Introduction to Infrastructure Resource Management

Infrastructure resource management (IRM) is a collection of best practices, processes, procedures, technologies, and tools along with the people skill sets and knowledge used to manage IT resources effectively. While there can be areas of overlap, the aim of IRM

Acronym Term Description

CMDB Confi guration management database

IT management repository or knowledge base

DPA Data protection analysis Analysis of data protection activities DPM Data protection management Management of data protection activities

E2E End-to-end From resource to service delivery

IRM Infrastructure resource management

Management of IT resources and service delivery

ITIL IT infrastructure library Processes and methodologies for IT service management

ITSM IT service management IRM functions including service desk MTTM Mean time to migrate How quickly a migration can be done MTTP Mean time to provision How quickly resources are provisioned for use MTBF Mean time between failures Time between failures or downtime

MTTR Mean time to repair/recover How fast a resource or service is restored to use

KPI Key performance indicators IT and IRM service metrics PACE Performance availability

capacity energy or economics

Common application and services attribute characteristics

PCFE Power, cooling, and fl oor space EH&S (environmental

RPO Recovery-point objective Time to which data is protected

RTO Recovery-time objective Time until service or resources will be ready for use

SLA Service-level agreement Agreement for services to be delivered SLO Service-level objective Level of services to be delivered SRA Storage/system resource

analysis

Analysis, correlation, and reporting tools

SRM Storage resource management

May also mean system resource management or VMware Site Recovery Manager tool

Table 3.1 IRM-Related Terms

is to deliver application services and information to meet business service objectives while addressing performance, availability, capacity, and energy (PACE) requirements in a cost-effective manner. IRM can be further broken down into resources manage-ment (e.g., managing servers, storage, I/O and networking hardware, software, and services) and managing services or information delivery. IRM is focused on processes, procedures, hardware, and software tools that facilitate application and data manage-ment tasks. There is some correlation with data managemanage-ment in that many IRM tasks are associated with serving, protecting, and preserving data. For example, data man-agement involves archiving, backup/restore, society, and enabling business continuance (BC) as well as disaster recovery (DR), just as IRM does.

With reference to the idea of an information factory that was introduced in Chapter 1, IRM is a corollary to enterprise resource management (ERM) and enter-prise resource planning (ERP) along with their associated tasks. For a traditional factory to be efficient and support effective business operations, there needs to be plan-ning, analysis, best practices, polices, procedures, workflows, product designs, tools, and measurement metrics. These same ideas apply to information factories and are known collectively as IRM. For those who like the “working smarter” philosophy, IRM can also mean intelligent resource management, whereby business agility and flexibility are enabled while reducing per-unit costs and boosting productivity without compromising services delivery.

Typically, industry messaging around efficiency is centered on consolidation or avoidance, which is part of the effectiveness equation. However, the other parts of becoming more effective—that is, doing more with what you have (or less)—are to reduce waste or rework. The most recent focus of efficiency has been on hardware waste in the form of driving up utilization via consolidation and server virtualization, or data footprint reduction (DFR) using archiving, compression, and deduplication, among other techniques. The next wave of efficiency shifts to boosting productivity for active data and applications, which is more about performance per watt of energy or in a given amount of time or footprint. This also means reducing waste in terms of complex workflow, management paperwork, and the amount of rework, along with out-of-band (exception-handling) tasks that lend themselves to automation.

For example, a factory can run at a high utilization rate to reduce the costs of facili-ties, hardware or software tools, and personnel by producing more goods (e.g., more goods produced per hour per person or tool). However, if a result of that higher utiliza-tion is that the defect and rework rate goes up or measurements are ignored leading to customer dissatisfaction, the improved utilization benefits are negated. This translates to cloud, virtualization, and data storage networking environments in that the associ-ated resources can be driven to higher levels of utilization to show reduced costs, but their effectiveness also needs to be considered.

Traditional IRM has had a paradigm based on hardware and application affinity (dependencies and mappings). Affinity has meant that hardware and software resources may be dedicated to specific applications, lines of business, or other entities. Even in shared networked storage (SAN or NAS) environments, resources may be dedicated while leveraging common infrastructure components. The result can be pockets of technologies, including SAN islands, where some applications may be lacking adequate

resources. At the same time, other applications may have surplus or otherwise available resources that cannot be shared, resulting in lost opportunity. Consequently, effective sharing for load balancing to maximize resource usage and return on investment may not be obtained.

The evolving IRM paradigm is around elasticity, multitenancy, scalability, and flexibility, and it is metered and service-oriented. Service-oriented means a combina-tion of being able to rapidly provide new services while keeping customer experience and satisfaction in mind. Also part of being focused on the customer is to enable orga-nizations to be competitive with outside service offerings while focusing on being more productive and economically efficient.

Part of the process of implementing cloud, virtual, or storage networking is to remove previous barriers and change traditional thinking such as hardware vs. soft-ware, servers vs. storage, storage vs. networking, applications vs. operating systems, and IT equipment vs. facilities. A reality is that hardware cannot exist without software and software cannot exist or function without hardware.

While specific technology domain areas or groups may be focused on their respec-tive areas, interdependencies across IT resource areas are a matter of fact for efficient virtual data centers. For example, provisioning a virtual server relies on configuration and security of the virtual environment, physical servers, storage, and networks, along with associated software and facility-related resources. Similarly, backing up or protect-ing data for an application can involve multiple servers runnprotect-ing different portions of an application, which requires coordination of servers, storage, networks, software, and data protection tasks.

There are many different tasks and activities along with various tools to facilitate managing IT resources across different technology domains. In a virtual data center, many of these tools and technologies take on increased interdependencies due to the reliance on abstracting physical resources to applications and IT services.

Common IRM activities include:

• Audit, accounting, analysis, billing, chargeback

• Backup/restore, business continuance/disaster recovery

• Configuration discovery, remediating, change validation management

• Data footprint reduction (archiving, compression, deduplication)

• Data protection and security (logical and physical)

• Establishment of templates, blueprints, and guides for configuration

• Metering, measuring, reporting, capacity planning

• Migrating data to support technology upgrades, refresh, or consolidation

• Provisioning of resources, troubleshooting, diagnostics

• Service-level agreements, service-level objectives, service delivery management

• Resource analysis, resolution, tuning, capacity planning

IRM tasks also include configuration of physical resources, for example, server and operating systems, applications, utilities, and other software. IRM also is involved in networking and I/O connectivity configuration, along with associated security, high availability, backup/restore, snapshots, replication, RAID, volume groups, and file

system setup. Other IRM tasks include creation or provisioning of virtual entities out of physical resources, including virtual machines (VMs), virtual networking and I/O interfaces, and virtual desktops, along with associated backup/restore capabilities.

Figure 3.2 Information services delivery and IRM stack.