any computer to disable the device.

Remote technical support for mobile devices is a challenge given their diversity and that of their operating systems and applications. The datacenter would be able to help if they have ready access to an inventory of data on the configuration of each of the devices and their software, the knowledge resources for diagnosis and remedies and the technical staff skilled able to provide support.

Enterprises have so far chosen to use special systems to manage mobile devices instead of using existing data centers. The cost of doing so is prohibitive at $2,500 for each mobile phone. As the number of devices in use increases, the cumulative cost will balloon. They have to begin implementing processes in their existing datacenters to keep the cost manageable and to leverage the entire stock of assets they have to ensure efficiency and security for their mobile assets as well.

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Equipment Level Energy Efficiencies: The Missed Opportunity

On 03.01.10, In GreenIT, By Kishore

Much information is lost to broad brush energy efficiency numbers such as Power Use Efficiency (PUE). For one, the averages miss the scatter in the metrics for individual pieces of equipment. When scrutinized with a fine tooth-comb, the relationships between the type, age and source of equipment and power consumption can uncover the root causes of the variations in the actual energy consumption. By drilling down, energy costs can be lowered in more ways like ensuring application needs and equipment capability matches, parity between processor performance and power and the relationships between software and hardware, house-keeping like temperature-control and equipment consolidation and retirement.

At the micro-level, the data looks dreadful; energy actually used for data processing is a small fraction of the total and much is lost to preventable causes. Experts reckon that only 3% of the electricity is used for data crunching.

Nearly 10% of the power is lost to servers that have lived out their life and are not retired because they are little noticed. An automatically updated inventory would quickly pinpoint the redundant servers.

A great deal of power is lost to servers with very low rates of utilization—as low as 10%. Data on applications tied to each server would quickly reveal the root cause of underutilization. Consolidation and virtualization will ensure that application needs and server performance are matched.

Nearly half the power is lost to overheads such as cooling which can be cut by creating arrays of IT equipment close to the coolers. Electricity is also misallocated when more of it is accorded to a piece of equipment than its needs due to its imprecise ratings. Granular data on variations in energy consumption will quickly reveal poor floor design that could be the root cause of inefficient energy consumption. The likelihood of energy losses will only grow as more computing power is concentrated in fewer pieces of equipment such as blade servers.

The key to increasing energy efficiency in the datacenter is to augment IT asset information with business related information such as descriptive information about processors’ conversion efficiencies. The right choice of processors can help save 20% of the energy costs. Dual core processor technologies provide added performance with the same level of power. The cooling needs for the processors can also be adjusted as performance needs fluctuate with relevant management applications on the operating system.

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Data Center Virtualization and Cost Reduction

On 03.01.10, In Data Centers, GreenIT, IT Asset Management, By Rajesh Kadam

GreenIT has brought significant cost saving opportunities by way of increased productivity.  Data Centers have been quick to grab on to this . According to the Green Grid, nearly 60% virtualized their IT equipment. Another 47% consolidated and optimized their servers, 46% bought computer equipment that uses low power / low wattage processors and 40% make full use of power management tools.

Virtualization and consolidation of servers and storage devices is a no-brainer—a way to reap productivity gains without sowing investment. The House of Representatives, for example, reduced its energy consumption its data centers by 50% and lowered its installed base of servers! With the state of IT Asset Management today, it’s not uncommon for server utilization to be as low as 2% to 5%. Companies can make-do with fewer servers, increase their rate of utilization and save the energy costs that are otherwise incurred on operating the surplus servers before virtualization reduces their numbers. A growing number of options exist to lower costs—blade servers which save space and energy costs, switch to cloud computing and desktop virtualization.

For efficient utilization of energy, the devil is in the details of comparative data of consumption by each piece of equipment and the angel in the overarching view of consumption patterns. Companies need to automatically discover their many assets and all the details of their versions, brand names, parameters of power consumption, etc. They also need to categorize the data for it to be intelligible and map the relationships in the asset classes, compare their baseline consumption with the benchmarks in order to detect opportunities for cost reduction while maintaining service levels. Manual data crunching with Excel sheets is way too cumbersome and slow. Software tools for IT Asset Management are needed to automate data gathering, analysis and visualization for identifying the sources of excess costs and means to lower them.

