Tag Archives: Data Management

Managing Information About Data Center Resources

Overview

Nowadays, there is an app for almost everything! Yet, we show little or no regard to what happens behind our shiny little screen until something breaks down and our lives descend to near chaos. That’s the conundrum of IT guys. The truth is that IT solutions are, in many cases, fragile things that need constant care. This is no easy task. In fact, most of the cost and effort involved in IT solutions is maintenance. A million things could go wrong. Words like preventive maintenance, service monitoring, business continuity, and disaster recovery are examples of the different activities done to maximize availability, and expedite troubleshooting. Everyone involved with these activities needs access to resources. Above all, they all need access to information.

What resources are being used?

IT data centers have both physical and digital resources. Physical resources include the facility (i.e. building), utilities, computer hardware (e.g. network switches, cables, servers, storage …etc.), and, also People. Digital resources are much fuzzier to define. A simplistic approach could classify them into data and applications. Each category can be further sub-classified into an entire ontology. The complexity increases when you consider the great number of potential resource types that can be created by combining physical and digital resources. Capturing, storing, and maintaining information about these resources is a big challenge. A lot of information can be retrieved from the resources themselves. Usually, each team responsible for supporting a certain group of resources would store information in spreadsheets and documents. More organized teams would use databases or knowledge management systems. More diligent organizations would have a central repository for everything.
What many fail to capture is the information about how all of these different clusters of resources are interconnected. That is often a much bigger and complex challenge. That information could be either buried deep in these systems (e.g. the username used to run a certain service), or is stored in people’s brains. The added value of an organizing system for data about data center resources can be multiplied if effectively organized information about their interactions.

Why are the resources organized?

Running an IT data center is complex, resource intensive, and risky. Customers require around the clock availability of services with no room for failure. The consequences of such failures go beyond financial loss and customer dissatisfaction. They could affect people’s safety and, even, national security. Cyber threats have become a constant threat for IT service providers, especially those that host highly sensitive data or serve critical operations. People can survive if their emails were inaccessible for an hour. However, what are the ramifications of a total failure of the IT infrastructure of the New York Stock Exchange? What if the airport systems of Heathrow airport failed?
These are some of the conditions that IT data center managers must work in.
Furthermore, technology advances have created highly diverse, complex, and integrated solutions. New resources are introduced frequently as old resources are retired. These activities require careful planning and execution to prevent the intricate eco-system from crashing. Having all the information required to plan these activities would mitigate that risk.

Nevertheless, when something wrong does happen, having the required information is equally important to expedite fixing it. In fact, availability of information increases with the severity of the problem. How can you rebuild a system if you don’t know how to connect its parts?
How much are the resources organized?
The granularity of the data required about data center resources varies between organizations and also between stakeholders of the same organization. The information can be classified into operational, and planning information.
Operational information is required for running day-to-day operations. These include information about resources and how they are interconnected. Many organizations put most of their focus on organizing operational information with high granularity. The granularity could be influenced by economic, political, an intellectual factors. Higher granularity means that more time and money are required to organize the information.
The level of granularity used to describe a resource type can be driven by the motives of the team leading the activity. For example, a hardware systems support team would invest more in building a robust organizing system for hardware systems and not focus on applications running on that hardware. Finally, the team’s intellectual abilities and knowledge would influence the granularity of the system. As the boundaries between physical and digital resources fade, system designers could face some challenging questions. For example, servers are, traditionally, considered hardware resources. However, many organization have switched to virtual servers running on big machines. In such a case, how would you define a server? Is it the big machine or the individual virtual servers? Is it a physical resource or a digital resource? If you have a standby clone of a virtual server, would you consider both to be the same entity or not?

Planning information is usually required to make business decisions and is usually less granular. This could include information about the purchase and maintenance costs, contracts, hardware life-times …etc. Mangers and planners could use this information to better plan for business activities, manage operational and capital costs, and make strategic decisions about the services and products the data center offers.

When are the resources organized?

Many data centers start building an organizing system of data about their resources based on existing resources. In such cases, building the system is the easy part. The real challenge is maintaining the information up-to-date in an ever-changing environment. Clear information life-cycle and change management processes are required in parallel with work processes to ensure information is updated.

Who does the organizing?

Based on the scope and level of granularity of the system, the number of resources could potentially be gargantuan. The organization must try to maximize the amount of information collected automatically using auto discovery ‘agents’ to keep update information. Inevitably, other information, especially information describing interdependencies, will require human entry. The organization must have a clear and comprehensive governance framework that details the roles and responsibilities of different parties in adding, and maintaining information.

Other considerations

Most big companies in the past operated their own corporate data centers. Their organizing system might have a smaller scope. The emergence of global cloud service providers has extended the commoditization of IT products and services across the entire technology landscape; from the consumers all the way back to the servers that provide them. These providers will have a bigger scope due to the diversity and dynamic provisioning of their services. As their