Data Center

Data Center Architecture Design

Architecture Design

Data center design is at an evolutionary crossroads. Massive data growth, challenging economic conditions, and the physical limitations of power, heat, and space are exerting substantial pressure on the enterprise. Finding architectures that can take cost, complexity, and associated risk out of the data center while improving service levels has become a major objective for most enterprises. Consider the challenges facing enterprise IT organizations today.

Data center IT staff is typically asked to address the following data center challenges:
 - Improve asset utilization to reduce or defer capital expenses.
 - Reduce capital expenses through better management of peak workloads.
 - Make data and resources available in real time to provide flexibility and alignment with current and future business agility needs.
 - Reduce power and cooling consumption to cut operational costs and align with "green" business practices.
 - Reduce deployment/churn time for new/existing services, saving operational costs and gaining competitive advantage in the market.
 - Enable/increase innovation through new consumption models and the adoption of new abstraction layers in the architecture.
 - Improve availability of services to avoid or reduce the business impact of unplanned outages or failures of service components.
 - Maintain information assurance through consistent and robust security posture and processes.

Efficiency

Virtualization of infrastructure with appropriate management tools. Infrastructure homogeneity is driving asset utilization up.

Scalability

Platform scalability can be achieved through explicit protocol choice (for example, TRILL) and hardware selection and also through implicit system design and implementation.

Reliability

Disaster recovery (BCP) planning, testing, and operational tools (for example, VMware's Site Recovery Manager, SNAP, or Clone backup capabilities).

Interoperability

Web-based (XML) APIs, for example, WSDL (W3C) using SOAP or the conceptually simpler RESTful protocol with standards compliance semantics, for example, RFC 4741 NETCONF or TMForum's Multi-Technology Operations Systems Interface (MTOSI) with message binding to "concrete" endpoint protocols.

Flexibility

Software abstraction to enable policy-based management of the underlying infrastructure. Use of "meta models" (frames, rules, and constraints of how to build infrastructure). Encourage independence rather than interdependence among functional components of the platform.

Modularity

Commonality of the underlying building blocks that can support scale-out and scale-up heterogeneous workload requirements with common integration points (web-based APIs). That is, integrated compute stacks or infrastructure packages (for example, a Vblock or a FlexPod). Programmatic workflows versus script-based workflows (discussed later in this chapter) along with the aforementioned software abstraction help deliver modularity of software tools.

Security

The appropriate countermeasures (tools, systems, processes, and protocols) relative to risk assessment derived from the threat model. Technology countermeasures are systems based, security in depth. Bespoke implementations/design patterns required to meet varied hosted tenant visibility and control requirements necessitated by regulatory compliance.

Robustness

System design and implementation—tools, methods, processes, and people that assist to mitigate collateral damage of a failure or failures internal to the administratively controlled system or even to external service dependencies to ensure service continuity.