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Automated System Management Of IT Sprawl in Mergers & Acquisitions

On 02.25.10, In IT Asset Management, By Kishore

Mergers and acquisitions are a leap of faith for companies and unsettling for data centers. Managements want the combination to have more value than the sum of the merging companies. They want to ferret out the hidden synergies and efficiencies in the IT sprawl that is typical in the data centers of large companies. The web of relationships between software and hardware are reconfigured to wring out more from fewer pieces of equipment and software licenses. Typically, managements of merged companies rethink the portfolio of services they want to support in the datacenter, enlarge their scale of operation and consolidate and virtualize to lower costs. The workloads between locations will in all probability be reallocated and reprioritized. To start, managements want the baseline numbers of the inventory of assets and their inter-dependencies before they can decide on the alterations or the additions and subtractions. They also want to map out the architecture and configuration of a data center they want in the future. Done manually, the transition is fraught with the risk of error and a manual labor of unwanted love.

SunTrust bank is a classic story of how a merger compounded the IT sprawl and became a millstone as it bogged down in the manual reconfiguration of their system. When it eventually installed a software tool to identify configuration issues, it found as many 8,000 of them. The cost of manually managing configuration changes would have been a whooping $300,000 dollars and would still not have been timely.

Automation has relieved the burden of manual housekeeping in the data centers of the large financial services companies and has saved costs. Wachovia’s merger with Wells Fargo was managed using standardized processes for changing the countless configurations in the systems of the two giants. The inter-dependencies between the technical and business services were calibrated with precision to ensure that they were all in sync. Altogether, the exercise saved the company $20 million.

Large multinational companies seek to bring order to their IT sprawl by integrating equipment acquired from numerous vendors by using a common taxonomy to describe their asset base. They want to have a global view of their assets in each of their regions where processes and configurations are determined locally. Microsoft Systems Management Server (now Systems Center Configuration Management) has been the platform of choice for managing large data centers. Managements are finding that they need alternatives to manage the diversity of their IT Asset base and identify opportunities for process improvement and optimization of their configurations to reduce costs and lower downtime. They are finding out that they need to normalize the data they extract from Microsoft SMS/SCCM so that it is readable by any system and intelligible from a business point of view.

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Cloud Computing and Datacenters

On 02.23.10, In Data Centers, IT Asset Management, By Ido Sarig

Enterprise datacenters are not any longer the one place to go for computing assets; they are the pivot of a choice of on-demand internal and external clouds or collocation facilities that an enterprise taps. If this seems too complicated, virtualization makes it simple by providing a single view of the physical resources on a screen. With drag and drop commands, the enterprise can call in on-demand computing resources when surges in traffic overwhelm the datacenter. All this sounds cool till you find out that the data on the physical assets in the virtualized environment is often incomplete or not descriptive enough of the business ownership, the life of the asset, etc.  You rummage through several spreadsheets and databases to painstakingly find the data you need. This one chink could well defeat the goal of quickly finding the resources you need when you need them. A virtual IT asset management solution automates the collation of data on the hardware and the software available in the virtualized environment.

In a perfect world, enterprises would rather wash their hands off the messy business of managing datacenters. The reality is that the treasure trove of consumer and financial information or intellectual property is something enterprises want to zealously guard within their own datacenter. They need to redirect non-critical data to the cloud when they experience traffic spikes. There are also instances when companies want services but don’t want to invest capital resources to get them. As their assets are spread out over several locations and cloud vendors, it is harder to know what is available where and in what form.

Traffic can shoot up during a market promotion, consumer buying during holiday seasons or something quirky like a victory of a sports team. Sony Entertainment was caught off-guard when demand surged for Michael Jackson’s music following his unexpected death. The surge in traffic could have been managed by letting customers browse the catalogue on a cloud service while reserving the enterprise datacenter for the purchases.

Fear of losing control of critical data like customer information to cloud service providers is well founded in facts of recent history. The Linkup, an online storage services provider, closed down after it lost access to 45% of its customer information that was stored with Nirvanix, an online storage service company which shut down.

Virtualization of data centers or the emergence of internal clouds is the foundation for their synchronization with external clouds. An effective inventory of Assets with appropriate offline market data associated with each piece of hardware and software inventory is a precondition for effectively leveraging the resources available in a virtualized network.

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Datacenter Consolidation: Management of Latent Inefficiencies

On 02.16.10, In Data Centers, GreenIT, IT Asset Management, By Rajesh Kadam

Over the past few years, datacenters bought a grab bag of servers and other IT equipment in a bunch as if from a clearance sale. But then Datacenter managers woke up to the fact that they were running up soaring bills for energy, software licensing, maintenance, duplicate applications, higher cost of space and staff to manage the assorted equipment. A garage sale of servers followed as applications were consolidated on fewer servers and data center managers grabbed the low hanging fruit of higher server utilization. Now the time for a slog has come—the gains from server consolidation and virtualization in recent quarters have diminished. Global sales of virtualization software fell 18.7 %, according to IDC data, in the second quarter of 2009. Analysts at IDC and Gartner agree that this was not due to the economic recession alone. The Gartner analyst concludes, “data center managers are still not paying sufficient attention to the process of measuring, monitoring and modeling…….”.

Currently, equipment in datacenters is largely monitored manually with excel spreadsheets which is something like highway police tracking traffic without radar. A Computerworld survey revealed that 63% of enterprises rely on excel spreadsheets to assign IP addresses. As the size of the datacenter increases, the excel plodding gets more excruciating and the single largest component of the operations cost according to IDC.

In consolidated and virtualized dataceters, the price of any outage is jolting. A single outage in Amazon was estimated to have cost $1.86 million per hour. More applications are deployed on fewer but more powerful servers which consume more electricity. If they are underutilized, the loss from malfunctioning of applications and loss of electricity is a whole lot more than with older servers.

Virtualization lowers visibility into performance of individual units of equipment as capacity is assigned randomly by unseen electronic means to whichever unit working at less than full capacity. Manual monitoring of capacity use would be like recording the movement of a submarine with binoculars. Capacity assigned by electronic means is best read automatically by software able to sense the signals on the network.

A consolidated and virtualized data center subsumes the previously siloed physical pieces of equipment and depends on on its many inter-connected moving parts working together for optimal performance. Any chink anywhere in the network has a cascading effect on the entire system and brings it down like a house of cards. Automated discovery and monitoring is like a medical device reading the pulse of the body and forewarns against failure and finds the root cause if the damage is already done.

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Leveraging Microsoft SCCM for Strategic IT Decisions

On 02.08.10, In Data Normalization, By Rajesh Kadam

Many enterprises have deployed and depend on Microsoft SCCM or SMS to meet day-to-day operational objectives such as patch management or configuration management. SCCM generates millions of rows of data associated with the hardware and software for any given Windows environment. This data, in its raw form, is overwhelming and unusable when it comes to effective license or asset management.

BDNA has developed a unique service to normalize the SCCM data into a form that is legible and usable with other systems and processes. In addition, once the data is normalized, it is enriched by way of the BDNA Catalog with attributes such as support dates for software, power ratings for hardware and CPU and core information for hardware. Once this process is complete (usually within days), an organization has unobtrusively leveraged their SCCM investment and gained incredibly valuable data to drive projects and initiatives – all without installing yet one more tool in the enterprise.

From a strategic standpoint, the benefits of IT operations data analysis is undeniable. Benefits include lower costs of technical support, faster response to adverse events and reduction in operations costs. Some global banks have reported that the cost of disruptions from change was lowered by 60% over a 12 month period (down to 76 from 190) saving $10 million in costs of service interruptions and productivity losses with an incremental cost of $30,000. Proctor and Gamble reported savings of $500 million which was 10% of its IT budget over a four year period.

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BDNA Submits Paper to SAP Virtualization Week

On 02.02.10, In Other, By Rajesh Kadam

The SAP Virtualization Week has grown over the past few years to become one of the most successful Virtualization and Green IT centric events. It is invitation only community based event and brings together the SAP customers and partner ecosystem. Large SAP customers  as well as Partners will be sharing their experiences.

SAP has called for papers for the conference and there are over 70 submissions. These are open to voting and the most popular ones will be asked to present. BDNA has submitted a proposal titled: “How Greening IT Infrastructure Saved the State of California $44M”.

Here is the link to submit your vote: http://www.sapvweek.com

Since it’s a long list, just search for ‘BDNA’ in case you want to find our submission.

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IT Asset Management: Baselines and Benchmarks for Datacenters

On 02.01.10, In IT Asset Management, By Ido Sarig

IT Asset Management for cost reduction, which has often been an afterthought, has risen to be the top priority for IT investment allocations in 2010. While IT budgets will remain flat in 2010, the share of expenditures on cost reduction and corresponding technologies for consolidation, virtualization and alignment with business will increase by all accounts. The investment on projects for lowering operating costs increased the most by a whooping 19% percentage points from 39% in 2009 to 58% in 2010. Server consolidation and virtualization has been accorded the highest priority at 46% of the allocation. The times call for solutions that help determine the metrics of baseline consumption of resources in data centers and the benchmarks to be achieved.

Companies can find cues for cost control by comparing industry averages with their own metrics. The data for standards for the overall efficiency of the data center are prepared by the Uptime Institute and energy efficiency from the Green Grid. Startling insights are uncovered when the number crunching is completed. The Uptime Institute, for example, revealed that 19 datacenters it surveyed wasted 1.9 watts of electricity for every watt they consume!

The hard work is in measuring the devilish details of baseline numbers of their own data centers. The data, if it collected at all, is manually updated, scattered in the departments who own the specific IT assets and is likely hard to slice and dice. If the measurements are done manually, an expense of 250 hours of work for a facility with 1000 servers is incurred. Without automation of asset discovery and collation of data, the task of estimating the baseline numbers is overwhelming and most companies don’t even try.

Companies can distinguish themselves by using innovative methods for estimating the baselines and the benchmarks. Intel experimented with more granular measurements of energy efficiency than those available from the Green Grid by determining the metrics for individual servers and the impact the consumption of useful energy and workloads have on their capacity utilization. The improvements were dramatic. For the period March 2008 to May 2009, it was able to replace older servers with more efficient new servers so that installed number of servers decreased by 14.2% while the compute capacity (EDA MIPS) increased by 96.4% and energy efficiency (EDA MIPS/kW) increased by 309%!  Without software to automate the measurements and the reporting of data, the servers would have continued to be underutilized.

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Green IT: Measurement and Analysis

On 01.29.10, In Data Centers, Data Normalization, GreenIT, By Ido Sarig

Measurement and analysis of energy utilization is a pre-requisite for energy cost reduction. The challenge today is that the sources of soaring energy costs in data centers and IT networks are lost in the maze of countless servers, storage devices and computing equipment sprawled in the data centers of large corporations. Measurement of the sum total of energy costs, their breakdown by each category of equipment and related software and relationships between the components provides cues for lowering costs.  CIOs hard-pressed by the Great Recession have been startled when the facts of energy consumption are revealed to them. Relief follows shock when they realize they have an opportunity to increase productivity by reorganization of their data centers and networks.

Just how much impact visibility has on energy efficiency decisions was revealed in a survey by The Green Grid, a global alliance of IT companies and professionals seeking to lower energy costs in data centers and business computing ecosystems.  Completed in November 2009, the survey found that 90% of the 151 respondents had taken steps to reduce energy consumption following measurements of their energy consumption. Yes, 90%! A rude awakening for sure, a number that high is otherwise rare in surveys.

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